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Illini Football Dataset (All Games Since 1892)


The "Football Dataset" contains every game played by the University of Illinois' football team from 1892 through the end of the 2020 season.

  • Dataset Format: Well-formatted CSV with column headers as the first row
  • Dataset Size: 1,259 rows ร— 9 columns
  • CSV File Location: https://waf.cs.illinois.edu/discovery/football.csv
  • Dataset Variables:
    • Season : number โžœ The season when the game was played. Usually the same as Year, except for some rate January games (ex: bowl games)
    • Date : string โžœ The date when the game was played
    • Location : string โžœ vs. for home games; @ for away games; the city, state for games at neutral sites (ex: Chicago, IL)
    • Opponent : string โžœ The name of the opponent (ex: Purdue)
    • OpponentRank : number โžœ The NCAA rank of the opponent (only available for very recent seasons) or blank
    • Result : string โžœ W for an Illini win; L for an Illini loss; T for a tied game
    • IlliniScore : number โžœ The final score for the University of Illinois
    • OpponentScore : number โžœ The final score for the opponent
    • Note : string โžœ Notes for bowl games (ex: Rose Bowl), homecoming (Homecoming), or cancelled games (ex: Canceled (COVID-19))

Using the Football Dataset in Python

The dataset can be loaded using the pandas library in Python:

import pandas as pd
df = pd.read_csv("https://waf.cs.illinois.edu/discovery/football.csv")
df
SeasonDateLocationOpponentOpponentRankResultIlliniScoreOpponentScoreNote
0202010/23/2020@Wisconsin14.0L7.045.0NaN
1202010/31/2020vs.PurdueNaNL24.031.0NaN
2202011/7/2020vs.MinnesotaNaNL14.041.0NaN
3202011/14/2020@RutgersNaNW23.020.0NaN
4202011/21/2020@NebraskaNaNW41.023.0NaN
..............................
125418921892-10-29@Kansas City A.C.NaNW42.00.0NaN
125518921892-11-05vs.Englewood HighNaNW38.00.0NaN
125618921892-11-16@ChicagoNaNL4.010.0NaN
125718921892-11-18vs.DePauwNaNW34.00.0NaN
125818921892-11-24vs.ChicagoNaNW28.012.0NaN

The full Football Dataset stored in a DataFrame (1,259 rows).

Pages Using the Football Dataset

  1. Learn Page: Grouping Data in Python
  2. Learn Page: Basic Data Visualization in Python
  3. Video Walk-Through & Worksheet: Learn Page: Reading Histograms (Part 2)