How Basketball Statistics Affect Winning Percentage for a NCAA Division 1 Team

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How Basketball Statistics Affect Winning Percentage for a NCAA Division 1 Team

We tried to find out how certain basketball statistics affect winning percentage for a NCAA Division I basketball team. We used the entire NCAA division I 1999-2000 season statistics. We considered the following statistics: Field Goals, Free Throws, Personal Fouls, Turnovers, 3 Pointers, Blocks, & Steals.

Our conclusion is that while a rise in each stat had some affect in the rise or fall of winning percentage, we could not determine a single stat that had a direct affect on the dependent variable (Winning Percentage). Our results were more effective when we ran the test on how the combination of all stats affected winning percentage, however, this would be obvious given the nature of our study.

While this study did not produce the result we wanted, we believe that we could use the information learned from this study and develop a study that would be more effective.

Introduction

Coaches are always looking for a better understanding of what makes up a winning team. This knowledge would help them in recruiting athletes that could improve the team’s statistics in the areas we observed. We took the entire statistical breakdown from the 1999-2000 season and were hoping to find any key statistical areas that could be directly related to winning percentage.

Methodology

We will run regression analysis on how each independent variable affects the dependent variable individually and in total. The dependent variable is winning percentage, and the stats we measured were selected as the independent variables. The independent variables that we chose were: Field Goals per Game, Free Throws per Game, Assists per Game, Fouls per Game, Turnovers per Game, 3 Pointers per Game, Blocks per Game, Steals per Game & Rebounds per Game.

Our statistics were gathered from www.cbssportsline.com. We will use these statistics to run a regression analysis to see if any one statistic could be used to predict winning percentage.

Findings

This section includes the actual statistical calculations. It shows the calculations of how each statistical variable affected winning percentage individually and how in combinations the same statistical variables affected winning percentage.

The data we gathered from our analysis are presented in a formal way on the following page.

Regression Steals Turnovers Committed Made Field Goals Made Free Throws

Statistics Per Game Per Game Per Game Per Game

Multiple R 0.228547 0.429836 0.510207 0.384329

R Square 0.052234 0.184759 0.260311 0.147709

Adjusted R Square 0.049234 0.182179 0.257970 0.145011

Standard Error 0.177928 0.165020 0.157188 0.168728

Observations 318 318 318 318

Regression Made 3 Pointers Blocked Shots Personal Fouls All Variables

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