Package — additional Python functions — Validation

validate_game

validate_game(frame: 'pl.DataFrame', league: 'str', *, header: 'dict | None' = None, source: 'str' = 'espn', summary: 'dict | None' = None, box: 'dict | None' = None) -> 'GameReport'

Validate one processed game against the packaged invariant rules.

Pure and offline: nothing is fetched, nothing is written, the frame is not mutated. A rule whose columns the frame lacks is skipped rather than failed, so a slim frame validates the rules it can support.

For a source whose producer names the same quantities differently, SOURCE_COLUMNS supplies the ESPN-shaped aliases on a view of the frame, and NOT_APPLICABLE names the rules that source cannot support at all -- those are reported in not_applicable rather than skipped silently.

Parameters

Parameter	Type	Default	Description
frame	DataFrame		one game's processed plays, in processor row order -- the plays_frame attribute of NFLPlayProcess / CFBPlayProcess.
league	str		"nfl" or "cfb".
header	dict | None	None	the game's ESPN-shaped header dict. Only used to resolve game_id / season when the frame carries neither.
source	str	'espn'	the source the game came from ("espn", "shield", "cbs", "yahoo", "fox", "ncaa"). Rules that only judge ESPN's own feed are skipped for an adapted source.
summary	dict | None	None	the full ESPN-shaped summary, when available. Enables the header-score, final-WP, dropped-play, drive-count and ESPN box rules.
box	dict | None	None	the processor's advBoxScore dict. Enables the team box and team EPA aggregations.

Returns

ok is True when no rule fired at error severity.

Example

from sportsdataverse.nfl import NFLPlayProcess
from sportsdataverse.validation import validate_game

proc = NFLPlayProcess(gameId=401671801)
proc.espn_nfl_pbp()
game = proc.run_processing_pipeline()
report = validate_game(proc.plays_frame, "nfl", summary=proc.json, box=game.get("advBoxScore"))
report.ok, sorted(report.counts_by_rule)