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Contact Information: Tanya Klein Public Relations 973-596-3433

NJIT Math Professor Calls Detroit Tigers a Favorite to Win World Series

Since the Major League Baseball Division Series and League Championship Series have determined which teams will compete in the World Series, NJIT Math Professor Bruce Bukiet has again analyzed the probability of each team taking the title.

“The Detroit Tigers have a solid advantage over the San Francisco Giants.  The Tigers, who surprisingly swept the New York Yankees in four straight games in the American League Championship Series to reach the World Series, have a 58 percent chance of beating the Giants in the best of seven series,” he said.

At the season’s start, Bukiet used his mathematical model to project the number of wins each team should earn (http://m.njit.edu/~bukiet/baseball/SeasonProjections2012.html).  While Bukiet’s model picked only six of the ten post-season teams back in March (including the Tigers but not the Giants), he said that his performance was still comparable with many experts.  Bukiet updates the probabilities of each team taking their series throughout the Major League Baseball post-season at http://m.njit.edu/~bukiet/baseball/playoffs12.htm.

For the National League Championship Series, Bukiet’s model had the St. Louis Cardinals as large favorites (68 percent chance of winning) over the San Francisco Giants and the Cards jumped out to a 3 games to 1 lead, but the Giants won the final three games to make it into the World Series. Bukiet’s model had the Tigers as slight favorites (53 percent chance of winning) over the Yankees.

On Bukiet’s website, he provides the likelihood of each team taking the series in a given number of games.  Going into the series, the most likely outcome (20 percent) is for the Tigers to win in five games.  The Giants most likely winning scenario is their 17% chance of winning the series in seven games.

This is Bukiet’s 12th year using his model to determine whether it is worthwhile to wager on games each day during the baseball season.  His picks (posted on www.egrandslam.com) have led to positive results for 8 of the 12 years (counting 2012’s thus far positive performance).  He has also used the model to predict how teams should perform during a baseball season and these results have compared favorably with experts over the years.  In addition, the method enables one to rank player performance during the season in terms of the influence on the number of wins a given player would have added (or taken away) from an average team.  This allows the computation of who really should win the Most Valuable Player and Cy Young Awards.  Bukiet will publish those results for 2012 in the coming week.

Bukiet’s model originally appeared in the journal Operations Research.  More recent improvements were published by Bukiet and his research team in the International Journal of Performance Analysis in Sports.  The model computes the probability of a team with given hitters, bench, starting pitcher, lineup, relievers and home field advantage winning a game against another team. 

Contact: Bruce Bukiet, bukiet@m.njit.edu, 973-596-8392.

One of the nation's leading public technological universities, New Jersey Institute of Technology (NJIT) is a top-tier research university that prepares students to become leaders in the technology-dependent economy of the 21st century. NJIT's multidisciplinary curriculum and computing-intensive approach to education provide technological proficiency, business acumen and leadership skills. With an enrollment of more than 10,000 graduate and undergraduate students, NJIT offers small-campus intimacy with the resources of a major public research university. NJIT is a global leader in such fields as solar research, nanotechnology, resilient design, tissue engineering, and cyber-security, in addition to others. NJIT ranks 5th among U.S. polytechnic universities in research expenditures, topping $110 million, and is among the top 1 percent of public colleges and universities in return on educational investment, according to PayScale.com.