Datasets:

eatpizzanot
/

soccer-dataset

fixture_id int64 1 102M	team_id int64 1 100M	team_name stringlengths 2 28 ⌀	coach_name stringlengths 3 47 ⌀	coach_api_id int64 0 28.7k ⌀	formation stringclasses 30 values	in_csv bool 2 classes	in_pq bool 2 classes
176,940	52	Charlton	K. Robinson	616	null	false	true
176,953	71	Milton Keynes Dons	R. Barker	9,453	null	false	true
176,957	88	Walsall	J. Whitney	9,451	null	false	true
176,974	2,690	Southend	P. Brown	3,583	null	false	true
176,977	55	Bolton	J. Phillips	969	null	false	true
176,977	83	Bradford	S. McCall	3,574	null	false	true
176,981	88	Walsall	J. Whitney	9,451	null	false	true
177,001	60	Fleetwood Town	U. Rösler	1,389	null	false	true
177,005	50	Peterboro	G. McCann	99	null	false	true
177,005	2,698	Rochdale	K. Hill	590	null	false	true
177,010	58	Oxford	M. Appleton	645	null	false	true
177,027	65	Bristol Rvs	D. Clarke	606	null	false	true
177,047	76	Gillingham	A. Pennock	7,377	null	false	true
177,059	83	Bradford	S. McCall	3,574	null	false	true
177,061	75	AFC Wimbledon	N. Ardley	675	null	false	true
177,085	71	Milton Keynes Dons	R. Barker	9,453	4-4-2	false	true
177,104	58	Oxford	M. Appleton	645	4-4-2	false	true
177,118	52	Charlton	K. Robinson	616	4-3-3	false	true
177,130	66	Shrewsbury	P. Hurst	9,448	4-4-2	false	true
177,134	66	Shrewsbury	P. Hurst	9,448	4-4-2	false	true
177,139	52	Charlton	K. Robinson	616	4-2-3-1	false	true
177,150	62	Northampton	J. Edinburgh	3,799	4-4-2	false	true
177,176	2,690	Southend	P. Brown	3,583	4-4-2	false	true
177,177	88	Walsall	J. Whitney	9,451	4-4-1-1	false	true
177,180	52	Charlton	K. Robinson	616	4-4-2	false	true
177,183	47	Wigan	P. Cook	100	4-2-3-1	false	true
177,185	34	Plymouth	D. Adams	3,568	null	false	true
177,198	75	AFC Wimbledon	N. Ardley	675	4-3-3	false	true
177,199	76	Gillingham	A. Pennock	7,377	3-5-2	false	true
177,200	2,685	Oldham	J. Sheridan	668	4-3-3	false	true
177,212	37	Rotherham	P. Warne	580	3-5-2	false	true
177,212	64	Portsmouth	K. Jackett	622	3-5-2	false	true
177,223	65	Bristol Rvs	D. Clarke	606	4-3-3	false	true
177,224	76	Gillingham	A. Pennock	7,377	3-5-2	false	true
177,227	34	Plymouth	D. Adams	3,568	4-3-3	false	true
177,264	64	Portsmouth	K. Jackett	622	4-4-1-1	false	true
177,265	62	Northampton	J. Hasselbaink	9,450	4-3-3	false	true
177,269	2,690	Southend	P. Brown	3,583	4-3-3	false	true
177,278	2,685	Oldham	R. Wellens	582	4-3-1-2	false	true
177,279	64	Portsmouth	K. Jackett	622	4-2-3-1	false	true
177,280	75	AFC Wimbledon	N. Ardley	675	4-4-2	false	true
177,283	83	Bradford	S. McCall	3,574	4-3-3	false	true
177,287	2,698	Rochdale	K. Hill	590	4-3-3	false	true
177,292	71	Milton Keynes Dons	R. Neilson	2,057	4-3-3	false	true
177,296	37	Rotherham	P. Warne	580	4-5-1	false	true
177,305	58	Oxford	Josep Clotet Ruiz	91	4-2-3-1	false	true
177,306	2,685	Oldham	R. Wellens	582	4-4-2	false	true
177,309	45	Blackpool	G. Bowyer	591	4-3-3	false	true
177,309	2,690	Southend	P. Brown	3,583	4-4-2	false	true
177,315	2,698	Rochdale	K. Hill	590	4-4-2	false	true
177,320	74	Doncaster	D. Ferguson	598	4-3-1-2	false	true
177,330	76	Gillingham	P. Taylor	672	4-3-1-2	false	true
177,331	47	Wigan	P. Cook	100	4-2-3-1	false	true
177,332	62	Northampton	J. Hasselbaink	9,450	4-4-2	false	true
177,338	74	Doncaster	D. Ferguson	598	3-5-2	false	true
177,351	47	Wigan	P. Cook	100	null	false	true
177,355	76	Gillingham	P. Taylor	672	null	false	true
177,363	52	Charlton	K. Robinson	616	4-2-3-1	false	true
177,364	60	Fleetwood Town	U. Rösler	1,389	3-4-3	false	true
177,366	66	Shrewsbury	P. Hurst	9,448	4-5-1	false	true
177,369	2,690	Southend	P. Brown	3,583	4-4-2	false	true
177,376	28	Blackburn	T. Mowbray	88	null	false	true
177,406	52	Charlton	K. Robinson	616	null	false	true
177,409	62	Northampton	J. Hasselbaink	9,450	null	false	true
177,432	2,165	Bury	C. Lucketti	9,449	null	false	true
177,435	47	Wigan	P. Cook	100	null	false	true
177,453	37	Rotherham	P. Warne	580	null	false	true
177,470	66	Shrewsbury	P. Hurst	9,448	null	false	true
177,484	71	Milton Keynes Dons	R. Neilson	2,057	null	false	true
177,485	50	Peterboro	G. McCann	99	null	false	true
177,485	74	Doncaster	D. Ferguson	598	null	false	true
177,486	34	Plymouth	D. Adams	3,568	null	false	true
177,490	62	Northampton	J. Hasselbaink	9,450	null	false	true
177,496	83	Bradford	S. McCall	3,574	null	false	true
177,530	2,698	Rochdale	K. Hill	590	null	false	true
177,536	2,650	Scunthorpe	G. Alexander	628	null	false	true
177,540	47	Wigan	P. Cook	100	null	false	true
177,544	50	Peterboro	G. McCann	99	null	false	true
177,550	2,650	Scunthorpe	G. Alexander	628	null	false	true
177,556	2,698	Rochdale	K. Hill	590	null	false	true
177,562	60	Fleetwood Town	U. Rösler	1,389	null	false	true
177,563	88	Walsall	J. Whitney	9,451	null	false	true
177,571	45	Blackpool	G. Bowyer	591	null	false	true
177,572	62	Northampton	J. Hasselbaink	9,450	null	false	true
177,576	74	Doncaster	D. Ferguson	598	null	false	true
177,577	2,650	Scunthorpe	G. Alexander	628	null	false	true
177,583	28	Blackburn	T. Mowbray	88	null	false	true
177,619	58	Oxford	K. Robinson	616	null	false	true
177,620	76	Gillingham	S. Lovell	3,569	null	false	true
177,645	66	Shrewsbury	P. Hurst	9,448	null	false	true
177,649	2,690	Southend	C. Powell	3,566	null	false	true
177,655	76	Gillingham	S. Lovell	3,569	null	false	true
177,671	75	AFC Wimbledon	N. Ardley	675	null	false	true
177,672	74	Doncaster	D. Ferguson	598	null	false	true
177,684	58	Oxford	K. Robinson	616	null	false	true
177,704	75	AFC Wimbledon	N. Ardley	675	null	false	true
177,705	2,685	Oldham	R. Wellens	582	null	false	true
177,705	2,690	Southend	C. Powell	3,566	null	false	true
177,707	66	Shrewsbury	P. Hurst	9,448	null	false	true
177,714	34	Plymouth	D. Adams	3,568	null	false	true

End of preview. Expand in Data Studio

Global Football (Soccer) Data Lake

Cleaned, deduplicated, quality-gated football match data for BTTS / goals modelling. Sources: API-Football + football-data.co.uk. Pipeline & docs: https://github.com/eatpizzanot/soccer-dataset

673,966 fixtures (644,901 played), 271 leagues, 11,104 teams, 2008-06-07 - 2027-06-06.
BTTS base rate 0.5063. xG fake-zeros removed; known_at leakage guard; 12-dimension QA gate (QUALITY_REPORT.md).

Caveats: league history is uneven — check league_catalogue.history_status (full / recent_only / partial) per league. xg is a coarse provider estimate, not a real per-shot xG model: API-Football xG is a deterministic shots-by-zone formula (empirically xg ≈ 0.115·shots_inside_box + 0.035·shots_outside_box + 0.648·penalties, R²≈1.0), correlates ~0.4 with goals, and is NULL for uncovered league-seasons; never treat missing xG as 0.

from datasets import load_dataset
ds = load_dataset("eatpizzanot/soccer-dataset", "fixtures")

See data_dictionary.md for every column. Licensed CC-BY-4.0; cite API-Football and football-data.co.uk.

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