Datasets:

Mr-Bridge
/

fifa-world-cup-2026-espn

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 9 new columns ({'is_own_goal', 'scoring_team_id', 'period', 'conceding_team_id', 'conceding_team', 'scorer', 'is_penalty', 'scoring_team', 'is_home_goal'}) and 4 missing columns ({'team', 'card_type', 'player', 'team_id'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn/goals.csv (at revision c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f), ['hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/cards.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/goals.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/matches.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/odds.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/standings.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/team_match.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/teams.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              match_id: int64
              phase: string
              minute: int64
              minute_bucket: string
              period: int64
              scoring_team_id: int64
              scoring_team: string
              conceding_team_id: int64
              conceding_team: string
              is_home_goal: int64
              is_own_goal: int64
              is_penalty: int64
              type: string
              scorer: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1933
              to
              {'match_id': Value('int64'), 'phase': Value('string'), 'minute': Value('int64'), 'minute_bucket': Value('string'), 'team_id': Value('int64'), 'team': Value('string'), 'card_type': Value('string'), 'type': Value('string'), 'player': Value('string')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 9 new columns ({'is_own_goal', 'scoring_team_id', 'period', 'conceding_team_id', 'conceding_team', 'scorer', 'is_penalty', 'scoring_team', 'is_home_goal'}) and 4 missing columns ({'team', 'card_type', 'player', 'team_id'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn/goals.csv (at revision c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f), ['hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/cards.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/goals.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/matches.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/odds.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/standings.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/team_match.csv', 'hf://datasets/Mr-Bridge/fifa-world-cup-2026-espn@c5d4b31077d4c7f1c9a8c6b714168cdc8157aa5f/teams.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

match_id int64	phase string	minute int64	minute_bucket string	team_id int64	team string	card_type string	type string	player string
760,415	group-stage	17	16-30	467	South Africa	yellow	Yellow Card	Teboho Mokoena
760,415	group-stage	23	16-30	203	Mexico	yellow	Yellow Card	Brian Gutiérrez
760,415	group-stage	49	46-60	467	South Africa	red	Red Card	Sphephelo Sithole
760,415	group-stage	74	61-75	467	South Africa	yellow	Yellow Card	Nkosinathi Sibisi
760,415	group-stage	84	76-90	467	South Africa	red	Red Card	Themba Zwane
760,415	group-stage	92	90+/ET	203	Mexico	red	Red Card	César Montes
760,414	group-stage	96	90+/ET	451	South Korea	yellow	Yellow Card	Lee Gi-Hyuk
760,416	group-stage	11	1-15	206	Canada	yellow	Yellow Card	Alistair Johnston
760,416	group-stage	45	31-45	452	Bosnia-Herzegovina	yellow	Yellow Card	Ermedin Demirovic
760,416	group-stage	46	46-60	452	Bosnia-Herzegovina	yellow	Yellow Card	Jovo Lukic
760,416	group-stage	53	46-60	206	Canada	yellow	Yellow Card	Luc de Fougerolles
760,416	group-stage	93	90+/ET	452	Bosnia-Herzegovina	yellow	Yellow Card	Nikola Katic
760,417	group-stage	10	1-15	210	Paraguay	yellow	Yellow Card	Juan Jose Cáceres
760,417	group-stage	52	46-60	660	United States	red	VAR - (Red) Card Upgrade	Tim Ream
760,417	group-stage	53	46-60	210	Paraguay	yellow	Yellow Card	Miguel Almirón
760,417	group-stage	59	46-60	660	United States	yellow	Yellow Card	Tyler Adams
760,417	group-stage	79	76-90	210	Paraguay	yellow	Yellow Card	Diego Gómez
760,417	group-stage	88	76-90	210	Paraguay	yellow	Yellow Card	Alex Arce
760,417	group-stage	93	90+/ET	210	Paraguay	yellow	Yellow Card	Júnior Alonso
760,420	group-stage	16	16-30	4,398	Qatar	yellow	Yellow Card	Mahmoud Abunada
760,420	group-stage	23	16-30	4,398	Qatar	yellow	Yellow Card	Jassem Gaber
760,420	group-stage	42	31-45	475	Switzerland	yellow	Yellow Card	Denis Zakaria
760,419	group-stage	37	31-45	205	Brazil	yellow	Yellow Card	Casemiro
760,419	group-stage	43	31-45	205	Brazil	yellow	Yellow Card	Roger Ibañez
760,418	group-stage	39	31-45	2,654	Haiti	yellow	Yellow Card	Jean-Ricner Bellegarde
760,418	group-stage	46	46-60	580	Scotland	yellow	Yellow Card	Aaron Hickey
760,418	group-stage	91	90+/ET	580	Scotland	yellow	Yellow Card	Findlay Curtis
760,418	group-stage	95	90+/ET	580	Scotland	yellow	Yellow Card	Kenny McLean
760,421	group-stage	86	76-90	465	Türkiye	yellow	Yellow Card	Yunus Akgün
760,425	group-stage	61	61-75	449	Netherlands	yellow	Yellow Card	Crysencio Summerville
760,425	group-stage	83	76-90	449	Netherlands	yellow	Yellow Card	Memphis Depay
760,425	group-stage	91	90+/ET	449	Netherlands	yellow	Yellow Card	Micky van de Ven
760,423	group-stage	28	16-30	4,789	Ivory Coast	yellow	Yellow Card	Seko Fofana
760,423	group-stage	38	31-45	4,789	Ivory Coast	yellow	Yellow Card	Franck Kessié
760,423	group-stage	40	31-45	4,789	Ivory Coast	yellow	Yellow Card	Guela Doué
760,423	group-stage	73	61-75	209	Ecuador	yellow	Yellow Card	Jackson Porozo
760,424	group-stage	54	46-60	659	Tunisia	yellow	Yellow Card	Rani Khedira
760,428	group-stage	16	16-30	2,597	Cape Verde	yellow	Yellow Card	Sidny Lopes Cabral
760,428	group-stage	93	90+/ET	164	Spain	yellow	Yellow Card	Pedri
760,426	group-stage	13	1-15	2,620	Egypt	yellow	Yellow Card	Marawan Attia
760,426	group-stage	14	1-15	459	Belgium	yellow	Yellow Card	Timothy Castagne
760,426	group-stage	34	31-45	2,620	Egypt	yellow	Yellow Card	Ahmed Fatouh
760,426	group-stage	75	61-75	459	Belgium	yellow	Yellow Card	Maxim De Cuyper
760,429	group-stage	44	31-45	655	Saudi Arabia	yellow	Yellow Card	Abdulelah Al-Amri
760,427	group-stage	89	76-90	469	Iran	yellow	Yellow Card	Ehsan Hajsafi
760,430	group-stage	86	76-90	4,375	Iraq	yellow	Yellow Card	Zaid Tahseen
760,431	group-stage	77	76-90	474	Austria	yellow	Yellow Card	Marcel Sabitzer
760,435	group-stage	13	1-15	482	Portugal	yellow	Yellow Card	Bernardo Silva
760,435	group-stage	32	31-45	2,850	Congo DR	yellow	Yellow Card	Chancel Mbemba
760,435	group-stage	88	76-90	482	Portugal	yellow	Yellow Card	Nélson Semedo
760,435	group-stage	92	90+/ET	482	Portugal	yellow	Yellow Card	Tomás Araújo
760,434	group-stage	16	16-30	4,469	Ghana	yellow	Yellow Card	Caleb Yirenkyi
760,434	group-stage	72	61-75	2,659	Panama	yellow	Yellow Card	César Blackman
760,434	group-stage	99	90+/ET	2,659	Panama	yellow	Yellow Card	Carlos Harvey
760,436	group-stage	7	1-15	208	Colombia	yellow	Yellow Card	Johan Mojica
760,436	group-stage	34	31-45	2,570	Uzbekistan	yellow	Yellow Card	Abdukodir Khusanov
760,438	group-stage	33	31-45	467	South Africa	yellow	Yellow Card	Teboho Mokoena
760,438	group-stage	40	31-45	467	South Africa	yellow	Yellow Card	Thalente Mbatha
760,438	group-stage	75	61-75	450	Czechia	yellow	Yellow Card	Ladislav Krejcí
760,439	group-stage	59	46-60	452	Bosnia-Herzegovina	yellow	Yellow Card	Amar Dedic
760,439	group-stage	61	61-75	452	Bosnia-Herzegovina	yellow	Yellow Card	Edin Dzeko
760,439	group-stage	65	61-75	475	Switzerland	yellow	Yellow Card	Nico Elvedi
760,439	group-stage	80	76-90	452	Bosnia-Herzegovina	red	Red Card	Tarik Muharemovic
760,440	group-stage	9	1-15	206	Canada	yellow	Yellow Card	Derek Cornelius
760,440	group-stage	33	31-45	4,398	Qatar	red	Red Card	Homam Ahmed
760,440	group-stage	53	46-60	4,398	Qatar	red	Red Card	Assim Madibo
760,440	group-stage	62	61-75	4,398	Qatar	yellow	Yellow Card	Ahmed Fathy
760,441	group-stage	4	1-15	451	South Korea	yellow	Yellow Card	Lee Kang-In
760,441	group-stage	58	46-60	451	South Korea	yellow	Yellow Card	Paik Seung-Ho
760,442	group-stage	16	16-30	628	Australia	yellow	Yellow Card	Jordan Bos
760,442	group-stage	32	31-45	628	Australia	yellow	Yellow Card	Alessandro Circati
760,442	group-stage	56	46-60	660	United States	yellow	Yellow Card	Antonee Robinson
760,442	group-stage	88	76-90	628	Australia	yellow	Yellow Card	Harry Souttar
760,442	group-stage	89	76-90	660	United States	yellow	Yellow Card	Folarin Balogun
760,442	group-stage	89	76-90	628	Australia	yellow	Yellow Card	Jacob Italiano
760,442	group-stage	93	90+/ET	660	United States	yellow	Yellow Card	Chris Richards
760,445	group-stage	23	16-30	2,869	Morocco	yellow	Yellow Card	Issa Diop
760,445	group-stage	65	61-75	580	Scotland	yellow	Yellow Card	Andy Robertson
760,444	group-stage	4	1-15	2,654	Haiti	yellow	Yellow Card	Carlens Arcus
760,444	group-stage	49	46-60	2,654	Haiti	yellow	Yellow Card	Frantzdy Pierrot
760,444	group-stage	65	61-75	205	Brazil	yellow	Yellow Card	Douglas Santos
760,444	group-stage	72	61-75	2,654	Haiti	yellow	Yellow Card	Danley Jean Jacques
760,443	group-stage	4	1-15	210	Paraguay	yellow	Yellow Card	Matías Galarza
760,443	group-stage	48	46-60	210	Paraguay	red	Red Card	Miguel Almirón
760,443	group-stage	71	61-75	465	Türkiye	yellow	Yellow Card	Eren Elmali
760,447	group-stage	53	46-60	466	Sweden	yellow	Yellow Card	Gabriel Gudmundsson
760,447	group-stage	75	61-75	466	Sweden	yellow	Yellow Card	Yasin Ayari
760,447	group-stage	80	76-90	466	Sweden	yellow	Yellow Card	Lucas Bergvall
760,446	group-stage	38	31-45	209	Ecuador	yellow	Yellow Card	Jordy Alcívar
760,446	group-stage	39	31-45	11,678	Curaçao	yellow	Yellow Card	Leandro Bacuna
760,446	group-stage	53	46-60	11,678	Curaçao	yellow	Yellow Card	Juninho Bacuna
760,446	group-stage	56	46-60	11,678	Curaçao	yellow	Yellow Card	Livano Comenencia
760,446	group-stage	75	61-75	11,678	Curaçao	yellow	Yellow Card	Juriën Gaari
760,446	group-stage	91	90+/ET	11,678	Curaçao	yellow	Yellow Card	Gervane Kastaneer
760,453	group-stage	30	16-30	655	Saudi Arabia	yellow	Yellow Card	Salem Al-Dawsari
760,453	group-stage	60	46-60	655	Saudi Arabia	yellow	Yellow Card	Mohamed Kanno
760,451	group-stage	3	1-15	459	Belgium	yellow	Yellow Card	Romelu Lukaku
760,451	group-stage	33	31-45	469	Iran	yellow	Yellow Card	Saeid Ezatolahi
760,451	group-stage	66	61-75	459	Belgium	red	Red Card	Nathan Ngoy
760,450	group-stage	5	1-15	2,597	Cape Verde	yellow	Yellow Card	Sidny Lopes Cabral

End of preview.

FIFA World Cup 2026: ESPN Match Data

A clean, analysis-ready dataset of the 2026 FIFA World Cup (USA, Canada and Mexico, 48 teams, 104 matches), assembled from ESPN match data. Snapshot taken at the Round of 16 stage, with 94 of 104 matches played.

Published by MrBridge. It backs three data stories on mr-bridge.com:

Files

Seven relational tables, as CSV, plus a single combined JSON (fifa-world-cup-2026.json).

File	Rows	What it holds
`matches.csv`	104	One row per match: phase, date, local kickoff hour and slot, venue, city, country, scores, total goals, winner/loser, how it was decided, attendance
`team_match.csv`	188	One row per team per match: goals for/against, result, group points, FIFA rank and rank gap, home/away, venue context
`teams.csv`	48	Team metadata: group, FIFA rank and points, host flag, debutant flag
`goals.csv`	275	One row per goal: minute, minute bucket, period, scoring and conceding team, home/own/penalty flags, scorer
`cards.csv`	251	One row per card: minute, minute bucket, team, card type, player
`odds.csv`	94	Pre-match moneyline odds and implied probabilities per match
`standings.csv`	48	Group standings: played, wins/draws/losses, points, goals for/against, group rank, advanced flag

Integrity is cross-checked: the 275 goals reconcile between final scores and the goal timelines.

Notes

Source: ESPN match data for the 2026 FIFA World Cup, structured to a MrBridge schema. Underlying rights to the source data belong to their respective owners.
Snapshot: the tournament is in progress; this release captures matches through the Round of 16 (94 of 104 played). Stage is detected from the data, not assumed.
Use: provided for research and educational use.
Related tool: MrBridge also publishes the ESPN MCP Server, which connects AI assistants to live ESPN scores, standings, odds and stats across 25+ leagues.

Attribution: MrBridge (mr-bridge.com).

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