Package — additional Python functions — ESPN

xfl_pbp

xfl_pbp(game_id: 'Union[str, int]', *, return_as_pandas: 'bool' = False) -> "Union[pl.DataFrame, 'pd.DataFrame']"

Enriched XFL play-by-play (EP/EPA/WP/WPA/CP/CPOE).

Fetches the ESPN game summary, unrolls its drives into an nflverse-shape frame, and scores it with the same parity-validated NFL EP/WP pipeline used league-wide (see sportsdataverse.football.spring_football_ep_wp).

Parameters

Parameter	Type	Default	Description
`game_id`	`Union[str, int]`		ESPN XFL event id.
`return_as_pandas`	`bool`	`False`	When `True`, return a `pandas.DataFrame`.

Returns

One row per play with ep/epa/wp/wpa/cp/cpoe and the other enrich_nfl_pbp output columns. Zero rows for a game ESPN has no play-by-play for.

col_name	type	description
`defteam`	character
`defteam_score`	integer
`defteam_timeouts_remaining`	integer
`dome`	integer
`down`	integer
`game_half`	character
`game_id`	character
`game_seconds_remaining`	double
`half_seconds_remaining`	double
`home`	integer
`home_team`	character
`outdoors`	integer
`play_id`	character
`posteam`	character
`posteam_score`	integer
`posteam_timeouts_remaining`	integer
`receive_2h_ko`	integer
`retractable`	integer
`roof`	character
`score_differential`	integer
`season`	integer
`spread_line`	double
`yardline_100`	integer
`ydstogo`	integer
`air_yards`	double
`kickoff_attempt`	integer
`play_type`	character
`qtr`	integer
`ep`	double
`td_prob`	double
`opp_td_prob`	double
`fg_prob`	double
`opp_fg_prob`	double
`safety_prob`	double
`opp_safety_prob`	double
`no_score_prob`	double
`epa`	double
`qb_epa`	double
`air_epa`	double
`yac_epa`	double
`comp_air_epa`	double
`comp_yac_epa`	double
`total_home_comp_air_epa`	double
`total_away_comp_air_epa`	double
`total_home_comp_yac_epa`	double
`total_away_comp_yac_epa`	double
`total_home_raw_air_epa`	double
`total_away_raw_air_epa`	double
`total_home_raw_yac_epa`	double
`total_away_raw_yac_epa`	double
`posteam_spread`	double
`elapsed_share`	double
`spread_time`	double
`Diff_Time_Ratio`	double
`wp`	double
`vegas_wp`	double
`home_wp`	double
`away_wp`	double
`def_wp`	double
`vegas_home_wpa`	double
`vegas_wpa`	double
`wpa`	double
`air_wpa`	double
`yac_wpa`	double
`comp_air_wpa`	double
`comp_yac_wpa`	double
`total_home_comp_air_wpa`	double
`total_away_comp_air_wpa`	double
`total_home_comp_yac_wpa`	double
`total_away_comp_yac_wpa`	double
`total_home_raw_air_wpa`	double
`total_away_raw_air_wpa`	double
`total_home_raw_yac_wpa`	double
`total_away_raw_yac_wpa`	double
`cp`	double
`cpoe`	double
`xpass`	double
`pass_oe`	double
`xyac_epa`	double
`xyac_mean_yardage`	double
`xyac_median_yardage`	double
`xyac_success`	double
`xyac_fd`	double
`home_opening_kickoff`	double
`go_wp`	double
`first_down_prob`	double
`wp_succeed`	double
`wp_fail`	double
`fg_make_prob`	double
`make_fg_wp`	double
`miss_fg_wp`	double
`fg_wp`	double
`punt_wp`	double
`go_boost`	double
`go_wp_diff`	double
`punt_wp_diff`	double
`fg_wp_diff`	double
`fourth_down_recommendation`	character

Example

from sportsdataverse.football.xfl import xfl_pbp

df = xfl_pbp("401517780")
print(df.select("play_id", "epa", "wp").head())

xfl_pbp​

xfl_pbp