Datasets:

wchai
/

penalty-bench

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
event: string
conversation_id: string
init: struct<cwd: string, tools: list<item: string>, permission_mode: string, json_schema: struct<type: st (... 245 chars omitted)
  child 0, cwd: string
  child 1, tools: list<item: string>
      child 0, item: string
  child 2, permission_mode: string
  child 3, json_schema: struct<type: string, properties: struct<awarded: struct<type: string, enum: list<item: string>>, sho (... 159 chars omitted)
      child 0, type: string
      child 1, properties: struct<awarded: struct<type: string, enum: list<item: string>>, should_have_been: struct<type: strin (... 95 chars omitted)
          child 0, awarded: struct<type: string, enum: list<item: string>>
              child 0, type: string
              child 1, enum: list<item: string>
                  child 0, item: string
          child 1, should_have_been: struct<type: string, enum: list<item: string>>
              child 0, type: string
              child 1, enum: list<item: string>
                  child 0, item: string
          child 2, confidence: struct<type: string, minimum: int64, maximum: int64>
              child 0, type: string
              child 1, minimum: int64
              child 2, maximum: int64
      child 2, required: list<item: string>
          child 0, item: string
step_update: struct<conversation_id: string, step_index: int64, state: string, step_type: string, text_delta: str (... 159 chars omitted)
  child 0, conversation_id: string
  child 1, step_index: int64
...

segments: list<item: struct<segment: int64, t0: double, t1: double, frames: list<item: int64>, boxes: list<ite (... 113 chars omitted)
  child 0, item: struct<segment: int64, t0: double, t1: double, frames: list<item: int64>, boxes: list<item: struct<x (... 101 chars omitted)
      child 0, segment: int64
      child 1, t0: double
      child 2, t1: double
      child 3, frames: list<item: int64>
          child 0, item: int64
      child 4, boxes: list<item: struct<x: int64, y: int64, w: int64, h: int64, area_frac: double, status: string, mean_pe (... 19 chars omitted)
          child 0, item: struct<x: int64, y: int64, w: int64, h: int64, area_frac: double, status: string, mean_persistence:  (... 7 chars omitted)
              child 0, x: int64
              child 1, y: int64
              child 2, w: int64
              child 3, h: int64
              child 4, area_frac: double
              child 5, status: string
              child 6, mean_persistence: double
id: string
params: struct<EDGE_T: double, P_SEG: double, STD_SEG: double, P_WIN: double, STD_WIN: double, TOP_BAND: dou (... 59 chars omitted)
  child 0, EDGE_T: double
  child 1, P_SEG: double
  child 2, STD_SEG: double
  child 3, P_WIN: double
  child 4, STD_WIN: double
  child 5, TOP_BAND: double
  child 6, BOTTOM_BAND: double
  child 7, MAX_AREA: double
  child 8, MIN_DIM: int64
active_region_analysis_px: list<item: int64>
  child 0, item: int64
height: int64
segments_from: string
width: int64
duration: double
to
{'id': Value('string'), 'src': Value('string'), 'width': Value('int64'), 'height': Value('int64'), 'duration': Value('float64'), 'active_region_analysis_px': List(Value('int64')), 'segments_from': Value('string'), 'segments': List({'segment': Value('int64'), 't0': Value('float64'), 't1': Value('float64'), 'frames': List(Value('int64')), 'boxes': List({'x': Value('int64'), 'y': Value('int64'), 'w': Value('int64'), 'h': Value('int64'), 'area_frac': Value('float64'), 'status': Value('string'), 'mean_persistence': Value('float64')})}), 'params': {'EDGE_T': Value('float64'), 'P_SEG': Value('float64'), 'STD_SEG': Value('float64'), 'P_WIN': Value('float64'), 'STD_WIN': Value('float64'), 'TOP_BAND': Value('float64'), 'BOTTOM_BAND': Value('float64'), 'MAX_AREA': Value('float64'), 'MIN_DIM': Value('int64')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              event: string
              conversation_id: string
              init: struct<cwd: string, tools: list<item: string>, permission_mode: string, json_schema: struct<type: st (... 245 chars omitted)
                child 0, cwd: string
                child 1, tools: list<item: string>
                    child 0, item: string
                child 2, permission_mode: string
                child 3, json_schema: struct<type: string, properties: struct<awarded: struct<type: string, enum: list<item: string>>, sho (... 159 chars omitted)
                    child 0, type: string
                    child 1, properties: struct<awarded: struct<type: string, enum: list<item: string>>, should_have_been: struct<type: strin (... 95 chars omitted)
                        child 0, awarded: struct<type: string, enum: list<item: string>>
                            child 0, type: string
                            child 1, enum: list<item: string>
                                child 0, item: string
                        child 1, should_have_been: struct<type: string, enum: list<item: string>>
                            child 0, type: string
                            child 1, enum: list<item: string>
                                child 0, item: string
                        child 2, confidence: struct<type: string, minimum: int64, maximum: int64>
                            child 0, type: string
                            child 1, minimum: int64
                            child 2, maximum: int64
                    child 2, required: list<item: string>
                        child 0, item: string
              step_update: struct<conversation_id: string, step_index: int64, state: string, step_type: string, text_delta: str (... 159 chars omitted)
                child 0, conversation_id: string
                child 1, step_index: int64
              ...
              
              segments: list<item: struct<segment: int64, t0: double, t1: double, frames: list<item: int64>, boxes: list<ite (... 113 chars omitted)
                child 0, item: struct<segment: int64, t0: double, t1: double, frames: list<item: int64>, boxes: list<item: struct<x (... 101 chars omitted)
                    child 0, segment: int64
                    child 1, t0: double
                    child 2, t1: double
                    child 3, frames: list<item: int64>
                        child 0, item: int64
                    child 4, boxes: list<item: struct<x: int64, y: int64, w: int64, h: int64, area_frac: double, status: string, mean_pe (... 19 chars omitted)
                        child 0, item: struct<x: int64, y: int64, w: int64, h: int64, area_frac: double, status: string, mean_persistence:  (... 7 chars omitted)
                            child 0, x: int64
                            child 1, y: int64
                            child 2, w: int64
                            child 3, h: int64
                            child 4, area_frac: double
                            child 5, status: string
                            child 6, mean_persistence: double
              id: string
              params: struct<EDGE_T: double, P_SEG: double, STD_SEG: double, P_WIN: double, STD_WIN: double, TOP_BAND: dou (... 59 chars omitted)
                child 0, EDGE_T: double
                child 1, P_SEG: double
                child 2, STD_SEG: double
                child 3, P_WIN: double
                child 4, STD_WIN: double
                child 5, TOP_BAND: double
                child 6, BOTTOM_BAND: double
                child 7, MAX_AREA: double
                child 8, MIN_DIM: int64
              active_region_analysis_px: list<item: int64>
                child 0, item: int64
              height: int64
              segments_from: string
              width: int64
              duration: double
              to
              {'id': Value('string'), 'src': Value('string'), 'width': Value('int64'), 'height': Value('int64'), 'duration': Value('float64'), 'active_region_analysis_px': List(Value('int64')), 'segments_from': Value('string'), 'segments': List({'segment': Value('int64'), 't0': Value('float64'), 't1': Value('float64'), 'frames': List(Value('int64')), 'boxes': List({'x': Value('int64'), 'y': Value('int64'), 'w': Value('int64'), 'h': Value('int64'), 'area_frac': Value('float64'), 'status': Value('string'), 'mean_persistence': Value('float64')})}), 'params': {'EDGE_T': Value('float64'), 'P_SEG': Value('float64'), 'STD_SEG': Value('float64'), 'P_WIN': Value('float64'), 'STD_WIN': Value('float64'), 'TOP_BAND': Value('float64'), 'BOTTOM_BAND': Value('float64'), 'MAX_AREA': Value('float64'), 'MIN_DIM': Value('int64')}}
              because column names don't match

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penalty-bench

penalty-bench asks a model to watch a short football clip and decide whether the incident is a penalty. Each item is a penalty-area incident involving Cristiano Ronaldo between 2006 and 2026. The label is either the on-field decision or a verdict from published referee analysis.

path	what it holds
`incidents.jsonl`	43 incidents, one JSON object per line
`clips/`	trimmed clips around each incident, named `<id>.mp4`
`clips_masked/`	the same clips with persistent on-screen graphics (scoreboard, channel logos) masked; each `<id>.json` lists the masked boxes and the detector parameters
`raw_video/`	source footage the clips are cut from: video only, up to 720p, under 25 minutes; one folder per incident id, and `_direct/` for videos fetched by exact URL; each video has a yt-dlp `.info.json` beside it with the original URL
`runs/`	model runs: arguments, raw outputs, per-session traces and a summary table

Incident fields

id: <date>_<home>_<away>_<minute>; the minute is x when it is unknown.
date, competition, season, match, ronaldo_team, minute
description_neutral: what happens, written without names or the outcome.
on_field_decision: penalty or no_penalty.
var_involvement: none, checked_no_change, overturned_to_penalty, overturned_to_no_penalty or unknown.
expert_verdict, expert_sources: referee or pundit verdicts, each with a URL and a quote.
gt: penalty, no_penalty or split. gt_source_type says whether it follows the on-field call (on_field) or an expert column (expert_column).
video_source_url, clip_path, clip_start_s, clip_end_s, contact_time_in_clip_s, has_replay
leak_checked: whether the clip was checked for frames that show the decision, such as the referee pointing to the spot.
notes: how the clip was cut and caveats on the label.

Labels that follow the on-field call carry the referee's error rate, so treat on_field items as noisier than expert_column items.

License

The dataset has two parts under different terms. See LICENSE.

Annotations, masks and run logs (incidents.jsonl, clips_masked/*.json, runs/): CC BY 4.0.
Video (clips/, clips_masked/*.mp4, raw_video/): match footage belongs to its broadcasters, leagues and clubs. It was collected from public online sources and is shared here only for non-commercial research and evaluation. No license to the footage is granted. Do not redistribute it or use it commercially.

Rights holders who want a video removed can open a discussion on this repository, and we will take it down.

Downloads last month: 2,435

Total file size:

10.6 GB

penalty-bench

Contents

Incident fields

License