# Physical fitness characteristics and comprehensive physical fitness evaluation model of basketball players based on association rule algorithm

## TL;DR

This paper uses data mining to analyze the physical fitness of basketball players and identify key factors affecting performance.

## Contribution

A novel physical fitness evaluation model for basketball players using the Apriori association rule algorithm.

## Key findings

- The study identified key physical characteristics influencing basketball performance.
- Association rule mining revealed relationships between different fitness indicators.
- The model offers insights for improving training and performance standards in college basketball.

## Abstract

Physical fitness refers to the health of all body functions, including cardiorespiratory endurance, muscle strength, flexibility, stamina, and body composition, which can help individuals effectively cope with daily activities and sports challenges. This paper explores the physical characteristics of basketball players, aiming to improve training effects through unique physical evaluation indicators and provide a theoretical framework for improving college basketball performance and training standards. The study adopted the Apriori association rule algorithm in data mining. First, the physical data of basketball players were collected and preprocessed. Then, frequent item sets were extracted through the association rule mining algorithm, association rules were generated, and the key factors affecting the physical performance of athletes were analyzed. The article’s results revealed the potential relationship between different physical characteristics and emphasized the application prospects of association rule mining in the physical evaluation of basketball players.