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The dataset generation failed because of a cast error
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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