Game Resultsο
Team Resultsο
- ncaa_scraper.ncaa_team_results(school, season):
Obtains the results of games for a given school in a given season, from stats.ncaa.org
- School:
school name (str) or NCAA school_id (int)
- Season:
season (int, YYYY) or NCAA season_id (int), valid 2013-2022
- Return (pd.DataFrame):
- boydsworld_scraper.boydsworld_team_results(school, start, end=None, vs="all", parse_dates=True):
A function to scrape Division I game results, from boydsworld.com
- School (str):
team whose games to select
- Start (int):
the start year of games, 1992 <= x <= 2022
- End (int, optional):
the end season of games, 1992 <= x <= 2022
- Vs (str, optional):
school to filter games against. default: βallβ
- Parse_dates (bool, optional):
whether to parse data into datetime64
- Return (pd.DataFrame):
of all games played for a given team inclusive of start & end
- win_pct.calculate_actual_win_pct(games):
A function to calculate the winning percentage as # games won / # games plated
- Games (pd.DataFrame):
from boydsworld_team_results()
- Return (tuple):
of actual winning percentage (float), wins (int), ties (int), losses (int)
- win_pct.calculate_pythagenpat_win_pct(games):
A function to calculate the the PythagenPat expectated winning percentage. Pythagenpat Expectation formula (developed by David Smyth and Patriot):
W% = R^x/(R^x + RA^x) where x = (RPG)^.287 Developed by David Smyth and Patriot
- Games (pd.DataFrame):
from boydsworld_team_results()
- Return (tuple):
of expected winning percentage as a float, total run differential as int