Australian Open Tennis (2008-2022)

two-way tables
Results from matches at the Men’s Australian Open Tennis Tournament between 2008 and 2022.

Trent Meyer, Robin Lock


August 3, 2023


The Australian Open is an annual tennis tournament in Melbourne, Australia. We have data from the men’s tournament in the years 2008-2022, with variables for both the winner and loser of each match, along with information such as what hand they play with and their Association of Tennis Professionals (ATP) rank and characteristics of the players. Which characteristics might help predict the outcome of the matches?


Each row of data gives 19 variables of information for one of the 1905 Men’s Australian Open matches played between 2008 and 2022.

Variable Description
Year Year (2008-2022)
Winner winner of the match
Loser loser of the match
WRank winning player’s rank
LRank losing player’s rank
pl1_flag winning player’s country they choose to represent
pl1_year_pro winning player’s first year as a professional
pl1_weight winning player’s weight in kilograms
pl1_height winning player’s height in centimeters
pl1_hand winning player’s handedness that they play with
pl2_flag losing player’s country they choose to represent
pl2_year_pro losing player’s first year as a professional
pl2_weight losing player’s weight in kilograms
pl2_height losing player’s height in centimeters
pl2_hand losing player’s handedness that they play with
higher_rank_won Did the higher rank win? Yes orNo
rank_diff difference in rank between the players
rank_diff_cat categroies for difference in rank between the players: Low (30 or less), Medium (31-75), High (more than 75)
same_handedness Do the players have the same handedness? Yes or No

: AustralianOpenLater.csv has the same variables (with the addition of a Round variable), but only for 105 matches from the quarterfinals, semifinals, and finals each year.


  1. What proportion of time does the higher (ATP) rank player win?

  2. Does the proportion of higher ranked wins change much when the players play with opposite hands (i.e. a right-handed player vs. a left-handed payer)

  3. Construct a two-way table of higher_rank_won vs. rank_diff_cat and see if teh two variables appear to be related.

  4. Investigate a logistic regression model to predict it the higher ranked player wins using the difference in ranks as the predictor.

  5. Are the results for any of these questions much different if we consider only matches in the later rounds for the tournament (quarterfinals, semifinals, and finals) in AustralianOpenLater.csv?


The data are a subset of the data found at Kaggle.