Disciplines
Statistical Models
Abstract (300 words maximum)
The average salary of a Women’s National Basketball Association (WNBA) player is 110 times less than a National Basketball Association (NBA) player’s. Despite growing WNBA viewership, gender inequality in sports remains high, with critics claiming female athletes are less skilled. Gender bias in sports is severely understudied, making direct comparisons to men’s leagues unfair due to long-term lack of investment in women’s sports. This study investigates whether the perceived disparity in skill levels between WNBA and NBA players' is genuine or influenced more by external factors by developing an unbiased measure of player efficiency to compare athletic performance. This dataset was sourced from Basketball-reference.com and cleaned to remove duplicates and observations with missing values, resulting in 555 players (166 WNBA, 389 NBA). Extreme outliers were assessed. An unbiased measure for comparing player efficiency (dependent variable) was developed: Efficiency=(Points+Rebounds+Assists+Steals+Blocks)–(Missed Shots+Turnovers)/100 Team Possessions. A multiple linear regression model was conducted. Independent variables included games played, games started, personal fouls, organization and the interaction between games started and organization. Average efficiency of WNBA players was 24.2 (SD=8.1) points and 26.5 (SD=8.2) for NBA players. Multiple linear regression revealed that 23.6% of the variation in efficiency was explained by games started, games played, personal fouls, organization, and games started*organization, (R²=0.236, F(5)=33.54, p<0.001). Number of games started had a stronger effect on NBA players' efficiency than WNBA players. Specifically for every additional game started by an NBA player, efficiency decreased by .200 units on average, compared WNBA players (t=-4.63, p<0.001). Findings indicate that WNBA players are not less skilled than NBA players, but games started significantly impacts NBA players differently than WNBA players. These results emphasize the need for greater investment in female sports’ data collection and research to create a more equitable comparison of performance between genders.
Academic department under which the project should be listed
CCSE - Data Science and Analytics
Primary Investigator (PI) Name
Dr. Lauren Matheny
Included in
Sabrina vs Steph: The Battle Between the WNBA and NBA
The average salary of a Women’s National Basketball Association (WNBA) player is 110 times less than a National Basketball Association (NBA) player’s. Despite growing WNBA viewership, gender inequality in sports remains high, with critics claiming female athletes are less skilled. Gender bias in sports is severely understudied, making direct comparisons to men’s leagues unfair due to long-term lack of investment in women’s sports. This study investigates whether the perceived disparity in skill levels between WNBA and NBA players' is genuine or influenced more by external factors by developing an unbiased measure of player efficiency to compare athletic performance. This dataset was sourced from Basketball-reference.com and cleaned to remove duplicates and observations with missing values, resulting in 555 players (166 WNBA, 389 NBA). Extreme outliers were assessed. An unbiased measure for comparing player efficiency (dependent variable) was developed: Efficiency=(Points+Rebounds+Assists+Steals+Blocks)–(Missed Shots+Turnovers)/100 Team Possessions. A multiple linear regression model was conducted. Independent variables included games played, games started, personal fouls, organization and the interaction between games started and organization. Average efficiency of WNBA players was 24.2 (SD=8.1) points and 26.5 (SD=8.2) for NBA players. Multiple linear regression revealed that 23.6% of the variation in efficiency was explained by games started, games played, personal fouls, organization, and games started*organization, (R²=0.236, F(5)=33.54, p<0.001). Number of games started had a stronger effect on NBA players' efficiency than WNBA players. Specifically for every additional game started by an NBA player, efficiency decreased by .200 units on average, compared WNBA players (t=-4.63, p<0.001). Findings indicate that WNBA players are not less skilled than NBA players, but games started significantly impacts NBA players differently than WNBA players. These results emphasize the need for greater investment in female sports’ data collection and research to create a more equitable comparison of performance between genders.