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AdamRoch
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nfl-play-normalization-v2

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Text Generation

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The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
control_record_count: int64
curve_point: string
dataset_file: string
dataset_sha256: string
format: string
record_count: int64
record_counts_by_season: struct<2019: int64, 2020: int64, 2021: int64, 2022: int64>
  child 0, 2019: int64
  child 1, 2020: int64
  child 2, 2021: int64
  child 3, 2022: int64
record_ids: list<item: string>
  child 0, item: string
record_ids_sha256: string
seed: int64
source_dataset: struct<approved_by: string, approved_on: timestamp[s], file: string, record_count: int64, sha256: st (... 5 chars omitted)
  child 0, approved_by: string
  child 1, approved_on: timestamp[s]
  child 2, file: string
  child 3, record_count: int64
  child 4, sha256: string
target_rule_match_counts: struct<lateral: int64, multiple_yardage_clauses: int64, repeated_fumble: int64, turnover_with_penalt (... 9 chars omitted)
  child 0, lateral: int64
  child 1, multiple_yardage_clauses: int64
  child 2, repeated_fumble: int64
  child 3, turnover_with_penalty: int64
target_rule_version: string
target_rules: struct<lateral: string, multiple_yardage_clauses: string, repeated_fumble: string, turnover_with_pen (... 13 chars omitted)
  child 0, lateral: string
  child 1, multiple_yardage_clauses: string
  child 2, repeated_fumble: string
  child 3, turnover_with_penalty: string
targeted_record_count: int64
v1_baseline: struct<ordered_record_ids_sha256: string, record_count: int64, seed: int64, selection_method: string (... 31 chars omitted)
  child 0, ordered_record_ids_sha256: string
  child 1, record_count: int64
  child 2, seed: int64
  child 3, selection_method: string
  child 4, targeted_record_count: int64
v1_to_v2: null
points: list<item: struct<control_record_count: int64, dataset_file: string, dataset_sha256: string, manifes (... 106 chars omitted)
  child 0, item: struct<control_record_count: int64, dataset_file: string, dataset_sha256: string, manifest_file: str (... 94 chars omitted)
      child 0, control_record_count: int64
      child 1, dataset_file: string
      child 2, dataset_sha256: string
      child 3, manifest_file: string
      child 4, manifest_sha256: string
      child 5, name: string
      child 6, record_count: int64
      child 7, targeted_record_count: int64
target_rule_counts_in_source: struct<lateral: int64, multiple_yardage_clauses: int64, repeated_fumble: int64, turnover_with_penalt (... 9 chars omitted)
  child 0, lateral: int64
  child 1, multiple_yardage_clauses: int64
  child 2, repeated_fumble: int64
  child 3, turnover_with_penalty: int64
to
{'format': Value('string'), 'points': List({'control_record_count': Value('int64'), 'dataset_file': Value('string'), 'dataset_sha256': Value('string'), 'manifest_file': Value('string'), 'manifest_sha256': Value('string'), 'name': Value('string'), 'record_count': Value('int64'), 'targeted_record_count': Value('int64')}), 'seed': Value('int64'), 'source_dataset': {'file': Value('string'), 'manifest_file': Value('string'), 'manifest_sha256': Value('string'), 'record_count': Value('int64'), 'sha256': Value('string')}, 'target_rule_counts_in_source': {'lateral': Value('int64'), 'multiple_yardage_clauses': Value('int64'), 'repeated_fumble': Value('int64'), 'turnover_with_penalty': Value('int64')}, 'target_rule_version': Value('string'), 'target_rules': {'lateral': Value('string'), 'multiple_yardage_clauses': Value('string'), 'repeated_fumble': Value('string'), 'turnover_with_penalty': Value('string')}, 'v1_baseline': {'ordered_record_ids_sha256': Value('string'), 'record_count': Value('int64'), 'seed': Value('int64'), 'selection_method': Value('string'), 'targeted_record_count': Value('int64')}, 'v1_to_v2': {'added_target_record_ids': List(Value('string')), 'overlap_percent': Value('float64'), 'overlap_record_count': Value('int64'), 'removed_control_record_ids': List(Value('string')), 'v2_record_count': Value('int64')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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 343, 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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              control_record_count: int64
              curve_point: string
              dataset_file: string
              dataset_sha256: string
              format: string
              record_count: int64
              record_counts_by_season: struct<2019: int64, 2020: int64, 2021: int64, 2022: int64>
                child 0, 2019: int64
                child 1, 2020: int64
                child 2, 2021: int64
                child 3, 2022: int64
              record_ids: list<item: string>
                child 0, item: string
              record_ids_sha256: string
              seed: int64
              source_dataset: struct<approved_by: string, approved_on: timestamp[s], file: string, record_count: int64, sha256: st (... 5 chars omitted)
                child 0, approved_by: string
                child 1, approved_on: timestamp[s]
                child 2, file: string
                child 3, record_count: int64
                child 4, sha256: string
              target_rule_match_counts: struct<lateral: int64, multiple_yardage_clauses: int64, repeated_fumble: int64, turnover_with_penalt (... 9 chars omitted)
                child 0, lateral: int64
                child 1, multiple_yardage_clauses: int64
                child 2, repeated_fumble: int64
                child 3, turnover_with_penalty: int64
              target_rule_version: string
              target_rules: struct<lateral: string, multiple_yardage_clauses: string, repeated_fumble: string, turnover_with_pen (... 13 chars omitted)
                child 0, lateral: string
                child 1, multiple_yardage_clauses: string
                child 2, repeated_fumble: string
                child 3, turnover_with_penalty: string
              targeted_record_count: int64
              v1_baseline: struct<ordered_record_ids_sha256: string, record_count: int64, seed: int64, selection_method: string (... 31 chars omitted)
                child 0, ordered_record_ids_sha256: string
                child 1, record_count: int64
                child 2, seed: int64
                child 3, selection_method: string
                child 4, targeted_record_count: int64
              v1_to_v2: null
              points: list<item: struct<control_record_count: int64, dataset_file: string, dataset_sha256: string, manifes (... 106 chars omitted)
                child 0, item: struct<control_record_count: int64, dataset_file: string, dataset_sha256: string, manifest_file: str (... 94 chars omitted)
                    child 0, control_record_count: int64
                    child 1, dataset_file: string
                    child 2, dataset_sha256: string
                    child 3, manifest_file: string
                    child 4, manifest_sha256: string
                    child 5, name: string
                    child 6, record_count: int64
                    child 7, targeted_record_count: int64
              target_rule_counts_in_source: struct<lateral: int64, multiple_yardage_clauses: int64, repeated_fumble: int64, turnover_with_penalt (... 9 chars omitted)
                child 0, lateral: int64
                child 1, multiple_yardage_clauses: int64
                child 2, repeated_fumble: int64
                child 3, turnover_with_penalty: int64
              to
              {'format': Value('string'), 'points': List({'control_record_count': Value('int64'), 'dataset_file': Value('string'), 'dataset_sha256': Value('string'), 'manifest_file': Value('string'), 'manifest_sha256': Value('string'), 'name': Value('string'), 'record_count': Value('int64'), 'targeted_record_count': Value('int64')}), 'seed': Value('int64'), 'source_dataset': {'file': Value('string'), 'manifest_file': Value('string'), 'manifest_sha256': Value('string'), 'record_count': Value('int64'), 'sha256': Value('string')}, 'target_rule_counts_in_source': {'lateral': Value('int64'), 'multiple_yardage_clauses': Value('int64'), 'repeated_fumble': Value('int64'), 'turnover_with_penalty': Value('int64')}, 'target_rule_version': Value('string'), 'target_rules': {'lateral': Value('string'), 'multiple_yardage_clauses': Value('string'), 'repeated_fumble': Value('string'), 'turnover_with_penalty': Value('string')}, 'v1_baseline': {'ordered_record_ids_sha256': Value('string'), 'record_count': Value('int64'), 'seed': Value('int64'), 'selection_method': Value('string'), 'targeted_record_count': Value('int64')}, 'v1_to_v2': {'added_target_record_ids': List(Value('string')), 'overlap_percent': Value('float64'), 'overlap_record_count': Value('int64'), 'removed_control_record_ids': List(Value('string')), 'v2_record_count': Value('int64')}}
              because column names don't match

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NFL Play Normalization V2 Data-Efficiency Curve

This dataset contains four nested training sets with 3,125, 6,250, 12,500, and 25,000 unchanged real nflverse play descriptions from the 2019 through 2022 seasons. The v2 selection targets laterals, repeated fumbles, accepted penalties after turnovers, and descriptions with several yardage clauses.

The curve manifest pins every dataset and point-manifest checksum. The review file explains the deterministic selection and the fixed-data comparison with the corrected MVP sample.

Construction and revisions

Source corpus SHA-256: 9129b63f8de1c45e864898cf4d6f0fcd453e59fc5c0587d05b59d54788a49957
Canonical schema SHA-256: b5fc039929b7a93753f41a233579881f560ef83446f2aa0fe255fe4e9ddaa807
Publication code revision: de8bba2ce956be1061e3f0d97e7b556abd9ed5ab
Selection rule: multi-event-yardage-v1

The immutable Hugging Face dataset revision is recorded by scripts/publish_v2_dataset.py after upload because a repository cannot include the hash of the commit that contains that same hash.

Source attribution

nflverse data is licensed CC BY 4.0. Attribute nflverse and its upstream sources when using this dataset. The exact source releases are:

2019: https://github.com/nflverse/nflverse-data/releases/download/pbp/play_by_play_2019.parquet with SHA-256 60c3067017db2d28a78f66a79b657268be8578d9a5288e6a827efdcd7fe42540
2020: https://github.com/nflverse/nflverse-data/releases/download/pbp/play_by_play_2020.parquet with SHA-256 73b7dbf66fa8cb9356f58bf6b1f15a0fee197ecc10cf4983b640cb9679b15cb4
2021: https://github.com/nflverse/nflverse-data/releases/download/pbp/play_by_play_2021.parquet with SHA-256 333ad34378e5339d5172717cc83378e908daf02c8699416ab3e17c2ec10f78d8
2022: https://github.com/nflverse/nflverse-data/releases/download/pbp/play_by_play_2022.parquet with SHA-256 931121d8897779d7944e2a293e92ed8799c8e5cceef84096ac42339003fedc09

Intended use and limitations

Use this dataset to train NFL play-description normalizers against the included canonical JSON contract and to reproduce the four-point data-efficiency curve. It is not a replacement for nflverse structured fields. It does not cover spoken commentary, video, betting, fantasy, prediction, or coaching advice. The selection deliberately increases multi-event yardage examples, so it is not an unbiased sample of all NFL plays.

Downloads last month: 35

Total file size:

29.3 MB

Models trained or fine-tuned on AdamRoch/nfl-play-normalization-v2

AdamRoch/qwen3-0.6b-nfl-play-normalizer-v2-n-25000

Updated 9 days ago