WSBA HOCKEY

WSBA128

A Python package for scraping and analyzing hockey data under the motto: Evaluating, analyzing, and understanding the game of hockey through the lens of different analytical methods.

INSTALLATION AND USAGE

pip install wsba_hockey

import wsba_hockey as wsba

ALL FEATURES

SCRAPING

NHL Play-by-Play (of any game frame up to a full season)

Functions:

wsba.nhl_scrape_game(2024020918,split_shifts=False,remove=['game-end'])
wsba.nhl_scrape_season(20242025,split_shifts=False,remove=['game-end'],local=True)

Reusing Scrapy-backed Sessions

import wsba_hockey as wsba

with wsba.make_pooled_session() as session:
    games = [2024020918, 2024020919]
    pbp = [wsba.nhl_scrape_game(game, session=session) for game in games]

The session uses Scrapy internally while preserving the package's synchronous API. Scrapy remote control is disabled because it is not used by the client.

NHL Season Information

wsba.nhl_scrape_schedule(20242025)
wsba.nhl_scrape_seasons_info(seasons=[20212022,20222023,20232024,20242025])
wsba.nhl_scrape_standings()

NHL Rosters and Player Information

wsba.nhl_scrape_roster(20242025)
wsba.nhl_scrape_player_info([8477956, 8479987])
wsba.nhl_scrape_team_info()

NHL Draft Rankings and Prospects

wsba.nhl_scrape_draft_rankings()
wsba.nhl_scrape_prospects('BOS')

NHL EDGE Data

wsba.nhl_scrape_edge(20252026,'skater',[8477956, 8479987])
wsba.nhl_scrape_edge(20252026,'goalie',[8480280])
wsba.nhl_scrape_edge(20252026,'team',['BOS'])

NHL Event Tracking Data

wsba.nhl_scrape_event_data({2023020001: [101, 102]})

DATA ANALYTICS

Expected Goals

pbp = wsba.nhl_scrape_game(2024020918,split_shifts=False,remove=['game-end'])
pbp = wsba.nhl_apply_xG(pbp)

Goal Impacts and Shot Analysis

Stat Aggregation

pbp = wsba.nhl_scrape_season(20232024, local = True)
wsba.nhl_calculate_stats(
    pbp,
    'skater',
    ['5v5', '4v4', '3v3'],
    season_types=[2, 3],
)

Shot Plotting (Plots, Heatmaps, etc.)

pbp = wsba.nhl_scrape_season(20212022, remove=[], local=True)

plots = wsba.nhl_plot_events(
    pbp,
    group="game",
    entities=[2021020002],
    events=["goal", "shot-on-goal", "missed-shot", "blocked-shot"],
    strengths=["5v5"],
    season_types=2,
    legend=True,
    rotation=0,
    display_range="full",
)
plots[2021020002].savefig("skater_events.png", bbox_inches="tight")

Sample Plot:

Sample Plot

REPOSITORY

Team Information

wsba.repo_load_teaminfo()
wsba.repo_load_rosters(seasons=[20212022,20222023,20232024,20242025])

Schedule

wsba.repo_load_schedule(seasons=[20212022,20222023,20232024,20242025])

DOCUMENTATION

View full documentation here: WSBA Hockey Package Documentation

EXPORTING DATA

Tabular scraping functions return Polars DataFrames that can be written directly to CSV or Parquet:

data = wsba.nhl_scrape_edge(20252026, "skater", [8477956])
data.write_csv("edge.csv")
data.write_parquet("edge.parquet")

API fields that contain lists or structs, such as player badges and EDGE detail data, are stored as JSON strings in the returned table so both formats remain portable.

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for OSv38 from gravatar.com OSv38

Credits

Author: Owen Singh

License

MIT License

Requires

Python >=3.8

Tags

wsba hockey scraping NHL analytics

Classifiers

Report project as malware

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