Tennis Major Tournament Match Statistics
Donated on 5/31/2014
This is a collection of 8 files containing the match statistics for both women and men at the four major tennis tournaments of the year 2013. Each file has 42 columns and a minimum of 76 rows.
Dataset Characteristics
Multivariate
Subject Area
Other
Associated Tasks
Classification, Regression, Clustering
Feature Type
Integer, Real
# Instances
127
# Features
42
Dataset Information
Has Missing Values?
Yes
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| Tournament | Feature | Categorical | no | ||
| Player1 | Feature | Categorical | no | ||
| Player2 | Feature | Categorical | no | ||
| Round | Feature | Integer | no | ||
| Result | Target | Binary | no | ||
| FNL1 | Feature | Binary | yes | ||
| FNL2 | Feature | Integer | yes | ||
| FSP.1 | Feature | Integer | no | ||
| FSW.1 | Feature | Integer | no | ||
| SSP.1 | Feature | Integer | no |
0 to 10 of 43
Additional Variable Information
Player 1 Name of Player 1 Player 2 Name of Player 2 Result Result of the match (0/1) - Referenced on Player 1 is Result = 1 if Player 1 wins (FNL.1>FNL.2) FSP.1 First Serve Percentage for player 1 (Real Number) FSW.1 First Serve Won by player 1 (Real Number) SSP.1 Second Serve Percentage for player 1 (Real Number) SSW.1 Second Serve Won by player 1 (Real Number) ACE.1 Aces won by player 1 (Numeric-Integer) DBF.1 Double Faults committed by player 1 (Numeric-Integer) WNR.1 Winners earned by player 1 (Numeric) UFE.1 Unforced Errors committed by player 1 (Numeric) BPC.1 Break Points Created by player 1 (Numeric) BPW.1 Break Points Won by player 1 (Numeric) NPA.1 Net Points Attempted by player 1 (Numeric) NPW.1 Net Points Won by player 1 (Numeric) TPW.1 Total Points Won by player 1 (Numeric) ST1.1 Set 1 result for Player 1 (Numeric-Integer) ST2.1 Set 2 Result for Player 1 (Numeric-Integer) ST3.1 Set 3 Result for Player 1 (Numeric-Integer) ST4.1 Set 4 Result for Player 1 (Numeric-Integer) ST5.1 Set 5 Result for Player 1 (Numeric-Integer) FNL.1 Final Number of Games Won by Player 1 (Numeric-Integer) FSP.2 First Serve Percentage for player 2 (Real Number) FSW.2 First Serve Won by player 2 (Real Number) SSP.2 Second Serve Percentage for player 2 (Real Number) SSW.2 Second Serve Won by player 2 (Real Number) ACE.2 Aces won by player 2 (Numeric-Integer) DBF.2 Double Faults committed by player 2 (Numeric-Integer) WNR.2 Winners earned by player 2 (Numeric) UFE.2 Unforced Errors committed by player 2 (Numeric) BPC.2 Break Points Created by player 2 (Numeric) BPW.2 Break Points Won by player 2 (Numeric) NPA.2 Net Points Attempted by player 2 (Numeric) NPW.2 Net Points Won by player 2 (Numeric) TPW.2 Total Points Won by player 2 (Numeric) ST1.2 Set 1 result for Player 2 (Numeric-Integer) ST2.2 Set 2 Result for Player 2 (Numeric-Integer) ST3.2 Set 3 Result for Player 2 (Numeric-Integer) ST4.2 Set 4 Result for Player 2 (Numeric-Integer) ST5.2 Set 5 Result for Player 2 (Numeric-Integer) FNL.2 Final Number of Games Won by Player 2 (Numeric-Integer) Round Round of the tournament at which game is played (Numeric-Integer)
Dataset Files
| File | Size |
|---|---|
| FrenchOpen-women-2013.csv | 16.9 KB |
| AusOpen-women-2013.csv | 16.6 KB |
| AusOpen-men-2013.csv | 16.5 KB |
| FrenchOpen-men-2013.csv | 16.5 KB |
| USOpen-men-2013.csv | 15.5 KB |
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset tennis_major_tournament_match_statistics = fetch_ucirepo(id=300) # data (as pandas dataframes) X = tennis_major_tournament_match_statistics.data.features y = tennis_major_tournament_match_statistics.data.targets # metadata print(tennis_major_tournament_match_statistics.metadata) # variable information print(tennis_major_tournament_match_statistics.variables)
Jauhari, S., Morankar, A., & Fokoue, E. (2014). Tennis Major Tournament Match Statistics [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C54C7K.
Creators
Shruti Jauhari
Aniket Morankar
Ernest Fokoue
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.