Tennis Match Analysis: Players' Time And Events' by Kaggle | Sports

About this Dataset

Tennis Match Analysis: Players' Time And Events'

Tennis Match Analysis: Players' Time and Events' Time

Analyzing Match Time, Surfaces, and Tournaments

By FiveThirtyEight [source]

About this dataset

This dataset contains data from a collection of professional tennis matches that took place between 2008 and 2019. It provides an in-depth analysis into the time played by each player, and factors such as tournament, surface and years taken into account. By utilizing this dataset, one can gain an interesting insight into the amount of time added to each point for every player in professional tennis match-ups. This data can then be used to analyze a variety of trends such as how increases or decreases in time spent per point affected a player's performance over different tournaments and surfaces during the period analysed. As such, we invite you to explore this dataset further – whether through your own stories or interactive visualizations – to uncover new patterns concerning the timing of play in professional tennis match-ups!

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How to use the dataset

This dataset provides information on how long tennis matches last when factoring in strokes, points, and rest periods. It also provides tournament-specific data on match length as well as surface-specific information.

This guide will provide an overview of the dataset and explain how you can use it to conduct thorough tennis match analysis.

Understanding the Data Columns

The dataset consists of a total of seven column features which are explained below:

Player: The name of the player participating in the match. (String)

Seconds Added per Point: The amount of time (in seconds) added to a match for each point played by a player. (Integer)

Tournament: The name of the tournament where the match was played. (String)

Surface: The type of court surface used for play during the match. There are three types included here – Hard, Clay, and Frictionless Court – with all other types falling under “Other”.(String)

Years : The year in which the match was played out.(Integer).

Analyzing Tennis Match Lengths with this Dataset

Armed with an understanding of what this dataset tracks, we can begin our analysis by looking at different scenarios related to tennis players and tournaments over different surfaces or years. For example, you might want to investigate which tournament produces matches that have longer average lengths than others or what is making them last so long? Was it because more points were being scored compared to other matches? Or were it due simply due to number additions based on restart times after each point? You could even look into whether certain players tend towards longer or shorter matches than others when playing against any given opponent or under any particular conditions related to surfaces or tournaments over specific years etc.

Research Ideas

Identifying players with the highest amount of playing time in certain tournaments, surface types or years to draw conclusions on the best performing players.

Investigating any correlations between time added per point and the surface type of a match to determine if certain surfaces are faster or slower than others.

Analyzing patterns of how different tournaments affect playing times across different player types and surfaces to better understand which tournament structures yield longer games per point/set/match

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: players_time.csv

Column name	Description
player	The name of the player. (String)
seconds_added_per_point	The amount of time added for each point played. (Float)

File: events_time.csv

Column name	Description
seconds_added_per_point	The amount of time added for each point played. (Float)
tournament	The name of the tournament. (String)
surface	The type of surface where the match was played. (String)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit FiveThirtyEight.

Tables

Events Time

@kaggle.thedevastator_tennis_match_analysis_players_time_and_events_ti.events_time

8.77 KB
205 rows
5 columns


CREATE TABLE events_time (
  "index" BIGINT,
  "tournament" VARCHAR,
  "surface" VARCHAR,
  "seconds_added_per_point" DOUBLE,
  "years" VARCHAR
);

Players Time

@kaggle.thedevastator_tennis_match_analysis_players_time_and_events_ti.players_time

8.37 KB
218 rows
3 columns


CREATE TABLE players_time (
  "index" BIGINT,
  "player" VARCHAR,
  "seconds_added_per_point" DOUBLE
);

Serve Times

@kaggle.thedevastator_tennis_match_analysis_players_time_and_events_ti.serve_times

7.51 KB
120 rows
8 columns


CREATE TABLE serve_times (
  "index" BIGINT,
  "server" VARCHAR,
  "seconds_before_next_point" BIGINT,
  "day" VARCHAR,
  "opponent" VARCHAR,
  "game_score" VARCHAR,
  "set" BIGINT,
  "game" VARCHAR
);