Team Performance Indicators Explain Outcome of Women’s 3x3 Basketball at Tokyo 2020 Olympics

Inhalt:
This study aimed to analyze the team performance indicators in winning and losing teams in women's 3x3 basketball at Tokyo 2020 Olympics. Machine learning models for data mining in the most cutting-edge quantitative research on basketball performance analysis. K-means clustering algorithm was used to classify the matches into two types such as balanced games and unbalanced games. The cluster analyzes the data via the “kmeans” function in the “cluster” package by R (version 4.1.3). There were 16 of these matches that were balanced matches where the differences between the two teams were 6 points or less. For each match, the team performance indicators were collected from the FIBA website. The performance indicators of all matches (n=34) of the women's 3x3 basketball at Tokyo 2020 Olympics were normalized by the minute. Differences between winning and losing teams were calculated using significance p-value and effect size. Winning teams showed a higher one-point field goal percentage, one-point field goal made, free throw made, defensive rebounds, foul against, and a lower foul which indicators have a significant large effect compared to losing teams in all matches. Winning teams showed a higher free throw attempet, defensive rebounds, foul against, free throw made, and a lower foul which indicators have a significant large effect compared to losing teams in balanced matches. Coaches should use these results to optimize their training sessions, focusing on those indicators that might increase the possibility to win matches. Further, examination of athlete workloads during matches, possibly via wearable technology, in conjunction with team performance indicators may identify successful team profiles to assist coaches with strategic planning during an international elite 3x3 basketball competition.