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University of Cincinnati
Basketball + quantitative analysis = master's degree at the University of Cincinnati
Combining love of sports and business at the University of Cincinnati
Paul Bessire has always loved sports. He grew up in Wisconsin, a fan of the Green Bay Packers. Being tall, and with two brothers, he frequently played pick-up games of basketball. He carried his love of sports into his choice of school and career. When it came time for him to choose a college, he narrowed his list to Duke, Arizona, Utah, William & Mary and the University of Cincinnati.
"Four of those schools were ranked in the top 25 in college basketball," Bessire points out. "UC and Duke were Nos. 1 and 2. I chose UC because of the great business school." Bessire admits that he made the final decision based on the school's academic programs, but he was first attracted by its success in basketball.
Bessire graduated in 2004 from UC with a bachelor's degree in finance and quantitative analysis from the college of business. He still had scholarship money left, so he applied for graduate school at UC's college of business again. In June 2005, he earned a Master's of Science degree in quantitative analysis ("MSQA"). The MSQA degree combines applied mathematics, statistics and computer applications in a business environment. The MSQA includes what is often called operations research and applied statistics. This degree helps UC graduates excel in all corners of the business world - not to mention sports.
"My love of numbers - and the fact that I could apply them to sports - led me to the MSQA program," says Bessire. After graduation, he took a full-time job doing data analysis for WhatIfSports.com, a sports simulation company.
What does quantitative analysis have to do with sports? At the end of the 2003-04 National Basketball Association season, the Detroit Pistons won the NBA championship. They didn't have a single player among the NBA's top ten scoring leaders. On the other hand, Team USA - made up of the most individually talented players in the world - failed to win gold as a team in the 2004 Olympics. How could this happen?
Bessire analyzed basketball teams' success (or failure) mathematically. He published the results of his research in his paper "Measuring Individual and Team Effectiveness in the NBA Through Multivariate Regression." This paper is required to earn his Master's degree.
"We believe that much of the variation found in a basketball team's success can be explained mathematically through looking at the interactions of the five players on the court and not just individual player abilities," says Paul Bessire. For this project, Bessire examined several methods for rating individual NBA players and used multivariate regression analysis to assist in building successful NBA teams.
"Multivariate regression is probably much simpler than it sounds," says Bessire. Multivariate regression is a mathematical approach to comparing many variables that have an effect on the outcome of a situation.
Bessire's model could be used to determine which players should play at each position, to predict the lineups that should have the greatest team success and to specify which skill areas the coaching staff should look to fill through the annual NBA draft, free agency and trades. For example, the paper applies the model to some trades that occurred in February 2005.
"For instance, it shows that a trade that sent Chris Webber, Matt Barnes and Michael Bradley of the Sacramento Kings to Philadelphia for the 76ers' Brian Skinner, Corliss Williamson and Kenny Thomas benefits both teams," Bessire says. "The 76ers get offensive help on the interior, something they needed immensely, and the Kings receive interior defense in return. Previous to the trade, the Kings had two similar players starting down low with Brad Miller and Webber. The 76ers started Thomas and Samuel Dalembert, also two similar players. Redundancy is inefficient so both teams improve."
On the other hand, in the trade of the Warriors' Speedy Claxton and Dale Davis for the Hornets' Baron Davis, neither team is helped (on the court).
"The analysis explains that the point guard position is overvalued in the NBA," Bessire says. "Any team that has a competent point guard, one who can pass well - which is almost every team - should not worry about an upgrade at that position. NBA teams do not differentiate themselves at the point guard position. Passing ability is important, but it is generally more important for a lineup to upgrade passing ability at the power forward and swing forward positions."
So did Bessire have any predictions for the playoffs?
"Unfortunately, the model cannot be used too effectively in predicting the NBA playoffs," he says. "The limited number of games allow for too many other factors to play a role in the outcome."
If you want to know more about quantitative analysis of basketball, visit Bessire's Web page. www.WhatIfSports.com
To learn more about the University of Cincinnati, business or basketball, visit www.uc.edu.