diff --git a/docs/examples/broadcast_tracking_data.ipynb b/docs/examples/broadcast_tracking_data.ipynb
index b6ed5a5a..09aaaa55 100644
--- a/docs/examples/broadcast_tracking_data.ipynb
+++ b/docs/examples/broadcast_tracking_data.ipynb
@@ -32,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "metadata": {
     "scrolled": true
    },
@@ -49,7 +49,7 @@
     "                           raw_data=tracking_file,\n",
     "                           limit=100)\n",
     "\n",
-    "df = dataset.to_pandas()"
+    "df = dataset.to_df()"
    ]
   },
   {
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -89,7 +89,7 @@
        " 'Serge Gnabry (22)']"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -103,7 +103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -135,7 +135,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -173,7 +173,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -199,14 +199,14 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>away_23_x</th>\n",
        "      <th>away_23_y</th>\n",
-       "      <th>away_23_d</th>\n",
-       "      <th>away_23_s</th>\n",
        "      <th>...</th>\n",
        "      <th>away_14_d</th>\n",
        "      <th>away_14_s</th>\n",
@@ -225,14 +225,14 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>11.2</td>\n",
+       "      <td>1523</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>0.747489</td>\n",
        "      <td>0.098509</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -249,14 +249,14 @@
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>11.3</td>\n",
+       "      <td>1524</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.791347</td>\n",
        "      <td>-0.020033</td>\n",
+       "      <td>2.243712</td>\n",
        "      <td>0.745323</td>\n",
        "      <td>0.099367</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -273,14 +273,14 @@
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>11.4</td>\n",
+       "      <td>1525</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.772630</td>\n",
        "      <td>-0.009469</td>\n",
+       "      <td>2.534799</td>\n",
        "      <td>0.742956</td>\n",
        "      <td>0.099743</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -297,14 +297,14 @@
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>11.5</td>\n",
+       "      <td>1526</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.754625</td>\n",
        "      <td>0.001612</td>\n",
+       "      <td>2.659813</td>\n",
        "      <td>0.740386</td>\n",
        "      <td>0.099638</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -321,14 +321,14 @@
        "      <th>4</th>\n",
        "      <td>1</td>\n",
        "      <td>11.6</td>\n",
+       "      <td>1527</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.737330</td>\n",
        "      <td>0.013210</td>\n",
+       "      <td>2.618755</td>\n",
        "      <td>0.737875</td>\n",
        "      <td>0.096646</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -343,42 +343,42 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 90 columns</p>\n",
+       "<p>5 rows × 92 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state  ball_owning_team_id    ball_x    ball_y  \\\n",
-       "0          1       11.2       None                  NaN       NaN       NaN   \n",
-       "1          1       11.3       None                  NaN  0.791347 -0.020033   \n",
-       "2          1       11.4       None                  NaN  0.772630 -0.009469   \n",
-       "3          1       11.5       None                  NaN  0.754625  0.001612   \n",
-       "4          1       11.6       None                  NaN  0.737330  0.013210   \n",
+       "   period_id  timestamp  frame_id ball_state  ball_owning_team_id    ball_x  \\\n",
+       "0          1       11.2      1523       None                  NaN       NaN   \n",
+       "1          1       11.3      1524       None                  NaN  0.791347   \n",
+       "2          1       11.4      1525       None                  NaN  0.772630   \n",
+       "3          1       11.5      1526       None                  NaN  0.754625   \n",
+       "4          1       11.6      1527       None                  NaN  0.737330   \n",
        "\n",
-       "   away_23_x  away_23_y  away_23_d  away_23_s  ...  away_14_d  away_14_s  \\\n",
-       "0   0.747489   0.098509        NaN        NaN  ...        NaN        NaN   \n",
-       "1   0.745323   0.099367        NaN        NaN  ...        NaN        NaN   \n",
-       "2   0.742956   0.099743        NaN        NaN  ...        NaN        NaN   \n",
-       "3   0.740386   0.099638        NaN        NaN  ...        NaN        NaN   \n",
-       "4   0.737875   0.096646        NaN        NaN  ...        NaN        NaN   \n",
+       "     ball_y    ball_z  away_23_x  away_23_y  ...  away_14_d  away_14_s  \\\n",
+       "0       NaN       NaN   0.747489   0.098509  ...        NaN        NaN   \n",
+       "1 -0.020033  2.243712   0.745323   0.099367  ...        NaN        NaN   \n",
+       "2 -0.009469  2.534799   0.742956   0.099743  ...        NaN        NaN   \n",
+       "3  0.001612  2.659813   0.740386   0.099638  ...        NaN        NaN   \n",
+       "4  0.013210  2.618755   0.737875   0.096646  ...        NaN        NaN   \n",
        "\n",
-       "  home_9_x home_9_y  home_9_d  home_9_s home_anon_75_x home_anon_75_y  \\\n",
-       "0      NaN      NaN       NaN       NaN            NaN            NaN   \n",
-       "1      NaN      NaN       NaN       NaN            NaN            NaN   \n",
-       "2      NaN      NaN       NaN       NaN            NaN            NaN   \n",
-       "3      NaN      NaN       NaN       NaN            NaN            NaN   \n",
-       "4      NaN      NaN       NaN       NaN            NaN            NaN   \n",
+       "   home_9_x  home_9_y home_9_d home_9_s  home_anon_75_x  home_anon_75_y  \\\n",
+       "0       NaN       NaN      NaN      NaN             NaN             NaN   \n",
+       "1       NaN       NaN      NaN      NaN             NaN             NaN   \n",
+       "2       NaN       NaN      NaN      NaN             NaN             NaN   \n",
+       "3       NaN       NaN      NaN      NaN             NaN             NaN   \n",
+       "4       NaN       NaN      NaN      NaN             NaN             NaN   \n",
        "\n",
-       "   home_anon_75_d  home_anon_75_s  \n",
-       "0             NaN             NaN  \n",
-       "1             NaN             NaN  \n",
-       "2             NaN             NaN  \n",
-       "3             NaN             NaN  \n",
-       "4             NaN             NaN  \n",
+       "  home_anon_75_d home_anon_75_s  \n",
+       "0            NaN            NaN  \n",
+       "1            NaN            NaN  \n",
+       "2            NaN            NaN  \n",
+       "3            NaN            NaN  \n",
+       "4            NaN            NaN  \n",
        "\n",
-       "[5 rows x 90 columns]"
+       "[5 rows x 92 columns]"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -411,7 +411,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/docs/examples/code_data.ipynb b/docs/examples/code_data.ipynb
index 9e4adcfb..d97228f1 100644
--- a/docs/examples/code_data.ipynb
+++ b/docs/examples/code_data.ipynb
@@ -189,7 +189,7 @@
     }
    ],
    "source": [
-    "code_dataset.to_pandas()"
+    "code_dataset.to_df()"
    ]
   },
   {
@@ -279,7 +279,7 @@
    ],
    "source": [
     "passes = code_dataset.filter(lambda code: code.code == 'PASS')\n",
-    "passes.to_pandas()"
+    "passes.to_df()"
    ]
   },
   {
@@ -359,9 +359,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/kloppy-3.7.1-py3.10.egg/kloppy/_providers/statsbomb.py:67: UserWarning: \n",
+      "\n",
+      "You are about to use StatsBomb public data.\n",
+      "By using this data, you are agreeing to the user agreement. \n",
+      "The user agreement can be found here: https://github.com/statsbomb/open-data/blob/master/LICENSE.pdf\n",
+      "\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
    "source": [
     "from kloppy import statsbomb\n",
     "\n",
@@ -370,7 +384,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -405,7 +419,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -785,18 +799,18 @@
        "27  Lionel Andrés Messi Cuccittini         Barcelona  "
       ]
      },
-     "execution_count": 14,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "code_dataset.to_pandas()"
+    "code_dataset.to_df()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -1213,7 +1227,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1245,7 +1259,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/examples/config.ipynb b/docs/examples/config.ipynb
index ae34daa3..6f78ed7a 100644
--- a/docs/examples/config.ipynb
+++ b/docs/examples/config.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 5,
    "id": "e8979b51",
    "metadata": {},
    "outputs": [],
@@ -32,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "b70b22c9",
    "metadata": {},
    "outputs": [
@@ -41,11 +41,13 @@
       "text/plain": [
        "{'cache': '/Users/koen/kloppy_cache',\n",
        " 'coordinate_system': 'kloppy',\n",
+       " 'event_factory': None,\n",
        " 'adapters.http.basic_authentication': None,\n",
-       " 'adapters.s3.s3fs': None}"
+       " 'adapters.s3.s3fs': None,\n",
+       " 'dataframe.engine': 'pandas'}"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -56,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "id": "9d75b69b",
    "metadata": {},
    "outputs": [
@@ -66,7 +68,7 @@
        "'kloppy'"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -91,6 +93,19 @@
    "id": "1ba6227a",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/kloppy-3.7.1-py3.10.egg/kloppy/_providers/statsbomb.py:67: UserWarning: \n",
+      "\n",
+      "You are about to use StatsBomb public data.\n",
+      "By using this data, you are agreeing to the user agreement. \n",
+      "The user agreement can be found here: https://github.com/statsbomb/open-data/blob/master/LICENSE.pdf\n",
+      "\n",
+      "  warnings.warn(\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -124,7 +139,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 9,
    "id": "6fc5b89c",
    "metadata": {},
    "outputs": [
@@ -137,13 +152,26 @@
       "After context: opta\n"
      ]
     },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/kloppy-3.7.1-py3.10.egg/kloppy/_providers/statsbomb.py:67: UserWarning: \n",
+      "\n",
+      "You are about to use StatsBomb public data.\n",
+      "By using this data, you are agreeing to the user agreement. \n",
+      "The user agreement can be found here: https://github.com/statsbomb/open-data/blob/master/LICENSE.pdf\n",
+      "\n",
+      "  warnings.warn(\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
-       "StatsbombCoordinateSystem(normalized=False, length=120, width=80)"
+       "StatsBombCoordinateSystem(normalized=False, length=120, width=80)"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -175,7 +203,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/examples/event_data.ipynb b/docs/examples/event_data.ipynb
index 60ad712d..10fb241f 100644
--- a/docs/examples/event_data.ipynb
+++ b/docs/examples/event_data.ipynb
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 55,
    "metadata": {
     "scrolled": true
    },
@@ -44,7 +44,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -61,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [
     {
@@ -80,7 +80,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [
     {
@@ -106,7 +106,7 @@
        " 'Marc-André ter Stegen (1)']"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 58,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -117,7 +117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [
     {
@@ -126,7 +126,7 @@
        "'statsbomb team id: 217 - 206'"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 59,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -138,7 +138,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [
     {
@@ -164,7 +164,7 @@
        " 'Marc-André ter Stegen id=20055']"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 60,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -176,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
@@ -206,7 +206,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
@@ -265,7 +265,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
@@ -301,18 +301,32 @@
    "source": [
     "## Use metadata when transforming to pandas dataframe\n",
     "\n",
-    "The metadata can also be used when transforming a dataset to a pandas dataframe. The `additional_columns` argument should be passed to `to_pandas`. "
+    "The metadata can also be used when transforming a dataset to a pandas dataframe. Using keyword argument additional columns can be created."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div><div id=215c8bb1-4d71-48a9-b3e4-a9769c87f596 style=\"display:none; background-color:#9D6CFF; color:white; width:200px; height:30px; padding-left:5px; border-radius:4px; flex-direction:row; justify-content:space-around; align-items:center;\" onmouseover=\"this.style.backgroundColor='#BA9BF8'\" onmouseout=\"this.style.backgroundColor='#9D6CFF'\" onclick=\"window.commands?.execute('create-mitosheet-from-dataframe-output');\">See Full Dataframe in Mito</div> <script> if (window.commands?.hasCommand('create-mitosheet-from-dataframe-output')) document.getElementById('215c8bb1-4d71-48a9-b3e4-a9769c87f596').style.display = 'flex' </script> <table border=\"1\" class=\"dataframe\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
@@ -377,7 +391,8 @@
        "      <td>Barcelona</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
-       "</table></div>"
+       "</table>\n",
+       "</div>"
       ],
       "text/plain": [
        "                               event_id event_type      result  timestamp  \\\n",
@@ -395,18 +410,17 @@
        "4      5477                   Ousmane Dembélé         Barcelona  "
       ]
      },
-     "execution_count": 37,
+     "execution_count": 64,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "\n",
-    "dataframe = dataset.to_pandas(\n",
-    "    additional_columns={\n",
-    "        'player_name': lambda event: str(event.player),\n",
-    "        'team_name': lambda event: str(event.player.team)\n",
-    "    }\n",
+    "dataframe = dataset.to_df(\n",
+    "    \"*\",  # Get all default columns\n",
+    "    player_name=lambda event: str(event.player),\n",
+    "    team_name=lambda event: str(event.player.team)\n",
     ")\n",
     "\n",
     "dataframe[[\n",
@@ -426,13 +440,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div><div id=24c550d6-6c0c-4bb4-a148-411a684dd3e2 style=\"display:none; background-color:#9D6CFF; color:white; width:200px; height:30px; padding-left:5px; border-radius:4px; flex-direction:row; justify-content:space-around; align-items:center;\" onmouseover=\"this.style.backgroundColor='#BA9BF8'\" onmouseout=\"this.style.backgroundColor='#9D6CFF'\" onclick=\"window.commands?.execute('create-mitosheet-from-dataframe-output');\">See Full Dataframe in Mito</div> <script> if (window.commands?.hasCommand('create-mitosheet-from-dataframe-output')) document.getElementById('24c550d6-6c0c-4bb4-a148-411a684dd3e2').style.display = 'flex' </script> <table border=\"1\" class=\"dataframe\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
@@ -497,7 +525,9 @@
        "      <td>9.721368</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
-       "</table></div>"
+       "</table>\n",
+       "<p>1160 rows × 2 columns</p>\n",
+       "</div>"
       ],
       "text/plain": [
        "      angle_to_goal  distance_to_goal\n",
@@ -516,7 +546,7 @@
        "[1160 rows x 2 columns]"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 65,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -541,7 +571,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
@@ -557,7 +587,7 @@
        "{'angle_to_goal': 90.48146580583835}"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 66,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -584,13 +614,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div><div id=d3fe7f8d-1308-4602-9315-2e25e4a97a97 style=\"display:none; background-color:#9D6CFF; color:white; width:200px; height:30px; padding-left:5px; border-radius:4px; flex-direction:row; justify-content:space-around; align-items:center;\" onmouseover=\"this.style.backgroundColor='#BA9BF8'\" onmouseout=\"this.style.backgroundColor='#9D6CFF'\" onclick=\"window.commands?.execute('create-mitosheet-from-dataframe-output');\">See Full Dataframe in Mito</div> <script> if (window.commands?.hasCommand('create-mitosheet-from-dataframe-output')) document.getElementById('d3fe7f8d-1308-4602-9315-2e25e4a97a97').style.display = 'flex' </script> <table border=\"1\" class=\"dataframe\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
@@ -703,7 +747,9 @@
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
-       "</table></div>"
+       "</table>\n",
+       "<p>1160 rows × 6 columns</p>\n",
+       "</div>"
       ],
       "text/plain": [
        "      period_id  timestamp  coordinates_x  coordinates_y  end_coordinates_x  \\\n",
@@ -735,7 +781,7 @@
        "[1160 rows x 6 columns]"
       ]
      },
-     "execution_count": 40,
+     "execution_count": 67,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -761,13 +807,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 68,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div><div id=6140a131-abf3-4942-b7cc-ff00fde97a16 style=\"display:none; background-color:#9D6CFF; color:white; width:200px; height:30px; padding-left:5px; border-radius:4px; flex-direction:row; justify-content:space-around; align-items:center;\" onmouseover=\"this.style.backgroundColor='#BA9BF8'\" onmouseout=\"this.style.backgroundColor='#9D6CFF'\" onclick=\"window.commands?.execute('create-mitosheet-from-dataframe-output');\">See Full Dataframe in Mito</div> <script> if (window.commands?.hasCommand('create-mitosheet-from-dataframe-output')) document.getElementById('6140a131-abf3-4942-b7cc-ff00fde97a16').style.display = 'flex' </script> <table border=\"1\" class=\"dataframe\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
@@ -783,35 +843,35 @@
        "      <td>1</td>\n",
        "      <td>0.098</td>\n",
        "      <td>1234</td>\n",
-       "      <td>3</td>\n",
+       "      <td>62</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>3.497</td>\n",
        "      <td>1234</td>\n",
-       "      <td>243</td>\n",
+       "      <td>252</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>6.785</td>\n",
        "      <td>1234</td>\n",
-       "      <td>74</td>\n",
+       "      <td>194</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>8.431</td>\n",
        "      <td>1234</td>\n",
-       "      <td>237</td>\n",
+       "      <td>121</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>1</td>\n",
        "      <td>10.433</td>\n",
        "      <td>1234</td>\n",
-       "      <td>165</td>\n",
+       "      <td>161</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -825,57 +885,59 @@
        "      <td>2</td>\n",
        "      <td>2787.914</td>\n",
        "      <td>1234</td>\n",
-       "      <td>79</td>\n",
+       "      <td>230</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1156</th>\n",
        "      <td>2</td>\n",
        "      <td>2791.395</td>\n",
        "      <td>1234</td>\n",
-       "      <td>252</td>\n",
+       "      <td>153</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1157</th>\n",
        "      <td>2</td>\n",
        "      <td>2795.127</td>\n",
        "      <td>1234</td>\n",
-       "      <td>197</td>\n",
+       "      <td>151</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1158</th>\n",
        "      <td>2</td>\n",
        "      <td>2798.906</td>\n",
        "      <td>1234</td>\n",
-       "      <td>54</td>\n",
+       "      <td>160</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1159</th>\n",
        "      <td>2</td>\n",
        "      <td>2802.770</td>\n",
        "      <td>1234</td>\n",
-       "      <td>59</td>\n",
+       "      <td>242</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
-       "</table></div>"
+       "</table>\n",
+       "<p>1160 rows × 4 columns</p>\n",
+       "</div>"
       ],
       "text/plain": [
        "      period  timestamp  some_columns  other_column\n",
-       "0          1      0.098          1234             3\n",
-       "1          1      3.497          1234           243\n",
-       "2          1      6.785          1234            74\n",
-       "3          1      8.431          1234           237\n",
-       "4          1     10.433          1234           165\n",
+       "0          1      0.098          1234            62\n",
+       "1          1      3.497          1234           252\n",
+       "2          1      6.785          1234           194\n",
+       "3          1      8.431          1234           121\n",
+       "4          1     10.433          1234           161\n",
        "...      ...        ...           ...           ...\n",
-       "1155       2   2787.914          1234            79\n",
-       "1156       2   2791.395          1234           252\n",
-       "1157       2   2795.127          1234           197\n",
-       "1158       2   2798.906          1234            54\n",
-       "1159       2   2802.770          1234            59\n",
+       "1155       2   2787.914          1234           230\n",
+       "1156       2   2791.395          1234           153\n",
+       "1157       2   2795.127          1234           151\n",
+       "1158       2   2798.906          1234           160\n",
+       "1159       2   2802.770          1234           242\n",
        "\n",
        "[1160 rows x 4 columns]"
       ]
      },
-     "execution_count": 41,
+     "execution_count": 68,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -906,25 +968,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 69,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[{'period': 1, 'timestamp': 0.098, 'some_columns': 1234, 'other_column': 33},\n",
-       " {'period': 1, 'timestamp': 3.497, 'some_columns': 1234, 'other_column': 98},\n",
-       " {'period': 1, 'timestamp': 6.785, 'some_columns': 1234, 'other_column': 64},\n",
-       " {'period': 1, 'timestamp': 8.431, 'some_columns': 1234, 'other_column': 171},\n",
-       " {'period': 1, 'timestamp': 10.433, 'some_columns': 1234, 'other_column': 56},\n",
-       " {'period': 1, 'timestamp': 11.15, 'some_columns': 1234, 'other_column': 179},\n",
-       " {'period': 1, 'timestamp': 24.687, 'some_columns': 1234, 'other_column': 251},\n",
-       " {'period': 1, 'timestamp': 30.008, 'some_columns': 1234, 'other_column': 20},\n",
-       " {'period': 1, 'timestamp': 34.738, 'some_columns': 1234, 'other_column': 218},\n",
-       " {'period': 1, 'timestamp': 37.467, 'some_columns': 1234, 'other_column': 255}]"
+       "[{'period': 1, 'timestamp': 0.098, 'some_columns': 1234, 'other_column': 42},\n",
+       " {'period': 1, 'timestamp': 3.497, 'some_columns': 1234, 'other_column': 72},\n",
+       " {'period': 1, 'timestamp': 6.785, 'some_columns': 1234, 'other_column': 135},\n",
+       " {'period': 1, 'timestamp': 8.431, 'some_columns': 1234, 'other_column': 100},\n",
+       " {'period': 1, 'timestamp': 10.433, 'some_columns': 1234, 'other_column': 193},\n",
+       " {'period': 1, 'timestamp': 11.15, 'some_columns': 1234, 'other_column': 64},\n",
+       " {'period': 1, 'timestamp': 24.687, 'some_columns': 1234, 'other_column': 22},\n",
+       " {'period': 1, 'timestamp': 30.008, 'some_columns': 1234, 'other_column': 157},\n",
+       " {'period': 1, 'timestamp': 34.738, 'some_columns': 1234, 'other_column': 73},\n",
+       " {'period': 1, 'timestamp': 37.467, 'some_columns': 1234, 'other_column': 226}]"
       ]
      },
-     "execution_count": 42,
+     "execution_count": 69,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -954,13 +1016,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div><div id=1e19e77d-1fa2-4b10-b292-cafa935b6578 style=\"display:none; background-color:#9D6CFF; color:white; width:200px; height:30px; padding-left:5px; border-radius:4px; flex-direction:row; justify-content:space-around; align-items:center;\" onmouseover=\"this.style.backgroundColor='#BA9BF8'\" onmouseout=\"this.style.backgroundColor='#9D6CFF'\" onclick=\"window.commands?.execute('create-mitosheet-from-dataframe-output');\">See Full Dataframe in Mito</div> <script> if (window.commands?.hasCommand('create-mitosheet-from-dataframe-output')) document.getElementById('1e19e77d-1fa2-4b10-b292-cafa935b6578').style.display = 'flex' </script> <table border=\"1\" class=\"dataframe\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
@@ -1001,10 +1077,112 @@
        "      <td>1095.914</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
+       "      <th>5</th>\n",
+       "      <td>0.089920</td>\n",
+       "      <td>Ousmane Dembélé</td>\n",
+       "      <td>1842.287</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>0.071365</td>\n",
+       "      <td>Ivan Rakitić</td>\n",
+       "      <td>2104.861</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0.078886</td>\n",
+       "      <td>Lionel Andrés Messi Cuccittini</td>\n",
+       "      <td>2248.168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>0.171218</td>\n",
+       "      <td>Gerard Piqué Bernabéu</td>\n",
+       "      <td>2250.989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>0.226095</td>\n",
+       "      <td>Ousmane Dembélé</td>\n",
+       "      <td>2308.083</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>0.257290</td>\n",
+       "      <td>Luis Alberto Suárez Díaz</td>\n",
+       "      <td>2434.592</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>0.145402</td>\n",
+       "      <td>Ousmane Dembélé</td>\n",
+       "      <td>2610.612</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0.143644</td>\n",
+       "      <td>Jordi Alba Ramos</td>\n",
+       "      <td>2864.792</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>0.034266</td>\n",
+       "      <td>Mubarak Wakaso</td>\n",
+       "      <td>3072.668</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>0.018334</td>\n",
+       "      <td>Luis Alberto Suárez Díaz</td>\n",
+       "      <td>3239.623</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>0.014615</td>\n",
+       "      <td>Philippe Coutinho Correia</td>\n",
+       "      <td>3301.656</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>0.039418</td>\n",
+       "      <td>Jordi Alba Ramos</td>\n",
+       "      <td>3339.758</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>0.026228</td>\n",
+       "      <td>Lionel Andrés Messi Cuccittini</td>\n",
+       "      <td>3446.115</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>0.031532</td>\n",
+       "      <td>Philippe Coutinho Correia</td>\n",
+       "      <td>3641.424</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>0.137812</td>\n",
+       "      <td>Lionel Andrés Messi Cuccittini</td>\n",
+       "      <td>3797.222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>0.081403</td>\n",
+       "      <td>Lionel Andrés Messi Cuccittini</td>\n",
+       "      <td>3948.856</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>0.009953</td>\n",
+       "      <td>Ivan Rakitić</td>\n",
+       "      <td>4118.643</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>0.337188</td>\n",
+       "      <td>Luis Alberto Suárez Díaz</td>\n",
+       "      <td>4352.760</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23</th>\n",
@@ -1037,7 +1215,8 @@
        "      <td>5508.038</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
-       "</table></div>"
+       "</table>\n",
+       "</div>"
       ],
       "text/plain": [
        "    statsbomb_xg                          player  timestamp\n",
@@ -1071,7 +1250,7 @@
        "27      0.289481  Lionel Andrés Messi Cuccittini   5508.038"
       ]
      },
-     "execution_count": 43,
+     "execution_count": 70,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1117,7 +1296,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1129,7 +1308,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1138,14 +1317,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 73,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -1153,13 +1332,15 @@
     }
    ],
    "source": [
+    "# You might need to install mplsoccer package\n",
+    "# %pip install mplsoccer\n",
+    "\n",
     "from mplsoccer.pitch import Pitch\n",
     "\n",
     "home_team = dataset.metadata.teams[0]\n",
     "\n",
-    "pitch = Pitch(pitch_type='statsbomb', orientation='horizontal',\n",
-    "              pitch_color='white', line_color='#c7d5cc', figsize=(16, 11),\n",
-    "              constrained_layout=True, tight_layout=False)\n",
+    "pitch = Pitch(pitch_type='statsbomb',\n",
+    "              pitch_color='white', line_color='#c7d5cc')\n",
     "fig, ax = pitch.draw()\n",
     "\n",
     "def get_color(player):\n",
@@ -1179,6 +1360,13 @@
     "\n",
     "_ = pitch.scatter(x, y, color=color, ax=ax)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -1197,7 +1385,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/docs/examples/navigating.ipynb b/docs/examples/navigating.ipynb
index 9643eac8..d4186e92 100644
--- a/docs/examples/navigating.ipynb
+++ b/docs/examples/navigating.ipynb
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 1,
    "id": "c910dd35",
    "metadata": {},
    "outputs": [
@@ -30,7 +30,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages/kloppy-3.2.0-py3.8.egg/kloppy/_providers/statsbomb.py:46: UserWarning: \n",
+      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/kloppy-3.7.1-py3.10.egg/kloppy/_providers/statsbomb.py:67: UserWarning: \n",
       "\n",
       "You are about to use StatsBomb public data.\n",
       "By using this data, you are agreeing to the user agreement. \n",
@@ -162,7 +162,7 @@
        "2      LEFT_FOOT  "
       ]
      },
-     "execution_count": 5,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -177,7 +177,7 @@
     "filtered_dataset = dataset.filter('shot.goal')\n",
     "\n",
     "# Show the results\n",
-    "filtered_dataset.to_pandas()"
+    "filtered_dataset.to_df()"
    ]
   },
   {
@@ -190,7 +190,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 2,
    "id": "57aac560",
    "metadata": {},
    "outputs": [
@@ -200,7 +200,7 @@
        "0"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -220,7 +220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 3,
    "id": "45de2f06",
    "metadata": {},
    "outputs": [
@@ -230,7 +230,7 @@
        "1132"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -250,17 +250,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 4,
    "id": "2df283f7",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<ShotEvent event_id='65f16e50-7c5d-4293-b2fc-d20887a772f9' time='P1T02:29' player='Lionel Andrés Messi Cuccittini' result='OFF_TARGET'>"
+       "<StatsBombShotEvent event_id='65f16e50-7c5d-4293-b2fc-d20887a772f9' time='P1T02:29' player='Lionel Andrés Messi Cuccittini' result='OFF_TARGET'>"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -271,7 +271,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 5,
    "id": "7c432ca0",
    "metadata": {},
    "outputs": [
@@ -301,17 +301,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 6,
    "id": "31fd93a8",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/kloppy-3.7.1-py3.10.egg/kloppy/_providers/statsbomb.py:67: UserWarning: \n",
+      "\n",
+      "You are about to use StatsBomb public data.\n",
+      "By using this data, you are agreeing to the user agreement. \n",
+      "The user agreement can be found here: https://github.com/statsbomb/open-data/blob/master/LICENSE.pdf\n",
+      "\n",
+      "  warnings.warn(\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
-       "<ShotEvent event_id='4c7c4ab1-6b9f-4504-a237-249c2e0c549f' time='P2T18:12' player='Lionel Andrés Messi Cuccittini' result='GOAL'>"
+       "<StatsBombShotEvent event_id='4c7c4ab1-6b9f-4504-a237-249c2e0c549f' time='P2T18:12' player='Lionel Andrés Messi Cuccittini' result='GOAL'>"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -326,7 +339,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 7,
    "id": "98dda35c",
    "metadata": {},
    "outputs": [
@@ -335,7 +348,7 @@
      "output_type": "stream",
      "text": [
       "<GenericEvent:Foul Won event_id='eed04441-624f-4f23-9843-7bd069c16232' time='P2T17:02' player='Lionel Andrés Messi Cuccittini' result='None'>\n",
-      "<ShotEvent event_id='4c7c4ab1-6b9f-4504-a237-249c2e0c549f' time='P2T18:12' player='Lionel Andrés Messi Cuccittini' result='GOAL'>\n",
+      "<StatsBombShotEvent event_id='4c7c4ab1-6b9f-4504-a237-249c2e0c549f' time='P2T18:12' player='Lionel Andrés Messi Cuccittini' result='GOAL'>\n",
       "<GenericEvent:Goal Keeper event_id='5080ad86-383c-40c5-b718-508d8c9be454' time='P2T18:13' player='Fernando Pacheco Flores' result='None'>\n"
      ]
     }
@@ -357,17 +370,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 8,
    "id": "841fa959",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<PassEvent event_id='df4a42e4-e5d3-4573-853a-604e46a588d4' time='P2T16:58' player='Ivan Rakitić' result='COMPLETE'>"
+       "<StatsBombPassEvent event_id='df4a42e4-e5d3-4573-853a-604e46a588d4' time='P2T16:58' player='Ivan Rakitić' result='COMPLETE'>"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -386,7 +399,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 9,
    "id": "16aad417",
    "metadata": {},
    "outputs": [
@@ -396,7 +409,7 @@
        "<CarryEvent event_id='95bded73-4861-4374-99cf-2a278ff07ea6' time='P2T17:02' player='Lionel Andrés Messi Cuccittini' result='COMPLETE'>"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -420,7 +433,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 10,
    "id": "963e687d",
    "metadata": {},
    "outputs": [
@@ -433,7 +446,7 @@
        " <GenericEvent:Foul Won event_id='eed04441-624f-4f23-9843-7bd069c16232' time='P2T17:02' player='Lionel Andrés Messi Cuccittini' result='None'>]"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -445,7 +458,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 11,
    "id": "7d2c3377",
    "metadata": {},
    "outputs": [
@@ -463,7 +476,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 12,
    "id": "3e53ee99",
    "metadata": {},
    "outputs": [
@@ -504,7 +517,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/examples/plotting.ipynb b/docs/examples/plotting.ipynb
index 819ffc26..3a65f6b5 100644
--- a/docs/examples/plotting.ipynb
+++ b/docs/examples/plotting.ipynb
@@ -23,50 +23,30 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Collecting mplsoccer\n",
-      "  Downloading mplsoccer-1.0.5.tar.gz (57 kB)\n",
-      "\u001b[K     |████████████████████████████████| 57 kB 1.4 MB/s eta 0:00:01\n",
-      "\u001b[?25hCollecting matplotlib\n",
-      "  Downloading matplotlib-3.5.1-cp38-cp38-macosx_11_0_arm64.whl (7.2 MB)\n",
-      "\u001b[K     |████████████████████████████████| 7.2 MB 666 kB/s eta 0:00:01\n",
-      "\u001b[?25hCollecting seaborn\n",
-      "  Downloading seaborn-0.11.2-py3-none-any.whl (292 kB)\n",
-      "\u001b[K     |████████████████████████████████| 292 kB 795 kB/s eta 0:00:01\n",
-      "\u001b[?25hCollecting scipy\n",
-      "  Downloading scipy-1.7.3-1-cp38-cp38-macosx_12_0_arm64.whl (26.9 MB)\n",
-      "\u001b[K     |████████████████████████████████| 26.9 MB 1.3 MB/s eta 0:00:01\n",
-      "\u001b[?25hRequirement already satisfied: pandas in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages (from mplsoccer) (1.3.5)\n",
-      "Collecting pillow\n",
-      "  Downloading Pillow-8.4.0-cp38-cp38-macosx_11_0_arm64.whl (2.8 MB)\n",
-      "\u001b[K     |████████████████████████████████| 2.8 MB 1.2 MB/s eta 0:00:01\n",
-      "\u001b[?25hRequirement already satisfied: numpy in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages (from mplsoccer) (1.21.4)\n",
-      "Collecting beautifulsoup4\n",
-      "  Downloading beautifulsoup4-4.10.0-py3-none-any.whl (97 kB)\n",
-      "\u001b[K     |████████████████████████████████| 97 kB 1.1 MB/s eta 0:00:01\n",
-      "\u001b[?25hRequirement already satisfied: python-dateutil>=2.7 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages (from matplotlib) (2.8.2)\n",
-      "Collecting fonttools>=4.22.0\n",
-      "  Downloading fonttools-4.28.5-py3-none-any.whl (890 kB)\n",
-      "\u001b[K     |████████████████████████████████| 890 kB 630 kB/s eta 0:00:01\n",
-      "\u001b[?25hCollecting cycler>=0.10\n",
-      "  Downloading cycler-0.11.0-py3-none-any.whl (6.4 kB)\n",
-      "Requirement already satisfied: packaging>=20.0 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages (from matplotlib) (21.3)\n",
-      "Requirement already satisfied: pyparsing>=2.2.1 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages (from matplotlib) (3.0.6)\n",
-      "Collecting kiwisolver>=1.0.1\n",
-      "  Downloading kiwisolver-1.3.2-cp38-cp38-macosx_11_0_arm64.whl (59 kB)\n",
-      "\u001b[K     |████████████████████████████████| 59 kB 1.3 MB/s eta 0:00:01\n",
-      "\u001b[?25hRequirement already satisfied: six>=1.5 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
-      "Requirement already satisfied: pytz>=2017.3 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages (from pandas->mplsoccer) (2021.3)\n",
-      "Collecting soupsieve>1.2\n",
-      "  Downloading soupsieve-2.3.1-py3-none-any.whl (37 kB)\n",
-      "Building wheels for collected packages: mplsoccer\n",
-      "  Building wheel for mplsoccer (setup.py) ... \u001b[?25ldone\n",
-      "\u001b[?25h  Created wheel for mplsoccer: filename=mplsoccer-1.0.5-py3-none-any.whl size=62945 sha256=16994e8b7249911aca813d3ad2e701c61450199c86ba47a3ceab2c4b4201f639\n",
-      "  Stored in directory: /Users/koen/Library/Caches/pip/wheels/9d/00/80/238af6bc002b4ab5163484f1584ff6b9e795b8b1a33463768d\n",
-      "Successfully built mplsoccer\n",
-      "Installing collected packages: pillow, kiwisolver, fonttools, cycler, soupsieve, scipy, matplotlib, seaborn, beautifulsoup4, mplsoccer\n",
-      "Successfully installed beautifulsoup4-4.10.0 cycler-0.11.0 fonttools-4.28.5 kiwisolver-1.3.2 matplotlib-3.5.1 mplsoccer-1.0.5 pillow-8.4.0 scipy-1.7.3 seaborn-0.11.2 soupsieve-2.3.1\n",
-      "\u001b[33mWARNING: You are using pip version 21.1.2; however, version 21.3.1 is available.\n",
-      "You should consider upgrading via the '/Users/koen/Developer/Projects/PySport/kloppy/.venv/bin/python -m pip install --upgrade pip' command.\u001b[0m\n"
+      "Requirement already satisfied: mplsoccer in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (1.1.10)\n",
+      "Requirement already satisfied: matplotlib in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (3.7.1)\n",
+      "Requirement already satisfied: seaborn in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (0.12.2)\n",
+      "Requirement already satisfied: scipy in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from mplsoccer) (1.10.1)\n",
+      "Requirement already satisfied: pillow in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from mplsoccer) (9.4.0)\n",
+      "Requirement already satisfied: requests in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/requests-2.28.2-py3.10.egg (from mplsoccer) (2.28.2)\n",
+      "Requirement already satisfied: numpy in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from mplsoccer) (1.24.2)\n",
+      "Requirement already satisfied: pandas in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from mplsoccer) (1.5.3)\n",
+      "Requirement already satisfied: fonttools>=4.22.0 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from matplotlib) (4.38.0)\n",
+      "Requirement already satisfied: packaging>=20.0 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from matplotlib) (23.0)\n",
+      "Requirement already satisfied: pyparsing>=2.3.1 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from matplotlib) (3.0.9)\n",
+      "Requirement already satisfied: python-dateutil>=2.7 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/python_dateutil-2.8.2-py3.10.egg (from matplotlib) (2.8.2)\n",
+      "Requirement already satisfied: cycler>=0.10 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from matplotlib) (0.11.0)\n",
+      "Requirement already satisfied: contourpy>=1.0.1 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from matplotlib) (1.0.7)\n",
+      "Requirement already satisfied: kiwisolver>=1.0.1 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages (from matplotlib) (1.4.4)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/pytz-2022.7.1-py3.10.egg (from pandas->mplsoccer) (2022.7.1)\n",
+      "Requirement already satisfied: six>=1.5 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/six-1.16.0-py3.10.egg (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/charset_normalizer-3.0.1-py3.10-macosx-12-arm64.egg (from requests->mplsoccer) (3.0.1)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/idna-3.4-py3.10.egg (from requests->mplsoccer) (3.4)\n",
+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/urllib3-1.26.14-py3.10.egg (from requests->mplsoccer) (1.26.14)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/certifi-2022.12.7-py3.10.egg (from requests->mplsoccer) (2022.12.7)\n",
+      "\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.0.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
      ]
     }
    ],
@@ -77,7 +57,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -112,9 +92,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -125,7 +105,7 @@
     "df = (\n",
     "    dataset\n",
     "    .filter(lambda event: event.player == messi)\n",
-    "    .to_pandas()\n",
+    "    .to_df()\n",
     ")\n",
     "\n",
     "\n",
@@ -135,7 +115,7 @@
     "    df[\"coordinates_x\"],\n",
     "    df[\"coordinates_y\"],\n",
     "    ax=ax,\n",
-    "    shade=True,\n",
+    "    fill=True,\n",
     "    n_levels=50,\n",
     ")"
    ]
@@ -164,7 +144,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/docs/examples/state.ipynb b/docs/examples/state.ipynb
index 42760224..32226afe 100644
--- a/docs/examples/state.ipynb
+++ b/docs/examples/state.ipynb
@@ -17,9 +17,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/kloppy-3.7.1-py3.10.egg/kloppy/_providers/statsbomb.py:67: UserWarning: \n",
+      "\n",
+      "You are about to use StatsBomb public data.\n",
+      "By using this data, you are agreeing to the user agreement. \n",
+      "The user agreement can be found here: https://github.com/statsbomb/open-data/blob/master/LICENSE.pdf\n",
+      "\n",
+      "  warnings.warn(\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -49,7 +62,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -58,7 +71,7 @@
        "{'score': Score(home=0, away=0)}"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -80,7 +93,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -89,7 +102,7 @@
        "28"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -102,41 +115,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Jordi Alba Ramos - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - ShotResult.SAVED\n",
-      "0-0 Deportivo Alavés - Rubén Sobrino Pozuelo - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Luis Alberto Suárez Díaz - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Ousmane Dembélé - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Ivan Rakitić - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - ShotResult.POST\n",
-      "0-0 Barcelona - Gerard Piqué Bernabéu - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Ousmane Dembélé - ShotResult.SAVED\n",
-      "0-0 Barcelona - Luis Alberto Suárez Díaz - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Ousmane Dembélé - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Jordi Alba Ramos - ShotResult.SAVED\n",
-      "0-0 Deportivo Alavés - Mubarak Wakaso - ShotResult.BLOCKED\n",
-      "0-0 Barcelona - Luis Alberto Suárez Díaz - ShotResult.BLOCKED\n",
-      "0-0 Barcelona - Philippe Coutinho Correia - ShotResult.BLOCKED\n",
-      "0-0 Barcelona - Jordi Alba Ramos - ShotResult.BLOCKED\n",
-      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - ShotResult.OFF_TARGET\n",
-      "0-0 Barcelona - Philippe Coutinho Correia - ShotResult.BLOCKED\n",
-      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - ShotResult.GOAL\n",
-      "1-0 Barcelona - Lionel Andrés Messi Cuccittini - ShotResult.POST\n",
-      "1-0 Barcelona - Ivan Rakitić - ShotResult.BLOCKED\n",
-      "1-0 Barcelona - Luis Alberto Suárez Díaz - ShotResult.SAVED\n",
-      "1-0 Deportivo Alavés - Adrián Marín Gómez - ShotResult.OFF_TARGET\n",
-      "1-0 Barcelona - Philippe Coutinho Correia - ShotResult.SAVED\n",
-      "1-0 Barcelona - Philippe Coutinho Correia - ShotResult.GOAL\n",
-      "2-0 Barcelona - Lionel Andrés Messi Cuccittini - ShotResult.SAVED\n",
-      "2-0 Barcelona - Lionel Andrés Messi Cuccittini - ShotResult.GOAL\n"
+      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - OFF_TARGET\n",
+      "0-0 Barcelona - Jordi Alba Ramos - OFF_TARGET\n",
+      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - SAVED\n",
+      "0-0 Deportivo Alavés - Rubén Sobrino Pozuelo - OFF_TARGET\n",
+      "0-0 Barcelona - Luis Alberto Suárez Díaz - OFF_TARGET\n",
+      "0-0 Barcelona - Ousmane Dembélé - OFF_TARGET\n",
+      "0-0 Barcelona - Ivan Rakitić - OFF_TARGET\n",
+      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - POST\n",
+      "0-0 Barcelona - Gerard Piqué Bernabéu - OFF_TARGET\n",
+      "0-0 Barcelona - Ousmane Dembélé - SAVED\n",
+      "0-0 Barcelona - Luis Alberto Suárez Díaz - OFF_TARGET\n",
+      "0-0 Barcelona - Ousmane Dembélé - OFF_TARGET\n",
+      "0-0 Barcelona - Jordi Alba Ramos - SAVED\n",
+      "0-0 Deportivo Alavés - Mubarak Wakaso - BLOCKED\n",
+      "0-0 Barcelona - Luis Alberto Suárez Díaz - BLOCKED\n",
+      "0-0 Barcelona - Philippe Coutinho Correia - BLOCKED\n",
+      "0-0 Barcelona - Jordi Alba Ramos - BLOCKED\n",
+      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - OFF_TARGET\n",
+      "0-0 Barcelona - Philippe Coutinho Correia - BLOCKED\n",
+      "0-0 Barcelona - Lionel Andrés Messi Cuccittini - GOAL\n",
+      "1-0 Barcelona - Lionel Andrés Messi Cuccittini - POST\n",
+      "1-0 Barcelona - Ivan Rakitić - BLOCKED\n",
+      "1-0 Barcelona - Luis Alberto Suárez Díaz - SAVED\n",
+      "1-0 Deportivo Alavés - Adrián Marín Gómez - OFF_TARGET\n",
+      "1-0 Barcelona - Philippe Coutinho Correia - SAVED\n",
+      "1-0 Barcelona - Philippe Coutinho Correia - GOAL\n",
+      "2-0 Barcelona - Lionel Andrés Messi Cuccittini - SAVED\n",
+      "2-0 Barcelona - Lionel Andrés Messi Cuccittini - GOAL\n"
      ]
     }
    ],
@@ -147,7 +160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -189,7 +202,6 @@
        "      <th>body_part_type</th>\n",
        "      <th>home_score</th>\n",
        "      <th>away_score</th>\n",
-       "      <th>set_piece_type</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -213,7 +225,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -235,7 +246,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -257,7 +267,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -279,7 +288,6 @@
        "      <td>HEAD</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -301,7 +309,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
@@ -323,7 +330,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
@@ -345,7 +351,6 @@
        "      <td>HEAD</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
@@ -367,7 +372,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>FREE_KICK</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
@@ -389,7 +393,6 @@
        "      <td>HEAD</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
@@ -411,7 +414,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
@@ -433,7 +435,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
@@ -455,7 +456,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
@@ -477,7 +477,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
@@ -499,7 +498,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
@@ -521,7 +519,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
@@ -543,7 +540,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
@@ -565,7 +561,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
@@ -587,7 +582,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
@@ -609,7 +603,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
@@ -631,7 +624,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>FREE_KICK</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
@@ -653,7 +645,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21</th>\n",
@@ -675,7 +666,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
@@ -697,7 +687,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23</th>\n",
@@ -719,7 +708,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24</th>\n",
@@ -741,7 +729,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25</th>\n",
@@ -763,7 +750,6 @@
        "      <td>RIGHT_FOOT</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>26</th>\n",
@@ -785,7 +771,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>2</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>27</th>\n",
@@ -807,7 +792,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>2</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -904,47 +888,48 @@
        "26      5503       0.883750       0.575625              None   \n",
        "27      5503       0.932917       0.431875              None   \n",
        "\n",
-       "   end_coordinates_y body_part_type  home_score  away_score set_piece_type  \n",
-       "0               None     RIGHT_FOOT           0           0            NaN  \n",
-       "1               None      LEFT_FOOT           0           0            NaN  \n",
-       "2               None      LEFT_FOOT           0           0            NaN  \n",
-       "3               None           HEAD           0           0            NaN  \n",
-       "4               None     RIGHT_FOOT           0           0            NaN  \n",
-       "5               None      LEFT_FOOT           0           0            NaN  \n",
-       "6               None           HEAD           0           0            NaN  \n",
-       "7               None      LEFT_FOOT           0           0      FREE_KICK  \n",
-       "8               None           HEAD           0           0            NaN  \n",
-       "9               None     RIGHT_FOOT           0           0            NaN  \n",
-       "10              None     RIGHT_FOOT           0           0            NaN  \n",
-       "11              None     RIGHT_FOOT           0           0            NaN  \n",
-       "12              None      LEFT_FOOT           0           0            NaN  \n",
-       "13              None      LEFT_FOOT           0           0            NaN  \n",
-       "14              None     RIGHT_FOOT           0           0            NaN  \n",
-       "15              None     RIGHT_FOOT           0           0            NaN  \n",
-       "16              None      LEFT_FOOT           0           0            NaN  \n",
-       "17              None      LEFT_FOOT           0           0            NaN  \n",
-       "18              None     RIGHT_FOOT           0           0            NaN  \n",
-       "19              None      LEFT_FOOT           0           0      FREE_KICK  \n",
-       "20              None      LEFT_FOOT           1           0            NaN  \n",
-       "21              None     RIGHT_FOOT           1           0            NaN  \n",
-       "22              None      LEFT_FOOT           1           0            NaN  \n",
-       "23              None     RIGHT_FOOT           1           0            NaN  \n",
-       "24              None     RIGHT_FOOT           1           0            NaN  \n",
-       "25              None     RIGHT_FOOT           1           0            NaN  \n",
-       "26              None      LEFT_FOOT           2           0            NaN  \n",
-       "27              None      LEFT_FOOT           2           0            NaN  "
+       "   end_coordinates_y body_part_type  home_score  away_score  \n",
+       "0               None     RIGHT_FOOT           0           0  \n",
+       "1               None      LEFT_FOOT           0           0  \n",
+       "2               None      LEFT_FOOT           0           0  \n",
+       "3               None           HEAD           0           0  \n",
+       "4               None     RIGHT_FOOT           0           0  \n",
+       "5               None      LEFT_FOOT           0           0  \n",
+       "6               None           HEAD           0           0  \n",
+       "7               None      LEFT_FOOT           0           0  \n",
+       "8               None           HEAD           0           0  \n",
+       "9               None     RIGHT_FOOT           0           0  \n",
+       "10              None     RIGHT_FOOT           0           0  \n",
+       "11              None     RIGHT_FOOT           0           0  \n",
+       "12              None      LEFT_FOOT           0           0  \n",
+       "13              None      LEFT_FOOT           0           0  \n",
+       "14              None     RIGHT_FOOT           0           0  \n",
+       "15              None     RIGHT_FOOT           0           0  \n",
+       "16              None      LEFT_FOOT           0           0  \n",
+       "17              None      LEFT_FOOT           0           0  \n",
+       "18              None     RIGHT_FOOT           0           0  \n",
+       "19              None      LEFT_FOOT           0           0  \n",
+       "20              None      LEFT_FOOT           1           0  \n",
+       "21              None     RIGHT_FOOT           1           0  \n",
+       "22              None      LEFT_FOOT           1           0  \n",
+       "23              None     RIGHT_FOOT           1           0  \n",
+       "24              None     RIGHT_FOOT           1           0  \n",
+       "25              None     RIGHT_FOOT           1           0  \n",
+       "26              None      LEFT_FOOT           2           0  \n",
+       "27              None      LEFT_FOOT           2           0  "
       ]
      },
-     "execution_count": 23,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "dataframe = dataset.to_pandas(additional_columns={\n",
-    "    'home_score': lambda event: event.state['score'].home,\n",
-    "    'away_score': lambda event: event.state['score'].away\n",
-    "})\n",
+    "dataframe = dataset.to_df(\n",
+    "    \"*\",\n",
+    "    home_score=lambda event: event.state['score'].home,\n",
+    "    away_score=lambda event: event.state['score'].away\n",
+    ")\n",
     "dataframe"
    ]
   },
@@ -957,7 +942,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -999,7 +984,6 @@
        "      <th>body_part_type</th>\n",
        "      <th>home_score</th>\n",
        "      <th>away_score</th>\n",
-       "      <th>set_piece_type</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -1023,7 +1007,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>2</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>27</th>\n",
@@ -1045,7 +1028,6 @@
        "      <td>LEFT_FOOT</td>\n",
        "      <td>2</td>\n",
        "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1064,12 +1046,12 @@
        "26      5503       0.883750       0.575625              None   \n",
        "27      5503       0.932917       0.431875              None   \n",
        "\n",
-       "   end_coordinates_y body_part_type  home_score  away_score set_piece_type  \n",
-       "26              None      LEFT_FOOT           2           0            NaN  \n",
-       "27              None      LEFT_FOOT           2           0            NaN  "
+       "   end_coordinates_y body_part_type  home_score  away_score  \n",
+       "26              None      LEFT_FOOT           2           0  \n",
+       "27              None      LEFT_FOOT           2           0  "
       ]
      },
-     "execution_count": 24,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1089,9 +1071,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 37,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/kloppy-3.7.1-py3.10.egg/kloppy/_providers/statsbomb.py:67: UserWarning: \n",
+      "\n",
+      "You are about to use StatsBomb public data.\n",
+      "By using this data, you are agreeing to the user agreement. \n",
+      "The user agreement can be found here: https://github.com/statsbomb/open-data/blob/master/LICENSE.pdf\n",
+      "\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
    "source": [
     "from kloppy import statsbomb\n",
     "from kloppy.domain import EventType\n",
@@ -1110,7 +1106,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1119,7 +1115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1127,13 +1123,13 @@
     "    dataset\n",
     "    .add_state('lineup')\n",
     "    .filter(lambda event: arturo_vidal in event.state['lineup'].players)\n",
-    "    .to_pandas()\n",
+    "    .to_df()\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -1150,7 +1146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1158,15 +1154,16 @@
     "    dataset\n",
     "    .add_state('lineup')\n",
     "    .filter(lambda event: event.event_type == EventType.PASS and event.team == home_team)\n",
-    "    .to_pandas(additional_columns={\n",
-    "        'vidal_on_pitch': lambda event: arturo_vidal in event.state['lineup'].players\n",
-    "    })\n",
+    "    .to_df(\n",
+    "        \"*\",\n",
+    "        vidal_on_pitch=lambda event: arturo_vidal in event.state['lineup'].players\n",
+    "    )\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
@@ -1225,7 +1222,7 @@
        "True             83     88  94.318182"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 42,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1247,14 +1244,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages/kloppy-3.1.0-py3.8.egg/kloppy/_providers/statsbomb.py:46: UserWarning: \n",
+      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/kloppy-3.7.1-py3.10.egg/kloppy/_providers/statsbomb.py:67: UserWarning: \n",
       "\n",
       "You are about to use StatsBomb public data.\n",
       "By using this data, you are agreeing to the user agreement. \n",
@@ -1277,20 +1274,21 @@
     "    .filter(\n",
     "        lambda event: event.event_type == EventType.SHOT\n",
     "    )\n",
-    "    .to_pandas(additional_columns={\n",
-    "        'Team': lambda event: str(event.team),\n",
-    "        'Formation': lambda event: str(\n",
+    "    .to_df(\n",
+    "        \"*\",\n",
+    "        Team=lambda event: str(event.team),\n",
+    "        Formation=lambda event: str(\n",
     "            event.state['formation'].home \n",
     "            if event.team == dataset.metadata.teams[0] \n",
     "            else event.state['formation'].away\n",
     "        )\n",
-    "    })\n",
+    "    )\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
@@ -1367,7 +1365,7 @@
        "                 4-4-2          0      1    0.000000"
       ]
      },
-     "execution_count": 65,
+     "execution_count": 44,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1408,7 +1406,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/docs/examples/tracking_data.ipynb b/docs/examples/tracking_data.ipynb
index e603f926..a5311410 100644
--- a/docs/examples/tracking_data.ipynb
+++ b/docs/examples/tracking_data.ipynb
@@ -164,7 +164,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/docs/getting-started/datafactory.ipynb b/docs/getting-started/datafactory.ipynb
index 37bf9a9a..30695063 100644
--- a/docs/getting-started/datafactory.ipynb
+++ b/docs/getting-started/datafactory.ipynb
@@ -200,16 +200,8 @@
     "    event_types=[\"shot\", \"pass\"]\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "35a991ab",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -228,7 +220,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting-started/metrica.ipynb b/docs/getting-started/metrica.ipynb
index b4ab6301..9ff5599c 100644
--- a/docs/getting-started/metrica.ipynb
+++ b/docs/getting-started/metrica.ipynb
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "id": "f3e2e6fd",
    "metadata": {},
    "outputs": [
@@ -40,14 +40,14 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>home_11_x</th>\n",
        "      <th>home_11_y</th>\n",
-       "      <th>home_11_d</th>\n",
-       "      <th>home_11_s</th>\n",
        "      <th>...</th>\n",
        "      <th>away_26_d</th>\n",
        "      <th>away_26_s</th>\n",
@@ -66,14 +66,14 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>0.00</td>\n",
+       "      <td>1</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.45472</td>\n",
        "      <td>0.61291</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00082</td>\n",
        "      <td>0.51762</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -90,14 +90,14 @@
        "      <th>1</th>\n",
        "      <td>2</td>\n",
        "      <td>0.08</td>\n",
+       "      <td>145006</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.90456</td>\n",
        "      <td>0.54644</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -112,30 +112,26 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>2 rows × 118 columns</p>\n",
+       "<p>2 rows × 120 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state ball_owning_team_id   ball_x   ball_y  \\\n",
-       "0          1       0.00       None                None  0.45472  0.61291   \n",
-       "1          2       0.08       None                None      NaN      NaN   \n",
+       "   period_id  timestamp  frame_id ball_state ball_owning_team_id   ball_x  \\\n",
+       "0          1       0.00         1       None                None  0.45472   \n",
+       "1          2       0.08    145006       None                None      NaN   \n",
        "\n",
-       "   home_11_x  home_11_y home_11_d home_11_s  ...  away_26_d  away_26_s  \\\n",
-       "0    0.00082    0.51762      None      None  ...        NaN        NaN   \n",
-       "1    0.90456    0.54644      None      None  ...        NaN        NaN   \n",
+       "    ball_y ball_z  home_11_x  home_11_y  ... away_26_d away_26_s  away_27_x  \\\n",
+       "0  0.61291   None    0.00082    0.51762  ...       NaN       NaN        NaN   \n",
+       "1      NaN   None    0.90456    0.54644  ...       NaN       NaN    0.19754   \n",
        "\n",
-       "   away_27_x  away_27_y  away_27_d  away_27_s away_28_x away_28_y  away_28_d  \\\n",
-       "0        NaN        NaN        NaN        NaN       NaN       NaN        NaN   \n",
-       "1    0.19754    0.54636        NaN        NaN   0.21798   0.18921        NaN   \n",
+       "   away_27_y  away_27_d  away_27_s  away_28_x  away_28_y away_28_d away_28_s  \n",
+       "0        NaN        NaN        NaN        NaN        NaN       NaN       NaN  \n",
+       "1    0.54636        NaN        NaN    0.21798    0.18921       NaN       NaN  \n",
        "\n",
-       "   away_28_s  \n",
-       "0        NaN  \n",
-       "1        NaN  \n",
-       "\n",
-       "[2 rows x 118 columns]"
+       "[2 rows x 120 columns]"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -153,7 +149,7 @@
     "    coordinates=\"metrica\"\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -166,7 +162,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "id": "0a582d72",
    "metadata": {},
    "outputs": [
@@ -193,14 +189,14 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>home_11_x</th>\n",
        "      <th>home_11_y</th>\n",
-       "      <th>home_11_d</th>\n",
-       "      <th>home_11_s</th>\n",
        "      <th>...</th>\n",
        "      <th>away_22_d</th>\n",
        "      <th>away_22_s</th>\n",
@@ -219,14 +215,14 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.45472</td>\n",
        "      <td>0.61291</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00082</td>\n",
        "      <td>0.51762</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -243,14 +239,14 @@
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>0.2</td>\n",
+       "      <td>6</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.55677</td>\n",
        "      <td>0.61091</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00140</td>\n",
        "      <td>0.51762</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -267,14 +263,14 @@
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>0.4</td>\n",
+       "      <td>11</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.56504</td>\n",
        "      <td>0.69395</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00085</td>\n",
        "      <td>0.51890</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -291,14 +287,14 @@
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>0.6</td>\n",
+       "      <td>16</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.57330</td>\n",
        "      <td>0.77700</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00065</td>\n",
        "      <td>0.51916</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -315,14 +311,14 @@
        "      <th>4</th>\n",
        "      <td>1</td>\n",
        "      <td>0.8</td>\n",
+       "      <td>21</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.57247</td>\n",
        "      <td>0.79726</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00066</td>\n",
        "      <td>0.51879</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -337,42 +333,35 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 94 columns</p>\n",
+       "<p>5 rows × 96 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state ball_owning_team_id   ball_x   ball_y  \\\n",
-       "0          1        0.0       None                None  0.45472  0.61291   \n",
-       "1          1        0.2       None                None  0.55677  0.61091   \n",
-       "2          1        0.4       None                None  0.56504  0.69395   \n",
-       "3          1        0.6       None                None  0.57330  0.77700   \n",
-       "4          1        0.8       None                None  0.57247  0.79726   \n",
-       "\n",
-       "   home_11_x  home_11_y home_11_d home_11_s  ...  away_22_d  away_22_s  \\\n",
-       "0    0.00082    0.51762      None      None  ...       None       None   \n",
-       "1    0.00140    0.51762      None      None  ...       None       None   \n",
-       "2    0.00085    0.51890      None      None  ...       None       None   \n",
-       "3    0.00065    0.51916      None      None  ...       None       None   \n",
-       "4    0.00066    0.51879      None      None  ...       None       None   \n",
+       "   period_id  timestamp  frame_id ball_state ball_owning_team_id   ball_x  \\\n",
+       "0          1        0.0         1       None                None  0.45472   \n",
+       "1          1        0.2         6       None                None  0.55677   \n",
+       "2          1        0.4        11       None                None  0.56504   \n",
+       "3          1        0.6        16       None                None  0.57330   \n",
+       "4          1        0.8        21       None                None  0.57247   \n",
        "\n",
-       "  away_23_x away_23_y  away_23_d  away_23_s away_24_x away_24_y  away_24_d  \\\n",
-       "0   0.43693   0.94998       None       None   0.37833   0.72617       None   \n",
-       "1   0.43504   0.95116       None       None   0.37557   0.72327       None   \n",
-       "2   0.43128   0.95690       None       None   0.36945   0.71909       None   \n",
-       "3   0.42728   0.96250       None       None   0.36360   0.71470       None   \n",
-       "4   0.42275   0.96700       None       None   0.35810   0.71129       None   \n",
+       "    ball_y ball_z  home_11_x  home_11_y  ... away_22_d away_22_s  away_23_x  \\\n",
+       "0  0.61291   None    0.00082    0.51762  ...      None      None    0.43693   \n",
+       "1  0.61091   None    0.00140    0.51762  ...      None      None    0.43504   \n",
+       "2  0.69395   None    0.00085    0.51890  ...      None      None    0.43128   \n",
+       "3  0.77700   None    0.00065    0.51916  ...      None      None    0.42728   \n",
+       "4  0.79726   None    0.00066    0.51879  ...      None      None    0.42275   \n",
        "\n",
-       "   away_24_s  \n",
-       "0       None  \n",
-       "1       None  \n",
-       "2       None  \n",
-       "3       None  \n",
-       "4       None  \n",
+       "   away_23_y away_23_d away_23_s  away_24_x  away_24_y away_24_d away_24_s  \n",
+       "0    0.94998      None      None    0.37833    0.72617      None      None  \n",
+       "1    0.95116      None      None    0.37557    0.72327      None      None  \n",
+       "2    0.95690      None      None    0.36945    0.71909      None      None  \n",
+       "3    0.96250      None      None    0.36360    0.71470      None      None  \n",
+       "4    0.96700      None      None    0.35810    0.71129      None      None  \n",
        "\n",
-       "[5 rows x 94 columns]"
+       "[5 rows x 96 columns]"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -390,7 +379,7 @@
     "    coordinates=\"metrica\"\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -403,7 +392,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "id": "90ae6cf1",
    "metadata": {},
    "outputs": [
@@ -430,14 +419,14 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>home_11_x</th>\n",
        "      <th>home_11_y</th>\n",
-       "      <th>home_11_d</th>\n",
-       "      <th>home_11_s</th>\n",
        "      <th>...</th>\n",
        "      <th>away_22_d</th>\n",
        "      <th>away_22_s</th>\n",
@@ -456,14 +445,14 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.45472</td>\n",
        "      <td>0.61291</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00082</td>\n",
        "      <td>0.51762</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -480,14 +469,14 @@
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>0.2</td>\n",
+       "      <td>6</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.55677</td>\n",
        "      <td>0.61091</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00140</td>\n",
        "      <td>0.51762</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -504,14 +493,14 @@
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>0.4</td>\n",
+       "      <td>11</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.56504</td>\n",
        "      <td>0.69395</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00085</td>\n",
        "      <td>0.51890</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -528,14 +517,14 @@
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>0.6</td>\n",
+       "      <td>16</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.57330</td>\n",
        "      <td>0.77700</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00065</td>\n",
        "      <td>0.51916</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -552,14 +541,14 @@
        "      <th>4</th>\n",
        "      <td>1</td>\n",
        "      <td>0.8</td>\n",
+       "      <td>21</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.57247</td>\n",
        "      <td>0.79726</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.00066</td>\n",
        "      <td>0.51879</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -574,42 +563,35 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 94 columns</p>\n",
+       "<p>5 rows × 96 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state ball_owning_team_id   ball_x   ball_y  \\\n",
-       "0          1        0.0       None                None  0.45472  0.61291   \n",
-       "1          1        0.2       None                None  0.55677  0.61091   \n",
-       "2          1        0.4       None                None  0.56504  0.69395   \n",
-       "3          1        0.6       None                None  0.57330  0.77700   \n",
-       "4          1        0.8       None                None  0.57247  0.79726   \n",
+       "   period_id  timestamp  frame_id ball_state ball_owning_team_id   ball_x  \\\n",
+       "0          1        0.0         1       None                None  0.45472   \n",
+       "1          1        0.2         6       None                None  0.55677   \n",
+       "2          1        0.4        11       None                None  0.56504   \n",
+       "3          1        0.6        16       None                None  0.57330   \n",
+       "4          1        0.8        21       None                None  0.57247   \n",
        "\n",
-       "   home_11_x  home_11_y home_11_d home_11_s  ...  away_22_d  away_22_s  \\\n",
-       "0    0.00082    0.51762      None      None  ...       None       None   \n",
-       "1    0.00140    0.51762      None      None  ...       None       None   \n",
-       "2    0.00085    0.51890      None      None  ...       None       None   \n",
-       "3    0.00065    0.51916      None      None  ...       None       None   \n",
-       "4    0.00066    0.51879      None      None  ...       None       None   \n",
+       "    ball_y ball_z  home_11_x  home_11_y  ... away_22_d away_22_s  away_23_x  \\\n",
+       "0  0.61291   None    0.00082    0.51762  ...      None      None    0.43693   \n",
+       "1  0.61091   None    0.00140    0.51762  ...      None      None    0.43504   \n",
+       "2  0.69395   None    0.00085    0.51890  ...      None      None    0.43128   \n",
+       "3  0.77700   None    0.00065    0.51916  ...      None      None    0.42728   \n",
+       "4  0.79726   None    0.00066    0.51879  ...      None      None    0.42275   \n",
        "\n",
-       "  away_23_x away_23_y  away_23_d  away_23_s away_24_x away_24_y  away_24_d  \\\n",
-       "0   0.43693   0.94998       None       None   0.37833   0.72617       None   \n",
-       "1   0.43504   0.95116       None       None   0.37557   0.72327       None   \n",
-       "2   0.43128   0.95690       None       None   0.36945   0.71909       None   \n",
-       "3   0.42728   0.96250       None       None   0.36360   0.71470       None   \n",
-       "4   0.42275   0.96700       None       None   0.35810   0.71129       None   \n",
+       "   away_23_y away_23_d away_23_s  away_24_x  away_24_y away_24_d away_24_s  \n",
+       "0    0.94998      None      None    0.37833    0.72617      None      None  \n",
+       "1    0.95116      None      None    0.37557    0.72327      None      None  \n",
+       "2    0.95690      None      None    0.36945    0.71909      None      None  \n",
+       "3    0.96250      None      None    0.36360    0.71470      None      None  \n",
+       "4    0.96700      None      None    0.35810    0.71129      None      None  \n",
        "\n",
-       "   away_24_s  \n",
-       "0       None  \n",
-       "1       None  \n",
-       "2       None  \n",
-       "3       None  \n",
-       "4       None  \n",
-       "\n",
-       "[5 rows x 94 columns]"
+       "[5 rows x 96 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -626,7 +608,7 @@
     "    coordinates=\"metrica\"\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -639,7 +621,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 4,
    "id": "2ccac53a",
    "metadata": {},
    "outputs": [
@@ -666,14 +648,14 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>Track_1_x</th>\n",
        "      <th>Track_1_y</th>\n",
-       "      <th>Track_1_d</th>\n",
-       "      <th>Track_1_s</th>\n",
        "      <th>...</th>\n",
        "      <th>Track_21_x</th>\n",
        "      <th>Track_21_y</th>\n",
@@ -692,14 +674,14 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>18.0</td>\n",
+       "      <td>450</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.52867</td>\n",
        "      <td>0.70690</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.30602</td>\n",
        "      <td>0.97029</td>\n",
-       "      <td>None</td>\n",
-       "      <td>1.112790</td>\n",
        "      <td>...</td>\n",
        "      <td>0.39631</td>\n",
        "      <td>0.77277</td>\n",
@@ -716,14 +698,14 @@
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>18.2</td>\n",
+       "      <td>455</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.54588</td>\n",
        "      <td>0.71626</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.30817</td>\n",
        "      <td>0.96742</td>\n",
-       "      <td>None</td>\n",
-       "      <td>1.308405</td>\n",
        "      <td>...</td>\n",
        "      <td>0.40246</td>\n",
        "      <td>0.76937</td>\n",
@@ -740,14 +722,14 @@
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>18.4</td>\n",
+       "      <td>460</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.56310</td>\n",
        "      <td>0.72562</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.31071</td>\n",
        "      <td>0.96452</td>\n",
-       "      <td>None</td>\n",
-       "      <td>1.498831</td>\n",
        "      <td>...</td>\n",
        "      <td>0.40863</td>\n",
        "      <td>0.76542</td>\n",
@@ -764,14 +746,14 @@
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>18.6</td>\n",
+       "      <td>465</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.58031</td>\n",
        "      <td>0.73497</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.31365</td>\n",
        "      <td>0.96167</td>\n",
-       "      <td>None</td>\n",
-       "      <td>1.672004</td>\n",
        "      <td>...</td>\n",
        "      <td>0.41480</td>\n",
        "      <td>0.76085</td>\n",
@@ -788,14 +770,14 @@
        "      <th>4</th>\n",
        "      <td>1</td>\n",
        "      <td>18.8</td>\n",
+       "      <td>470</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>0.59753</td>\n",
        "      <td>0.74433</td>\n",
+       "      <td>None</td>\n",
        "      <td>0.31705</td>\n",
        "      <td>0.95887</td>\n",
-       "      <td>None</td>\n",
-       "      <td>1.848415</td>\n",
        "      <td>...</td>\n",
        "      <td>0.42098</td>\n",
        "      <td>0.75571</td>\n",
@@ -810,42 +792,42 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 116 columns</p>\n",
+       "<p>5 rows × 118 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state ball_owning_team_id   ball_x   ball_y  \\\n",
-       "0          1       18.0       None                None  0.52867  0.70690   \n",
-       "1          1       18.2       None                None  0.54588  0.71626   \n",
-       "2          1       18.4       None                None  0.56310  0.72562   \n",
-       "3          1       18.6       None                None  0.58031  0.73497   \n",
-       "4          1       18.8       None                None  0.59753  0.74433   \n",
+       "   period_id  timestamp  frame_id ball_state ball_owning_team_id   ball_x  \\\n",
+       "0          1       18.0       450       None                None  0.52867   \n",
+       "1          1       18.2       455       None                None  0.54588   \n",
+       "2          1       18.4       460       None                None  0.56310   \n",
+       "3          1       18.6       465       None                None  0.58031   \n",
+       "4          1       18.8       470       None                None  0.59753   \n",
        "\n",
-       "   Track_1_x  Track_1_y Track_1_d  Track_1_s  ...  Track_21_x  Track_21_y  \\\n",
-       "0    0.30602    0.97029      None   1.112790  ...     0.39631     0.77277   \n",
-       "1    0.30817    0.96742      None   1.308405  ...     0.40246     0.76937   \n",
-       "2    0.31071    0.96452      None   1.498831  ...     0.40863     0.76542   \n",
-       "3    0.31365    0.96167      None   1.672004  ...     0.41480     0.76085   \n",
-       "4    0.31705    0.95887      None   1.848415  ...     0.42098     0.75571   \n",
+       "    ball_y ball_z  Track_1_x  Track_1_y  ... Track_21_x  Track_21_y  \\\n",
+       "0  0.70690   None    0.30602    0.97029  ...    0.39631     0.77277   \n",
+       "1  0.71626   None    0.30817    0.96742  ...    0.40246     0.76937   \n",
+       "2  0.72562   None    0.31071    0.96452  ...    0.40863     0.76542   \n",
+       "3  0.73497   None    0.31365    0.96167  ...    0.41480     0.76085   \n",
+       "4  0.74433   None    0.31705    0.95887  ...    0.42098     0.75571   \n",
        "\n",
-       "   Track_21_d Track_21_s  Track_21_mapping  Track_22_x  Track_22_y  \\\n",
-       "0        None   3.338606              15.0         NaN         NaN   \n",
-       "1        None   3.387701              15.0         NaN         NaN   \n",
-       "2        None   3.442519              15.0         NaN         NaN   \n",
-       "3        None   3.514268              15.0         NaN         NaN   \n",
-       "4        None   3.601024              15.0         NaN         NaN   \n",
+       "   Track_21_d  Track_21_s  Track_21_mapping Track_22_x  Track_22_y  \\\n",
+       "0        None    3.338606              15.0        NaN         NaN   \n",
+       "1        None    3.387701              15.0        NaN         NaN   \n",
+       "2        None    3.442519              15.0        NaN         NaN   \n",
+       "3        None    3.514268              15.0        NaN         NaN   \n",
+       "4        None    3.601024              15.0        NaN         NaN   \n",
        "\n",
-       "   Track_22_d Track_22_s  Track_22_mapping  \n",
-       "0        None        NaN              21.0  \n",
-       "1        None        NaN              21.0  \n",
-       "2        None        NaN              21.0  \n",
-       "3        None        NaN              21.0  \n",
-       "4        None        NaN              21.0  \n",
+       "   Track_22_d  Track_22_s  Track_22_mapping  \n",
+       "0        None         NaN              21.0  \n",
+       "1        None         NaN              21.0  \n",
+       "2        None         NaN              21.0  \n",
+       "3        None         NaN              21.0  \n",
+       "4        None         NaN              21.0  \n",
        "\n",
-       "[5 rows x 116 columns]"
+       "[5 rows x 118 columns]"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -863,7 +845,7 @@
     "    coordinates=\"metrica\"\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -876,7 +858,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "6aaa7038",
    "metadata": {},
    "outputs": [
@@ -1061,7 +1043,7 @@
        "4            NaN  "
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1078,7 +1060,7 @@
     "    event_types=[\"shot\", \"pass\"]\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()\n"
+    "dataset.to_df().head()\n"
    ]
   }
  ],
@@ -1098,7 +1080,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting-started/opta.ipynb b/docs/getting-started/opta.ipynb
index 0694d90e..ef0f3441 100644
--- a/docs/getting-started/opta.ipynb
+++ b/docs/getting-started/opta.ipynb
@@ -220,7 +220,7 @@
     "    event_types=[\"pass\", \"shot\"]\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   }
  ],
@@ -240,7 +240,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting-started/secondspectrum.ipynb b/docs/getting-started/secondspectrum.ipynb
index c41609c9..dfc2275e 100644
--- a/docs/getting-started/secondspectrum.ipynb
+++ b/docs/getting-started/secondspectrum.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "id": "efbb67de",
    "metadata": {},
    "outputs": [
@@ -39,14 +39,14 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>20grw_x</th>\n",
        "      <th>20grw_y</th>\n",
-       "      <th>20grw_d</th>\n",
-       "      <th>20grw_s</th>\n",
        "      <th>...</th>\n",
        "      <th>56zeu_d</th>\n",
        "      <th>56zeu_s</th>\n",
@@ -65,14 +65,14 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>160.00</td>\n",
+       "      <td>4000</td>\n",
        "      <td>alive</td>\n",
        "      <td>456</td>\n",
        "      <td>48.434473</td>\n",
        "      <td>-16.681311</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>46.299561</td>\n",
        "      <td>-24.536171</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -89,14 +89,14 @@
        "      <th>1</th>\n",
        "      <td>2</td>\n",
        "      <td>681.72</td>\n",
+       "      <td>91600</td>\n",
        "      <td>alive</td>\n",
        "      <td>123</td>\n",
        "      <td>23.364446</td>\n",
        "      <td>-16.856017</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>8.861703</td>\n",
        "      <td>-33.088368</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
        "      <td>...</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
@@ -111,26 +111,26 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>2 rows × 94 columns</p>\n",
+       "<p>2 rows × 96 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state  ball_owning_team_id     ball_x     ball_y  \\\n",
-       "0          1     160.00      alive                  456  48.434473 -16.681311   \n",
-       "1          2     681.72      alive                  123  23.364446 -16.856017   \n",
+       "   period_id  timestamp  frame_id ball_state  ball_owning_team_id     ball_x  \\\n",
+       "0          1     160.00      4000      alive                  456  48.434473   \n",
+       "1          2     681.72     91600      alive                  123  23.364446   \n",
        "\n",
-       "     20grw_x    20grw_y 20grw_d 20grw_s  ...  56zeu_d  56zeu_s   27cl51_x  \\\n",
-       "0  46.299561 -24.536171    None    None  ...     None     None  46.646914   \n",
-       "1   8.861703 -33.088368    None    None  ...     None     None -48.850250   \n",
+       "      ball_y  ball_z    20grw_x    20grw_y  ... 56zeu_d 56zeu_s   27cl51_x  \\\n",
+       "0 -16.681311     0.0  46.299561 -24.536171  ...    None    None  46.646914   \n",
+       "1 -16.856017     0.0   8.861703 -33.088368  ...    None    None -48.850250   \n",
        "\n",
-       "    27cl51_y  27cl51_d  27cl51_s   eh90mu_x   eh90mu_y  eh90mu_d  eh90mu_s  \n",
-       "0  25.246787      None      None   5.033404 -21.188707      None      None  \n",
-       "1 -16.447842      None      None  15.112902  12.965995      None      None  \n",
+       "    27cl51_y 27cl51_d 27cl51_s   eh90mu_x   eh90mu_y eh90mu_d eh90mu_s  \n",
+       "0  25.246787     None     None   5.033404 -21.188707     None     None  \n",
+       "1 -16.447842     None     None  15.112902  12.965995     None     None  \n",
        "\n",
-       "[2 rows x 94 columns]"
+       "[2 rows x 96 columns]"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -150,7 +150,7 @@
     "    only_alive=True\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   }
  ],
@@ -170,7 +170,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting-started/skillcorner.ipynb b/docs/getting-started/skillcorner.ipynb
index 2a969160..27327bd8 100644
--- a/docs/getting-started/skillcorner.ipynb
+++ b/docs/getting-started/skillcorner.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 1,
    "id": "71e23535",
    "metadata": {},
    "outputs": [
@@ -39,14 +39,14 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>home_22_x</th>\n",
        "      <th>home_22_y</th>\n",
-       "      <th>home_22_d</th>\n",
-       "      <th>home_22_s</th>\n",
        "      <th>...</th>\n",
        "      <th>away_anon_304_d</th>\n",
        "      <th>away_anon_304_s</th>\n",
@@ -65,14 +65,14 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>12.0</td>\n",
+       "      <td>1531</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>18.887029</td>\n",
        "      <td>30.037350</td>\n",
+       "      <td>1.246213</td>\n",
        "      <td>14.195641</td>\n",
        "      <td>23.489013</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -89,14 +89,14 @@
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>13.0</td>\n",
+       "      <td>1541</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>13.514701</td>\n",
        "      <td>25.827027</td>\n",
+       "      <td>0.657040</td>\n",
        "      <td>14.230466</td>\n",
        "      <td>15.453939</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -113,14 +113,14 @@
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>14.0</td>\n",
+       "      <td>1551</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>16.835040</td>\n",
        "      <td>27.427233</td>\n",
+       "      <td>0.057516</td>\n",
        "      <td>15.328696</td>\n",
        "      <td>17.867260</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -137,14 +137,14 @@
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>15.0</td>\n",
+       "      <td>1561</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>11.656880</td>\n",
        "      <td>24.721404</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>13.642248</td>\n",
        "      <td>22.210971</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -161,6 +161,7 @@
        "      <th>4</th>\n",
        "      <td>1</td>\n",
        "      <td>16.0</td>\n",
+       "      <td>1571</td>\n",
        "      <td>None</td>\n",
        "      <td>103.0</td>\n",
        "      <td>7.426918</td>\n",
@@ -168,7 +169,6 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -183,23 +183,23 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 138 columns</p>\n",
+       "<p>5 rows × 140 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state  ball_owning_team_id     ball_x     ball_y  \\\n",
-       "0          1       12.0       None                  NaN  18.887029  30.037350   \n",
-       "1          1       13.0       None                  NaN  13.514701  25.827027   \n",
-       "2          1       14.0       None                  NaN  16.835040  27.427233   \n",
-       "3          1       15.0       None                  NaN  11.656880  24.721404   \n",
-       "4          1       16.0       None                103.0   7.426918  30.572856   \n",
+       "   period_id  timestamp  frame_id ball_state  ball_owning_team_id     ball_x  \\\n",
+       "0          1       12.0      1531       None                  NaN  18.887029   \n",
+       "1          1       13.0      1541       None                  NaN  13.514701   \n",
+       "2          1       14.0      1551       None                  NaN  16.835040   \n",
+       "3          1       15.0      1561       None                  NaN  11.656880   \n",
+       "4          1       16.0      1571       None                103.0   7.426918   \n",
        "\n",
-       "   home_22_x  home_22_y  home_22_d  home_22_s  ...  away_anon_304_d  \\\n",
-       "0  14.195641  23.489013        NaN        NaN  ...              NaN   \n",
-       "1  14.230466  15.453939        NaN        NaN  ...              NaN   \n",
-       "2  15.328696  17.867260        NaN        NaN  ...              NaN   \n",
-       "3  13.642248  22.210971        NaN        NaN  ...              NaN   \n",
-       "4        NaN        NaN        NaN        NaN  ...              NaN   \n",
+       "      ball_y    ball_z  home_22_x  home_22_y  ...  away_anon_304_d  \\\n",
+       "0  30.037350  1.246213  14.195641  23.489013  ...              NaN   \n",
+       "1  25.827027  0.657040  14.230466  15.453939  ...              NaN   \n",
+       "2  27.427233  0.057516  15.328696  17.867260  ...              NaN   \n",
+       "3  24.721404       NaN  13.642248  22.210971  ...              NaN   \n",
+       "4  30.572856       NaN        NaN        NaN  ...              NaN   \n",
        "\n",
        "   away_anon_304_s  home_anon_368_x  home_anon_368_y  home_anon_368_d  \\\n",
        "0              NaN              NaN              NaN              NaN   \n",
@@ -222,10 +222,10 @@
        "3              NaN  \n",
        "4              NaN  \n",
        "\n",
-       "[5 rows x 138 columns]"
+       "[5 rows x 140 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -244,7 +244,7 @@
     "    include_empty_frames=False\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -257,7 +257,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 2,
    "id": "bff4e3aa",
    "metadata": {},
    "outputs": [
@@ -284,14 +284,14 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>home_47_x</th>\n",
        "      <th>home_47_y</th>\n",
-       "      <th>home_47_d</th>\n",
-       "      <th>home_47_s</th>\n",
        "      <th>...</th>\n",
        "      <th>home_31_d</th>\n",
        "      <th>home_31_s</th>\n",
@@ -310,14 +310,14 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>452</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>14.693770</td>\n",
        "      <td>-0.907936</td>\n",
+       "      <td>5.222056e-02</td>\n",
        "      <td>-4.630710</td>\n",
        "      <td>-20.740084</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -334,12 +334,12 @@
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>462</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>14.634828</td>\n",
        "      <td>-0.030155</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>-3.604550e-02</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -358,14 +358,14 @@
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>13.0</td>\n",
+       "      <td>572</td>\n",
        "      <td>None</td>\n",
        "      <td>40.0</td>\n",
        "      <td>37.410470</td>\n",
        "      <td>-19.993496</td>\n",
+       "      <td>-7.256100e-16</td>\n",
        "      <td>19.580474</td>\n",
        "      <td>-19.368974</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -382,14 +382,14 @@
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>14.0</td>\n",
+       "      <td>582</td>\n",
        "      <td>None</td>\n",
        "      <td>40.0</td>\n",
        "      <td>42.215165</td>\n",
        "      <td>-22.637840</td>\n",
+       "      <td>1.230652e-01</td>\n",
        "      <td>26.785449</td>\n",
        "      <td>-18.257435</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -406,14 +406,14 @@
        "      <th>4</th>\n",
        "      <td>1</td>\n",
        "      <td>15.0</td>\n",
+       "      <td>592</td>\n",
        "      <td>None</td>\n",
        "      <td>40.0</td>\n",
        "      <td>42.433060</td>\n",
        "      <td>-28.680917</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>31.769383</td>\n",
        "      <td>-22.166959</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -428,23 +428,23 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 110 columns</p>\n",
+       "<p>5 rows × 112 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state  ball_owning_team_id     ball_x     ball_y  \\\n",
-       "0          1        1.0       None                  NaN  14.693770  -0.907936   \n",
-       "1          1        2.0       None                  NaN  14.634828  -0.030155   \n",
-       "2          1       13.0       None                 40.0  37.410470 -19.993496   \n",
-       "3          1       14.0       None                 40.0  42.215165 -22.637840   \n",
-       "4          1       15.0       None                 40.0  42.433060 -28.680917   \n",
+       "   period_id  timestamp  frame_id ball_state  ball_owning_team_id     ball_x  \\\n",
+       "0          1        1.0       452       None                  NaN  14.693770   \n",
+       "1          1        2.0       462       None                  NaN  14.634828   \n",
+       "2          1       13.0       572       None                 40.0  37.410470   \n",
+       "3          1       14.0       582       None                 40.0  42.215165   \n",
+       "4          1       15.0       592       None                 40.0  42.433060   \n",
        "\n",
-       "   home_47_x  home_47_y  home_47_d  home_47_s  ...  home_31_d  home_31_s  \\\n",
-       "0  -4.630710 -20.740084        NaN        NaN  ...        NaN        NaN   \n",
-       "1        NaN        NaN        NaN        NaN  ...        NaN        NaN   \n",
-       "2  19.580474 -19.368974        NaN        NaN  ...        NaN        NaN   \n",
-       "3  26.785449 -18.257435        NaN        NaN  ...        NaN        NaN   \n",
-       "4  31.769383 -22.166959        NaN        NaN  ...        NaN        NaN   \n",
+       "      ball_y        ball_z  home_47_x  home_47_y  ...  home_31_d  home_31_s  \\\n",
+       "0  -0.907936  5.222056e-02  -4.630710 -20.740084  ...        NaN        NaN   \n",
+       "1  -0.030155 -3.604550e-02        NaN        NaN  ...        NaN        NaN   \n",
+       "2 -19.993496 -7.256100e-16  19.580474 -19.368974  ...        NaN        NaN   \n",
+       "3 -22.637840  1.230652e-01  26.785449 -18.257435  ...        NaN        NaN   \n",
+       "4 -28.680917           NaN  31.769383 -22.166959  ...        NaN        NaN   \n",
        "\n",
        "   home_anon_471_x  home_anon_471_y  home_anon_471_d  home_anon_471_s  \\\n",
        "0              NaN              NaN              NaN              NaN   \n",
@@ -460,10 +460,10 @@
        "3              NaN              NaN              NaN              NaN  \n",
        "4              NaN              NaN              NaN              NaN  \n",
        "\n",
-       "[5 rows x 110 columns]"
+       "[5 rows x 112 columns]"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -482,7 +482,7 @@
     "    include_empty_frames=False\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -495,7 +495,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "id": "797091f9",
    "metadata": {},
    "outputs": [
@@ -522,14 +522,14 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>home_47_x</th>\n",
        "      <th>home_47_y</th>\n",
-       "      <th>home_47_d</th>\n",
-       "      <th>home_47_s</th>\n",
        "      <th>...</th>\n",
        "      <th>home_31_d</th>\n",
        "      <th>home_31_s</th>\n",
@@ -548,14 +548,14 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>452</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>14.693770</td>\n",
        "      <td>-0.907936</td>\n",
+       "      <td>5.222056e-02</td>\n",
        "      <td>-4.630710</td>\n",
        "      <td>-20.740084</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -572,12 +572,12 @@
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>462</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>14.634828</td>\n",
        "      <td>-0.030155</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>-3.604550e-02</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -596,14 +596,14 @@
        "      <th>2</th>\n",
        "      <td>1</td>\n",
        "      <td>13.0</td>\n",
+       "      <td>572</td>\n",
        "      <td>None</td>\n",
        "      <td>40.0</td>\n",
        "      <td>37.410470</td>\n",
        "      <td>-19.993496</td>\n",
+       "      <td>-7.256100e-16</td>\n",
        "      <td>19.580474</td>\n",
        "      <td>-19.368974</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -620,14 +620,14 @@
        "      <th>3</th>\n",
        "      <td>1</td>\n",
        "      <td>14.0</td>\n",
+       "      <td>582</td>\n",
        "      <td>None</td>\n",
        "      <td>40.0</td>\n",
        "      <td>42.215165</td>\n",
        "      <td>-22.637840</td>\n",
+       "      <td>1.230652e-01</td>\n",
        "      <td>26.785449</td>\n",
        "      <td>-18.257435</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -644,14 +644,14 @@
        "      <th>4</th>\n",
        "      <td>1</td>\n",
        "      <td>15.0</td>\n",
+       "      <td>592</td>\n",
        "      <td>None</td>\n",
        "      <td>40.0</td>\n",
        "      <td>42.433060</td>\n",
        "      <td>-28.680917</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>31.769383</td>\n",
        "      <td>-22.166959</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -666,23 +666,23 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 110 columns</p>\n",
+       "<p>5 rows × 112 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state  ball_owning_team_id     ball_x     ball_y  \\\n",
-       "0          1        1.0       None                  NaN  14.693770  -0.907936   \n",
-       "1          1        2.0       None                  NaN  14.634828  -0.030155   \n",
-       "2          1       13.0       None                 40.0  37.410470 -19.993496   \n",
-       "3          1       14.0       None                 40.0  42.215165 -22.637840   \n",
-       "4          1       15.0       None                 40.0  42.433060 -28.680917   \n",
+       "   period_id  timestamp  frame_id ball_state  ball_owning_team_id     ball_x  \\\n",
+       "0          1        1.0       452       None                  NaN  14.693770   \n",
+       "1          1        2.0       462       None                  NaN  14.634828   \n",
+       "2          1       13.0       572       None                 40.0  37.410470   \n",
+       "3          1       14.0       582       None                 40.0  42.215165   \n",
+       "4          1       15.0       592       None                 40.0  42.433060   \n",
        "\n",
-       "   home_47_x  home_47_y  home_47_d  home_47_s  ...  home_31_d  home_31_s  \\\n",
-       "0  -4.630710 -20.740084        NaN        NaN  ...        NaN        NaN   \n",
-       "1        NaN        NaN        NaN        NaN  ...        NaN        NaN   \n",
-       "2  19.580474 -19.368974        NaN        NaN  ...        NaN        NaN   \n",
-       "3  26.785449 -18.257435        NaN        NaN  ...        NaN        NaN   \n",
-       "4  31.769383 -22.166959        NaN        NaN  ...        NaN        NaN   \n",
+       "      ball_y        ball_z  home_47_x  home_47_y  ...  home_31_d  home_31_s  \\\n",
+       "0  -0.907936  5.222056e-02  -4.630710 -20.740084  ...        NaN        NaN   \n",
+       "1  -0.030155 -3.604550e-02        NaN        NaN  ...        NaN        NaN   \n",
+       "2 -19.993496 -7.256100e-16  19.580474 -19.368974  ...        NaN        NaN   \n",
+       "3 -22.637840  1.230652e-01  26.785449 -18.257435  ...        NaN        NaN   \n",
+       "4 -28.680917           NaN  31.769383 -22.166959  ...        NaN        NaN   \n",
        "\n",
        "   home_anon_471_x  home_anon_471_y  home_anon_471_d  home_anon_471_s  \\\n",
        "0              NaN              NaN              NaN              NaN   \n",
@@ -698,10 +698,10 @@
        "3              NaN              NaN              NaN              NaN  \n",
        "4              NaN              NaN              NaN              NaN  \n",
        "\n",
-       "[5 rows x 110 columns]"
+       "[5 rows x 112 columns]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -719,7 +719,7 @@
     "    include_empty_frames=False\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   }
  ],
@@ -739,7 +739,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting-started/sportec.ipynb b/docs/getting-started/sportec.ipynb
index fcd7b4df..399f8bb4 100644
--- a/docs/getting-started/sportec.ipynb
+++ b/docs/getting-started/sportec.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "e9adb7cb",
    "metadata": {},
    "outputs": [
@@ -159,7 +159,7 @@
        "      <td>4.21</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
@@ -194,10 +194,10 @@
        "1     DFL-OBJ-002G3I            NaN            NaN  \n",
        "2     DFL-OBJ-0027B9       THROW_IN            NaN  \n",
        "3                NaN            NaN     RIGHT_FOOT  \n",
-       "4                NaN            NaN            NaN  "
+       "4               None            NaN            NaN  "
       ]
      },
-     "execution_count": 2,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -214,7 +214,7 @@
     "    event_types=[\"pass\", \"shot\"]\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   }
  ],
@@ -234,7 +234,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting-started/sportscode.ipynb b/docs/getting-started/sportscode.ipynb
index 390b3a3c..a24e319b 100644
--- a/docs/getting-started/sportscode.ipynb
+++ b/docs/getting-started/sportscode.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "id": "523a21a7",
    "metadata": {},
    "outputs": [
@@ -101,7 +101,7 @@
        "2         NaN                 0.13  "
       ]
      },
-     "execution_count": 3,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -113,7 +113,7 @@
     "    data=\"../../kloppy/tests/files/code_xml.xml\"\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -126,7 +126,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 2,
    "id": "728790a3",
    "metadata": {},
    "outputs": [
@@ -221,7 +221,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting-started/statsbomb.ipynb b/docs/getting-started/statsbomb.ipynb
index 477015b1..dc94c0c0 100644
--- a/docs/getting-started/statsbomb.ipynb
+++ b/docs/getting-started/statsbomb.ipynb
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "id": "12ec8092",
    "metadata": {},
    "outputs": [
@@ -62,149 +62,162 @@
        "      <th>receiver_player_id</th>\n",
        "      <th>set_piece_type</th>\n",
        "      <th>body_part_type</th>\n",
+       "      <th>pass_type</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>34208ade-2af4-45c3-970e-655937cad938</td>\n",
+       "      <td>bbc398f7-c784-4958-a504-37b583caf97a</td>\n",
        "      <td>PASS</td>\n",
        "      <td>COMPLETE</td>\n",
        "      <td>True</td>\n",
        "      <td>1</td>\n",
-       "      <td>0.098</td>\n",
-       "      <td>2.007</td>\n",
+       "      <td>0.878</td>\n",
+       "      <td>2.788504</td>\n",
        "      <td>alive</td>\n",
-       "      <td>206</td>\n",
-       "      <td>206</td>\n",
-       "      <td>6581</td>\n",
-       "      <td>60.5</td>\n",
-       "      <td>40.5</td>\n",
-       "      <td>35.5</td>\n",
-       "      <td>25.5</td>\n",
-       "      <td>6855</td>\n",
+       "      <td>909</td>\n",
+       "      <td>909</td>\n",
+       "      <td>11086</td>\n",
+       "      <td>59.95</td>\n",
+       "      <td>39.95</td>\n",
+       "      <td>32.45</td>\n",
+       "      <td>28.75</td>\n",
+       "      <td>8963</td>\n",
        "      <td>KICK_OFF</td>\n",
-       "      <td>LEFT_FOOT</td>\n",
+       "      <td>RIGHT_FOOT</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>d1cccb73-c7ef-4b02-8267-ebd7f149904b</td>\n",
+       "      <td>5c210f79-9714-44a6-b2ec-387f6a117b37</td>\n",
        "      <td>PASS</td>\n",
-       "      <td>INCOMPLETE</td>\n",
-       "      <td>False</td>\n",
+       "      <td>COMPLETE</td>\n",
+       "      <td>True</td>\n",
        "      <td>1</td>\n",
-       "      <td>3.497</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>4.288</td>\n",
+       "      <td>6.764772</td>\n",
        "      <td>alive</td>\n",
-       "      <td>206</td>\n",
-       "      <td>206</td>\n",
-       "      <td>6855</td>\n",
-       "      <td>35.5</td>\n",
-       "      <td>28.5</td>\n",
+       "      <td>909</td>\n",
+       "      <td>909</td>\n",
+       "      <td>8963</td>\n",
+       "      <td>36.15</td>\n",
+       "      <td>30.35</td>\n",
+       "      <td>70.65</td>\n",
+       "      <td>75.75</td>\n",
+       "      <td>8541</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>RIGHT_FOOT</td>\n",
+       "      <td>LEFT_FOOT</td>\n",
+       "      <td>LONG_BALL</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>f1cc47d6-4b19-45a6-beb9-33d67fc83f4b</td>\n",
+       "      <td>8a3e6668-9680-4417-987e-8db0c6ce6a8b</td>\n",
        "      <td>PASS</td>\n",
        "      <td>COMPLETE</td>\n",
        "      <td>True</td>\n",
        "      <td>1</td>\n",
-       "      <td>6.785</td>\n",
-       "      <td>8.431</td>\n",
+       "      <td>12.163</td>\n",
+       "      <td>14.093230</td>\n",
        "      <td>alive</td>\n",
-       "      <td>217</td>\n",
-       "      <td>217</td>\n",
-       "      <td>5203</td>\n",
-       "      <td>34.5</td>\n",
-       "      <td>7.5</td>\n",
-       "      <td>34.5</td>\n",
-       "      <td>20.5</td>\n",
-       "      <td>5470</td>\n",
+       "      <td>914</td>\n",
+       "      <td>914</td>\n",
+       "      <td>8286</td>\n",
+       "      <td>43.05</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>15.75</td>\n",
+       "      <td>7.45</td>\n",
+       "      <td>6954</td>\n",
+       "      <td>THROW_IN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>HEAD</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>f774571f-4b65-43a0-9bfc-6384948d1b82</td>\n",
+       "      <td>f8e61bb0-b618-4695-9ff9-eaa0584bdbfa</td>\n",
        "      <td>PASS</td>\n",
        "      <td>COMPLETE</td>\n",
        "      <td>True</td>\n",
        "      <td>1</td>\n",
-       "      <td>8.431</td>\n",
-       "      <td>9.576</td>\n",
+       "      <td>16.420</td>\n",
+       "      <td>18.242108</td>\n",
        "      <td>alive</td>\n",
-       "      <td>217</td>\n",
-       "      <td>217</td>\n",
-       "      <td>5470</td>\n",
-       "      <td>35.5</td>\n",
-       "      <td>20.5</td>\n",
-       "      <td>35.5</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>5477</td>\n",
+       "      <td>914</td>\n",
+       "      <td>914</td>\n",
+       "      <td>6954</td>\n",
+       "      <td>3.25</td>\n",
+       "      <td>12.65</td>\n",
+       "      <td>7.85</td>\n",
+       "      <td>36.15</td>\n",
+       "      <td>7036</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RIGHT_FOOT</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>HEAD</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>46f0e871-3e72-4817-9a53-af27583ba6c1</td>\n",
+       "      <td>1d72ce76-31fd-43e0-a6b2-1f78c8a57a77</td>\n",
        "      <td>PASS</td>\n",
        "      <td>COMPLETE</td>\n",
        "      <td>True</td>\n",
        "      <td>1</td>\n",
-       "      <td>10.433</td>\n",
-       "      <td>11.150</td>\n",
+       "      <td>20.025</td>\n",
+       "      <td>21.071484</td>\n",
        "      <td>alive</td>\n",
-       "      <td>217</td>\n",
-       "      <td>217</td>\n",
-       "      <td>5477</td>\n",
-       "      <td>33.5</td>\n",
-       "      <td>2.5</td>\n",
-       "      <td>25.5</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>5211</td>\n",
+       "      <td>914</td>\n",
+       "      <td>914</td>\n",
+       "      <td>7036</td>\n",
+       "      <td>9.05</td>\n",
+       "      <td>38.85</td>\n",
+       "      <td>19.65</td>\n",
+       "      <td>47.85</td>\n",
+       "      <td>7173</td>\n",
        "      <td>NaN</td>\n",
        "      <td>RIGHT_FOOT</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               event_id event_type      result success  \\\n",
-       "0  34208ade-2af4-45c3-970e-655937cad938       PASS    COMPLETE    True   \n",
-       "1  d1cccb73-c7ef-4b02-8267-ebd7f149904b       PASS  INCOMPLETE   False   \n",
-       "2  f1cc47d6-4b19-45a6-beb9-33d67fc83f4b       PASS    COMPLETE    True   \n",
-       "3  f774571f-4b65-43a0-9bfc-6384948d1b82       PASS    COMPLETE    True   \n",
-       "4  46f0e871-3e72-4817-9a53-af27583ba6c1       PASS    COMPLETE    True   \n",
+       "                               event_id event_type    result success  \\\n",
+       "0  bbc398f7-c784-4958-a504-37b583caf97a       PASS  COMPLETE    True   \n",
+       "1  5c210f79-9714-44a6-b2ec-387f6a117b37       PASS  COMPLETE    True   \n",
+       "2  8a3e6668-9680-4417-987e-8db0c6ce6a8b       PASS  COMPLETE    True   \n",
+       "3  f8e61bb0-b618-4695-9ff9-eaa0584bdbfa       PASS  COMPLETE    True   \n",
+       "4  1d72ce76-31fd-43e0-a6b2-1f78c8a57a77       PASS  COMPLETE    True   \n",
        "\n",
        "   period_id  timestamp  end_timestamp ball_state ball_owning_team team_id  \\\n",
-       "0          1      0.098          2.007      alive              206     206   \n",
-       "1          1      3.497            NaN      alive              206     206   \n",
-       "2          1      6.785          8.431      alive              217     217   \n",
-       "3          1      8.431          9.576      alive              217     217   \n",
-       "4          1     10.433         11.150      alive              217     217   \n",
+       "0          1      0.878       2.788504      alive              909     909   \n",
+       "1          1      4.288       6.764772      alive              909     909   \n",
+       "2          1     12.163      14.093230      alive              914     914   \n",
+       "3          1     16.420      18.242108      alive              914     914   \n",
+       "4          1     20.025      21.071484      alive              914     914   \n",
        "\n",
        "  player_id  coordinates_x  coordinates_y  end_coordinates_x  \\\n",
-       "0      6581           60.5           40.5               35.5   \n",
-       "1      6855           35.5           28.5                NaN   \n",
-       "2      5203           34.5            7.5               34.5   \n",
-       "3      5470           35.5           20.5               35.5   \n",
-       "4      5477           33.5            2.5               25.5   \n",
+       "0     11086          59.95          39.95              32.45   \n",
+       "1      8963          36.15          30.35              70.65   \n",
+       "2      8286          43.05           0.05              15.75   \n",
+       "3      6954           3.25          12.65               7.85   \n",
+       "4      7036           9.05          38.85              19.65   \n",
+       "\n",
+       "   end_coordinates_y receiver_player_id set_piece_type body_part_type  \\\n",
+       "0              28.75               8963       KICK_OFF     RIGHT_FOOT   \n",
+       "1              75.75               8541            NaN      LEFT_FOOT   \n",
+       "2               7.45               6954       THROW_IN            NaN   \n",
+       "3              36.15               7036            NaN     RIGHT_FOOT   \n",
+       "4              47.85               7173            NaN     RIGHT_FOOT   \n",
        "\n",
-       "   end_coordinates_y receiver_player_id set_piece_type body_part_type  \n",
-       "0               25.5               6855       KICK_OFF      LEFT_FOOT  \n",
-       "1                NaN                NaN            NaN     RIGHT_FOOT  \n",
-       "2               20.5               5470            NaN           HEAD  \n",
-       "3                1.5               5477            NaN           HEAD  \n",
-       "4                1.5               5211            NaN     RIGHT_FOOT  "
+       "   pass_type  \n",
+       "0        NaN  \n",
+       "1  LONG_BALL  \n",
+       "2        NaN  \n",
+       "3        NaN  \n",
+       "4        NaN  "
       ]
      },
-     "execution_count": 4,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -224,7 +237,7 @@
     "    event_types=[\"pass\", \"shot\"]\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -239,7 +252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "id": "f3b9119e",
    "metadata": {},
    "outputs": [
@@ -282,6 +295,7 @@
        "      <th>receiver_player_id</th>\n",
        "      <th>set_piece_type</th>\n",
        "      <th>body_part_type</th>\n",
+       "      <th>pass_type</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -305,6 +319,7 @@
        "      <td>6855</td>\n",
        "      <td>KICK_OFF</td>\n",
        "      <td>LEFT_FOOT</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -314,18 +329,19 @@
        "      <td>False</td>\n",
        "      <td>1</td>\n",
        "      <td>3.497</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>6.785</td>\n",
        "      <td>alive</td>\n",
        "      <td>206</td>\n",
        "      <td>206</td>\n",
        "      <td>6855</td>\n",
        "      <td>35.5</td>\n",
        "      <td>28.5</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>85.5</td>\n",
+       "      <td>72.5</td>\n",
+       "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>RIGHT_FOOT</td>\n",
+       "      <td>LONG_BALL</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -347,6 +363,7 @@
        "      <td>5470</td>\n",
        "      <td>NaN</td>\n",
        "      <td>HEAD</td>\n",
+       "      <td>HEAD_PASS</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -368,6 +385,7 @@
        "      <td>5477</td>\n",
        "      <td>NaN</td>\n",
        "      <td>HEAD</td>\n",
+       "      <td>HEAD_PASS</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -389,6 +407,7 @@
        "      <td>5211</td>\n",
        "      <td>NaN</td>\n",
        "      <td>RIGHT_FOOT</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -404,27 +423,34 @@
        "\n",
        "   period_id  timestamp  end_timestamp ball_state ball_owning_team team_id  \\\n",
        "0          1      0.098          2.007      alive              206     206   \n",
-       "1          1      3.497            NaN      alive              206     206   \n",
+       "1          1      3.497          6.785      alive              206     206   \n",
        "2          1      6.785          8.431      alive              217     217   \n",
        "3          1      8.431          9.576      alive              217     217   \n",
        "4          1     10.433         11.150      alive              217     217   \n",
        "\n",
        "  player_id  coordinates_x  coordinates_y  end_coordinates_x  \\\n",
        "0      6581           60.5           40.5               35.5   \n",
-       "1      6855           35.5           28.5                NaN   \n",
+       "1      6855           35.5           28.5               85.5   \n",
        "2      5203           34.5            7.5               34.5   \n",
        "3      5470           35.5           20.5               35.5   \n",
        "4      5477           33.5            2.5               25.5   \n",
        "\n",
-       "   end_coordinates_y receiver_player_id set_piece_type body_part_type  \n",
-       "0               25.5               6855       KICK_OFF      LEFT_FOOT  \n",
-       "1                NaN                NaN            NaN     RIGHT_FOOT  \n",
-       "2               20.5               5470            NaN           HEAD  \n",
-       "3                1.5               5477            NaN           HEAD  \n",
-       "4                1.5               5211            NaN     RIGHT_FOOT  "
+       "   end_coordinates_y receiver_player_id set_piece_type body_part_type  \\\n",
+       "0               25.5               6855       KICK_OFF      LEFT_FOOT   \n",
+       "1               72.5               None            NaN     RIGHT_FOOT   \n",
+       "2               20.5               5470            NaN           HEAD   \n",
+       "3                1.5               5477            NaN           HEAD   \n",
+       "4                1.5               5211            NaN     RIGHT_FOOT   \n",
+       "\n",
+       "   pass_type  \n",
+       "0        NaN  \n",
+       "1  LONG_BALL  \n",
+       "2  HEAD_PASS  \n",
+       "3  HEAD_PASS  \n",
+       "4        NaN  "
       ]
      },
-     "execution_count": 5,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -441,7 +467,7 @@
     "    event_types=[\"pass\", \"shot\"]\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -457,7 +483,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 3,
    "id": "aa5df8f9",
    "metadata": {},
    "outputs": [
@@ -465,7 +491,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.8/site-packages/kloppy-3.0.0-py3.8.egg/kloppy/_providers/statsbomb.py:45: UserWarning: \n",
+      "/Users/koen/Developer/Projects/PySport/kloppy/.venv/lib/python3.10/site-packages/kloppy-3.7.1-py3.10.egg/kloppy/_providers/statsbomb.py:67: UserWarning: \n",
       "\n",
       "You are about to use StatsBomb public data.\n",
       "By using this data, you are agreeing to the user agreement. \n",
@@ -513,6 +539,7 @@
        "      <th>receiver_player_id</th>\n",
        "      <th>set_piece_type</th>\n",
        "      <th>body_part_type</th>\n",
+       "      <th>pass_type</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -536,6 +563,7 @@
        "      <td>6855</td>\n",
        "      <td>KICK_OFF</td>\n",
        "      <td>LEFT_FOOT</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -545,18 +573,19 @@
        "      <td>False</td>\n",
        "      <td>1</td>\n",
        "      <td>3.497</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>6.785</td>\n",
        "      <td>alive</td>\n",
        "      <td>206</td>\n",
        "      <td>206</td>\n",
        "      <td>6855</td>\n",
        "      <td>35.5</td>\n",
        "      <td>28.5</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>85.5</td>\n",
+       "      <td>72.5</td>\n",
+       "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>RIGHT_FOOT</td>\n",
+       "      <td>LONG_BALL</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -578,6 +607,7 @@
        "      <td>5470</td>\n",
        "      <td>NaN</td>\n",
        "      <td>HEAD</td>\n",
+       "      <td>HEAD_PASS</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -599,6 +629,7 @@
        "      <td>5477</td>\n",
        "      <td>NaN</td>\n",
        "      <td>HEAD</td>\n",
+       "      <td>HEAD_PASS</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -620,6 +651,7 @@
        "      <td>5211</td>\n",
        "      <td>NaN</td>\n",
        "      <td>RIGHT_FOOT</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -635,27 +667,34 @@
        "\n",
        "   period_id  timestamp  end_timestamp ball_state ball_owning_team team_id  \\\n",
        "0          1      0.098          2.007      alive              206     206   \n",
-       "1          1      3.497            NaN      alive              206     206   \n",
+       "1          1      3.497          6.785      alive              206     206   \n",
        "2          1      6.785          8.431      alive              217     217   \n",
        "3          1      8.431          9.576      alive              217     217   \n",
        "4          1     10.433         11.150      alive              217     217   \n",
        "\n",
        "  player_id  coordinates_x  coordinates_y  end_coordinates_x  \\\n",
        "0      6581           60.5           40.5               35.5   \n",
-       "1      6855           35.5           28.5                NaN   \n",
+       "1      6855           35.5           28.5               85.5   \n",
        "2      5203           34.5            7.5               34.5   \n",
        "3      5470           35.5           20.5               35.5   \n",
        "4      5477           33.5            2.5               25.5   \n",
        "\n",
-       "   end_coordinates_y receiver_player_id set_piece_type body_part_type  \n",
-       "0               25.5               6855       KICK_OFF      LEFT_FOOT  \n",
-       "1                NaN                NaN            NaN     RIGHT_FOOT  \n",
-       "2               20.5               5470            NaN           HEAD  \n",
-       "3                1.5               5477            NaN           HEAD  \n",
-       "4                1.5               5211            NaN     RIGHT_FOOT  "
+       "   end_coordinates_y receiver_player_id set_piece_type body_part_type  \\\n",
+       "0               25.5               6855       KICK_OFF      LEFT_FOOT   \n",
+       "1               72.5               None            NaN     RIGHT_FOOT   \n",
+       "2               20.5               5470            NaN           HEAD   \n",
+       "3                1.5               5477            NaN           HEAD   \n",
+       "4                1.5               5211            NaN     RIGHT_FOOT   \n",
+       "\n",
+       "   pass_type  \n",
+       "0        NaN  \n",
+       "1  LONG_BALL  \n",
+       "2  HEAD_PASS  \n",
+       "3  HEAD_PASS  \n",
+       "4        NaN  "
       ]
      },
-     "execution_count": 14,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -671,7 +710,7 @@
     "    event_types=[\"pass\", \"shot\"]\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   }
  ],
@@ -691,7 +730,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting-started/tracab.ipynb b/docs/getting-started/tracab.ipynb
index 48fe462c..280369de 100644
--- a/docs/getting-started/tracab.ipynb
+++ b/docs/getting-started/tracab.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 1,
    "id": "495a3f90",
    "metadata": {},
    "outputs": [
@@ -39,10 +39,12 @@
        "      <th></th>\n",
        "      <th>period_id</th>\n",
        "      <th>timestamp</th>\n",
+       "      <th>frame_id</th>\n",
        "      <th>ball_state</th>\n",
        "      <th>ball_owning_team_id</th>\n",
        "      <th>ball_x</th>\n",
        "      <th>ball_y</th>\n",
+       "      <th>ball_z</th>\n",
        "      <th>away_19_x</th>\n",
        "      <th>away_19_y</th>\n",
        "      <th>away_19_d</th>\n",
@@ -62,10 +64,12 @@
        "      <th>0</th>\n",
        "      <td>1</td>\n",
        "      <td>0.00</td>\n",
+       "      <td>100</td>\n",
        "      <td>alive</td>\n",
        "      <td>home</td>\n",
        "      <td>-27.0</td>\n",
        "      <td>25.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>8889.0</td>\n",
        "      <td>-666.0</td>\n",
        "      <td>NaN</td>\n",
@@ -83,10 +87,12 @@
        "      <th>1</th>\n",
        "      <td>2</td>\n",
        "      <td>0.00</td>\n",
+       "      <td>200</td>\n",
        "      <td>alive</td>\n",
        "      <td>home</td>\n",
        "      <td>-27.0</td>\n",
        "      <td>25.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -104,10 +110,12 @@
        "      <th>2</th>\n",
        "      <td>2</td>\n",
        "      <td>0.08</td>\n",
+       "      <td>202</td>\n",
        "      <td>alive</td>\n",
        "      <td>home</td>\n",
        "      <td>-27.0</td>\n",
        "      <td>25.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -126,23 +134,28 @@
        "</div>"
       ],
       "text/plain": [
-       "   period_id  timestamp ball_state ball_owning_team_id  ball_x  ball_y  \\\n",
-       "0          1       0.00      alive                home   -27.0    25.0   \n",
-       "1          2       0.00      alive                home   -27.0    25.0   \n",
-       "2          2       0.08      alive                home   -27.0    25.0   \n",
+       "   period_id  timestamp  frame_id ball_state ball_owning_team_id  ball_x  \\\n",
+       "0          1       0.00       100      alive                home   -27.0   \n",
+       "1          2       0.00       200      alive                home   -27.0   \n",
+       "2          2       0.08       202      alive                home   -27.0   \n",
        "\n",
-       "   away_19_x  away_19_y  away_19_d  away_19_s  home_19_x  home_19_y home_19_d  \\\n",
-       "0     8889.0     -666.0        NaN       0.55    -1234.0     -294.0      None   \n",
-       "1        NaN        NaN        NaN        NaN    -1234.0     -294.0      None   \n",
-       "2        NaN        NaN        NaN        NaN    -1234.0     -294.0      None   \n",
+       "   ball_y  ball_z  away_19_x  away_19_y  away_19_d  away_19_s  home_19_x  \\\n",
+       "0    25.0     0.0     8889.0     -666.0        NaN       0.55    -1234.0   \n",
+       "1    25.0     0.0        NaN        NaN        NaN        NaN    -1234.0   \n",
+       "2    25.0     0.0        NaN        NaN        NaN        NaN    -1234.0   \n",
        "\n",
-       "   home_19_s  away_1337_x  away_1337_y  away_1337_d  away_1337_s  \n",
-       "0       0.07          NaN          NaN          NaN          NaN  \n",
-       "1       0.07      -8889.0       -666.0          NaN         0.55  \n",
-       "2       0.07      -8889.0       -666.0          NaN         0.55  "
+       "   home_19_y home_19_d  home_19_s  away_1337_x  away_1337_y  away_1337_d  \\\n",
+       "0     -294.0      None       0.07          NaN          NaN          NaN   \n",
+       "1     -294.0      None       0.07      -8889.0       -666.0          NaN   \n",
+       "2     -294.0      None       0.07      -8889.0       -666.0          NaN   \n",
+       "\n",
+       "   away_1337_s  \n",
+       "0          NaN  \n",
+       "1         0.55  \n",
+       "2         0.55  "
       ]
      },
-     "execution_count": 11,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -162,7 +175,7 @@
     ")\n",
     "\n",
     "# Because this is a test dataset the output contains some garbage\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   }
  ],
@@ -182,7 +195,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting-started/wyscout.ipynb b/docs/getting-started/wyscout.ipynb
index f0f03b21..8da56f88 100644
--- a/docs/getting-started/wyscout.ipynb
+++ b/docs/getting-started/wyscout.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "f1120143",
    "metadata": {},
    "outputs": [
@@ -100,8 +100,8 @@
        "      <td>...</td>\n",
        "      <td>29.0</td>\n",
        "      <td>41.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>71.0</td>\n",
+       "      <td>94.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>False</td>\n",
        "      <td>HIGH_PASS</td>\n",
@@ -124,8 +124,8 @@
        "      <td>...</td>\n",
        "      <td>29.0</td>\n",
        "      <td>6.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>False</td>\n",
        "      <td>HEAD_PASS</td>\n",
@@ -203,8 +203,8 @@
        "\n",
        "   coordinates_y  end_coordinates_x  end_coordinates_y  receiver_player_id  \\\n",
        "0           50.0               29.0               41.0                 NaN   \n",
-       "1           41.0                NaN                NaN                 NaN   \n",
-       "2            6.0                NaN                NaN                 NaN   \n",
+       "1           41.0               71.0               94.0                 NaN   \n",
+       "2            6.0               36.0                3.0                 NaN   \n",
        "3            0.0               41.0               13.0                 NaN   \n",
        "4           13.0               63.0               15.0                 NaN   \n",
        "\n",
@@ -225,7 +225,7 @@
        "[5 rows x 21 columns]"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -241,7 +241,7 @@
     "    coordinates=\"wyscout\"\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -256,7 +256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "ada96b31",
    "metadata": {},
    "outputs": [
@@ -392,8 +392,8 @@
        "      <td>...</td>\n",
        "      <td>32.0</td>\n",
        "      <td>35.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>89.0</td>\n",
+       "      <td>6.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>False</td>\n",
        "      <td>HIGH_PASS</td>\n",
@@ -416,8 +416,8 @@
        "      <td>...</td>\n",
        "      <td>85.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>16.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>False</td>\n",
        "      <td>HAND_PASS</td>\n",
@@ -449,8 +449,8 @@
        "0           48.0               47.0               50.0                 NaN   \n",
        "1           50.0               41.0               48.0                 NaN   \n",
        "2           48.0               32.0               35.0                 NaN   \n",
-       "3           35.0                NaN                NaN                 NaN   \n",
-       "4            0.0                NaN                NaN                 NaN   \n",
+       "3           35.0               89.0                6.0                 NaN   \n",
+       "4            0.0               93.0               16.0                 NaN   \n",
        "\n",
        "   is_counter_attack    pass_type set_piece_type goalkeeper_action_type  \\\n",
        "0              False  SIMPLE_PASS            NaN                    NaN   \n",
@@ -469,7 +469,7 @@
        "[5 rows x 21 columns]"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -485,7 +485,7 @@
     "    coordinates=\"wyscout\"\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   },
   {
@@ -500,7 +500,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "8308124e",
    "metadata": {},
    "outputs": [
@@ -636,8 +636,8 @@
        "      <td>...</td>\n",
        "      <td>32.0</td>\n",
        "      <td>35.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>89.0</td>\n",
+       "      <td>6.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>False</td>\n",
        "      <td>HIGH_PASS</td>\n",
@@ -660,8 +660,8 @@
        "      <td>...</td>\n",
        "      <td>85.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>16.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>False</td>\n",
        "      <td>HAND_PASS</td>\n",
@@ -693,8 +693,8 @@
        "0           48.0               47.0               50.0                 NaN   \n",
        "1           50.0               41.0               48.0                 NaN   \n",
        "2           48.0               32.0               35.0                 NaN   \n",
-       "3           35.0                NaN                NaN                 NaN   \n",
-       "4            0.0                NaN                NaN                 NaN   \n",
+       "3           35.0               89.0                6.0                 NaN   \n",
+       "4            0.0               93.0               16.0                 NaN   \n",
        "\n",
        "   is_counter_attack    pass_type set_piece_type goalkeeper_action_type  \\\n",
        "0              False  SIMPLE_PASS            NaN                    NaN   \n",
@@ -713,7 +713,7 @@
        "[5 rows x 21 columns]"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -729,7 +729,7 @@
     "    coordinates=\"wyscout\"\n",
     ")\n",
     "\n",
-    "dataset.to_pandas().head()"
+    "dataset.to_df().head()"
    ]
   }
  ],
@@ -749,7 +749,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,
diff --git a/examples/datasets/metrica.py b/examples/datasets/metrica.py
index e7f70f0e..24bb63fd 100644
--- a/examples/datasets/metrica.py
+++ b/examples/datasets/metrica.py
@@ -22,12 +22,12 @@ def main():
     # We can pass additional keyword arguments to the loaders to specify a different dataset
     dataset = metrica.load_open_data(limit=1000, match_id="2")
 
-    data_frame = dataset.to_pandas()
+    data_frame = dataset.to_df()
     print(data_frame)
 
     # Also load dataset in new metrica format
     dataset = metrica.load_open_data(limit=10_000, match_id="3")
-    data_frame = dataset.to_pandas()
+    data_frame = dataset.to_df()
     df = data_frame[data_frame.ball_x.notnull()]
     print(df)
 
diff --git a/examples/datasets/statsbomb.py b/examples/datasets/statsbomb.py
index c2cb49c4..9e1b1d8a 100644
--- a/examples/datasets/statsbomb.py
+++ b/examples/datasets/statsbomb.py
@@ -30,7 +30,7 @@ def main():
         )
 
     with performance_logging("to pandas", logger=logger):
-        dataframe = dataset.to_pandas()
+        dataframe = dataset.to_df()
 
     print(dataframe[:50].to_string())