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"""Implements the label tranformers of the VAEP framework.""" |
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import pandas as pd |
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from pandera.typing import DataFrame |
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import socceraction.spadl.config as spadl |
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from socceraction.spadl.schema import SPADLSchema |
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def scores(actions: DataFrame[SPADLSchema], nr_actions: int = 10) -> pd.DataFrame: |
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"""Determine whether the team possessing the ball scored a goal within the next x actions. |
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Parameters |
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---------- |
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actions : pd.DataFrame |
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The actions of a game. |
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nr_actions : int, default=10 # noqa: DAR103 |
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Number of actions after the current action to consider. |
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Returns |
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------- |
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pd.DataFrame |
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A dataframe with a column 'scores' and a row for each action set to |
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True if a goal was scored by the team possessing the ball within the |
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next x actions; otherwise False. |
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""" |
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goals = actions["type_name"].str.contains("shot") & ( |
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actions["result_id"] == spadl.results.index("success") |
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) |
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owngoals = actions["type_name"].str.contains("shot") & ( |
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actions["result_id"] == spadl.results.index("owngoal") |
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) |
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y = pd.concat([goals, owngoals, actions["team_id"]], axis=1) |
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y.columns = ["goal", "owngoal", "team_id"] |
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for i in range(1, nr_actions): |
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for c in ["team_id", "goal", "owngoal"]: |
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shifted = y[c].shift(-i) |
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shifted[-i:] = y[c].iloc[len(y) - 1] |
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y["%s+%d" % (c, i)] = shifted |
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res = y["goal"] |
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for i in range(1, nr_actions): |
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gi = y["goal+%d" % i] & (y["team_id+%d" % i] == y["team_id"]) |
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ogi = y["owngoal+%d" % i] & (y["team_id+%d" % i] != y["team_id"]) |
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res = res | gi | ogi |
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return pd.DataFrame(res, columns=["scores"]) |
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def concedes(actions: DataFrame[SPADLSchema], nr_actions: int = 10) -> pd.DataFrame: |
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"""Determine whether the team possessing the ball conceded a goal within the next x actions. |
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Parameters |
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---------- |
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actions : pd.DataFrame |
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The actions of a game. |
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nr_actions : int, default=10 # noqa: DAR103 |
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Number of actions after the current action to consider. |
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Returns |
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------- |
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pd.DataFrame |
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A dataframe with a column 'concedes' and a row for each action set to |
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True if a goal was conceded by the team possessing the ball within the |
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next x actions; otherwise False. |
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""" |
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goals = actions["type_name"].str.contains("shot") & ( |
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actions["result_id"] == spadl.results.index("success") |
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) |
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owngoals = actions["type_name"].str.contains("shot") & ( |
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actions["result_id"] == spadl.results.index("owngoal") |
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) |
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y = pd.concat([goals, owngoals, actions["team_id"]], axis=1) |
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y.columns = ["goal", "owngoal", "team_id"] |
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for i in range(1, nr_actions): |
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for c in ["team_id", "goal", "owngoal"]: |
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shifted = y[c].shift(-i) |
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shifted[-i:] = y[c].iloc[len(y) - 1] |
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y["%s+%d" % (c, i)] = shifted |
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res = y["owngoal"] |
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for i in range(1, nr_actions): |
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gi = y["goal+%d" % i] & (y["team_id+%d" % i] != y["team_id"]) |
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ogi = y["owngoal+%d" % i] & (y["team_id+%d" % i] == y["team_id"]) |
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res = res | gi | ogi |
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return pd.DataFrame(res, columns=["concedes"]) |
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def goal_from_shot(actions: DataFrame[SPADLSchema]) -> pd.DataFrame: |
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"""Determine whether a goal was scored from the current action. |
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This label can be use to train an xG model. |
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Parameters |
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---------- |
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actions : pd.DataFrame |
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The actions of a game. |
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Returns |
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------- |
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pd.DataFrame |
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A dataframe with a column 'goal' and a row for each action set to |
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True if a goal was scored from the current action; otherwise False. |
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""" |
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goals = actions["type_name"].str.contains("shot") & ( |
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actions["result_id"] == spadl.results.index("success") |
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) |
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return pd.DataFrame(goals, columns=["goal_from_shot"]) |
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