sportsR

The sportsR package offers a rich and diverse collection of datasets focused on sports, athletics, physical performance, and related disciplines. It includes comprehensive professional and amateur sports data covering team sports such as soccer, basketball, baseball, American football, volleyball, rugby, cricket, hockey, and handball, as well as individual sports including tennis, badminton, table tennis, golf, swimming, cycling, athletics, gymnastics, wrestling, boxing, martial arts, weightlifting, triathlon, rowing, canoeing, climbing, surfing, skiing, snowboarding, and motorsports.

The package contains a wide variety of data types, including player and team performance, match statistics, tournament results, championship standings, Olympic and international competitions, rankings, player demographics, coaching and training, biomechanics, sports medicine, injuries, exercise physiology, fitness assessment, sports nutrition, wearable sensor measurements, talent identification, and sports analytics. Additional datasets encompass historical competitions, referee decisions, fan engagement, economic indicators, and sports management data obtained from public repositories, official organizations, research publications, and educational resources. Designed for sports scientists, coaches, analysts, researchers, educators, students, and data scientists, this package facilitates exploratory data analysis, statistical modeling, machine learning, visualization, and sports analytics research.

Installation

You can install the sportsR package from CRAN with the following R function:

install.packages("sportsR")

You can install the sportsR package from its GitHub repository with the following R function:

devtools::install_github("lightbluetitan/sportsR")

Example Datasets

Below are selected example datasets included in the sportsR package:

• atp_matches_2019: ATP tennis match results and player performance statistics from the 2019 season.
• english_football: Match results, standings, and seasonal team performance in English soccer.
• italian_football: Match statistics and standings for Italian professional football leagues.
• mlb_teams_2024: Major League Baseball team performance metrics, standings, and season indicators for 2024.
• pga_results: Professional Golf Association tournament results, scores, and player statistics.
• warriors_2016: Golden State Warriors team performance and game-by-game statistics from the 2016 NBA season.

Example Code

# Load the package
library(sportsR)

# List all datasets in the package
view_datasets_sportsR()

# Load dataset
data(atp_matches_2019)

# Preview the dataset
head(atp_matches_2019)

# Open in Viewer
View(atp_matches_2019)