Metrica¶

Load local csv tracking files¶

In [1]:

from kloppy import metrica

dataset = metrica.load_tracking_csv(
    home_data="../../kloppy/tests/files/metrica_home.csv",
    away_data="../../kloppy/tests/files/metrica_away.csv",
    
    # Optional arguments
    sample_rate=1/5,
    limit=100,
    coordinates="metrica"
)

dataset.to_df().head()

from kloppy import metrica dataset = metrica.load_tracking_csv( home_data="../../kloppy/tests/files/metrica_home.csv", away_data="../../kloppy/tests/files/metrica_away.csv", # Optional arguments sample_rate=1/5, limit=100, coordinates="metrica" ) dataset.to_df().head()

Out[1]:

	period_id	timestamp	frame_id	ball_state	ball_owning_team_id	ball_x	ball_y	ball_z	home_11_x	home_11_y	...	away_26_d	away_26_s	away_27_x	away_27_y	away_27_d	away_27_s	away_28_x	away_28_y	away_28_d	away_28_s
0	1	0.00	1	None	None	0.45472	0.61291	None	0.00082	0.51762	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	2	0.08	145006	None	None	NaN	NaN	None	0.90456	0.54644	...	NaN	NaN	0.19754	0.54636	NaN	NaN	0.21798	0.18921	NaN	NaN

2 rows × 120 columns

Load remote csv tracking files¶

In [2]:

from kloppy import metrica

dataset = metrica.load_tracking_csv(
    home_data="https://raw.githubusercontent.com/metrica-sports/sample-data/master/data/Sample_Game_1/Sample_Game_1_RawTrackingData_Home_Team.csv",
    away_data="https://raw.githubusercontent.com/metrica-sports/sample-data/master/data/Sample_Game_1/Sample_Game_1_RawTrackingData_Away_Team.csv",
    
    # Optional arguments
    sample_rate=1/5,
    limit=100,
    coordinates="metrica"
)

dataset.to_df().head()

from kloppy import metrica dataset = metrica.load_tracking_csv( home_data="https://raw.githubusercontent.com/metrica-sports/sample-data/master/data/Sample_Game_1/Sample_Game_1_RawTrackingData_Home_Team.csv", away_data="https://raw.githubusercontent.com/metrica-sports/sample-data/master/data/Sample_Game_1/Sample_Game_1_RawTrackingData_Away_Team.csv", # Optional arguments sample_rate=1/5, limit=100, coordinates="metrica" ) dataset.to_df().head()

Out[2]:

	period_id	timestamp	frame_id	ball_state	ball_owning_team_id	ball_x	ball_y	ball_z	home_11_x	home_11_y	...	away_22_d	away_22_s	away_23_x	away_23_y	away_23_d	away_23_s	away_24_x	away_24_y	away_24_d	away_24_s
0	1	0.0	1	None	None	0.45472	0.61291	None	0.00082	0.51762	...	None	None	0.43693	0.94998	None	None	0.37833	0.72617	None	None
1	1	0.2	6	None	None	0.55677	0.61091	None	0.00140	0.51762	...	None	None	0.43504	0.95116	None	None	0.37557	0.72327	None	None
2	1	0.4	11	None	None	0.56504	0.69395	None	0.00085	0.51890	...	None	None	0.43128	0.95690	None	None	0.36945	0.71909	None	None
3	1	0.6	16	None	None	0.57330	0.77700	None	0.00065	0.51916	...	None	None	0.42728	0.96250	None	None	0.36360	0.71470	None	None
4	1	0.8	21	None	None	0.57247	0.79726	None	0.00066	0.51879	...	None	None	0.42275	0.96700	None	None	0.35810	0.71129	None	None

5 rows × 96 columns

Load open tracking data¶

In [3]:

from kloppy import metrica

dataset = metrica.load_open_data(
    match_id=1,
    
    # Optional arguments
    sample_rate=1/5,
    limit=100,
    coordinates="metrica"
)

dataset.to_df().head()

from kloppy import metrica dataset = metrica.load_open_data( match_id=1, # Optional arguments sample_rate=1/5, limit=100, coordinates="metrica" ) dataset.to_df().head()

Out[3]:

	period_id	timestamp	frame_id	ball_state	ball_owning_team_id	ball_x	ball_y	ball_z	home_11_x	home_11_y	...	away_22_d	away_22_s	away_23_x	away_23_y	away_23_d	away_23_s	away_24_x	away_24_y	away_24_d	away_24_s
0	1	0.0	1	None	None	0.45472	0.61291	None	0.00082	0.51762	...	None	None	0.43693	0.94998	None	None	0.37833	0.72617	None	None
1	1	0.2	6	None	None	0.55677	0.61091	None	0.00140	0.51762	...	None	None	0.43504	0.95116	None	None	0.37557	0.72327	None	None
2	1	0.4	11	None	None	0.56504	0.69395	None	0.00085	0.51890	...	None	None	0.43128	0.95690	None	None	0.36945	0.71909	None	None
3	1	0.6	16	None	None	0.57330	0.77700	None	0.00065	0.51916	...	None	None	0.42728	0.96250	None	None	0.36360	0.71470	None	None
4	1	0.8	21	None	None	0.57247	0.79726	None	0.00066	0.51879	...	None	None	0.42275	0.96700	None	None	0.35810	0.71129	None	None

5 rows × 96 columns

Load local EPTS tracking files¶

In [4]:

from kloppy import metrica

dataset = metrica.load_tracking_epts(
    meta_data="../../kloppy/tests/files/epts_metrica_metadata.xml",
    raw_data="../../kloppy/tests/files/epts_metrica_tracking.txt",
    
    # Optional arguments
    sample_rate=1/5,
    limit=100,
    coordinates="metrica"
)

dataset.to_df().head()

from kloppy import metrica dataset = metrica.load_tracking_epts( meta_data="../../kloppy/tests/files/epts_metrica_metadata.xml", raw_data="../../kloppy/tests/files/epts_metrica_tracking.txt", # Optional arguments sample_rate=1/5, limit=100, coordinates="metrica" ) dataset.to_df().head()

Out[4]:

	period_id	timestamp	frame_id	ball_state	ball_owning_team_id	ball_x	ball_y	ball_z	Track_1_x	Track_1_y	...	Track_21_x	Track_21_y	Track_21_d	Track_21_s	Track_21_mapping	Track_22_x	Track_22_y	Track_22_d	Track_22_s	Track_22_mapping
0	1	18.0	450	None	None	0.52867	0.70690	None	0.30602	0.97029	...	0.39631	0.77277	None	3.338606	15.0	NaN	NaN	None	NaN	21.0
1	1	18.2	455	None	None	0.54588	0.71626	None	0.30817	0.96742	...	0.40246	0.76937	None	3.387701	15.0	NaN	NaN	None	NaN	21.0
2	1	18.4	460	None	None	0.56310	0.72562	None	0.31071	0.96452	...	0.40863	0.76542	None	3.442519	15.0	NaN	NaN	None	NaN	21.0
3	1	18.6	465	None	None	0.58031	0.73497	None	0.31365	0.96167	...	0.41480	0.76085	None	3.514268	15.0	NaN	NaN	None	NaN	21.0
4	1	18.8	470	None	None	0.59753	0.74433	None	0.31705	0.95887	...	0.42098	0.75571	None	3.601024	15.0	NaN	NaN	None	NaN	21.0

5 rows × 118 columns

Load local event files¶

In [5]:

from kloppy import metrica

dataset = metrica.load_event(
    event_data="../../kloppy/tests/files/metrica_events.json",
    meta_data="../../kloppy/tests/files/epts_metrica_metadata.xml",
    
    # Optional arguments
    coordinates="metrica",
    event_types=["shot", "pass"]
)

dataset.to_df().head()

from kloppy import metrica dataset = metrica.load_event( event_data="../../kloppy/tests/files/metrica_events.json", meta_data="../../kloppy/tests/files/epts_metrica_metadata.xml", # Optional arguments coordinates="metrica", event_types=["shot", "pass"] ) dataset.to_df().head()

Out[5]:

	event_id	event_type	result	success	period_id	timestamp	end_timestamp	ball_state	ball_owning_team	team_id	player_id	coordinates_x	coordinates_y	end_coordinates_x	end_coordinates_y	receiver_player_id	set_piece_type	body_part_type
0	None	PASS	COMPLETE	True	1	14.44	15.08	alive	TEAM_A	TEAM_A	None	0.50125	0.48725	0.49864	0.48705	NaN	KICK_OFF	NaN
1	None	PASS	COMPLETE	True	1	15.36	17.04	alive	TEAM_A	TEAM_A	None	0.49700	0.48500	0.63373	0.63449	NaN	NaN	NaN
2	None	PASS	COMPLETE	True	1	18.60	20.28	alive	TEAM_A	TEAM_A	None	0.66986	0.59707	0.80602	0.39821	NaN	NaN	NaN
3	None	PASS	COMPLETE	True	1	21.20	23.20	alive	TEAM_A	TEAM_A	None	0.80929	0.42922	0.79906	0.81522	NaN	NaN	NaN
4	None	PASS	COMPLETE	True	1	23.92	25.12	alive	TEAM_A	TEAM_A	None	0.79756	0.81998	0.68101	0.98059	NaN	NaN	NaN