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NJIT mathematical sciences professor releases major league baseball predictions

March 28, 2019

NJIT Mathematical Sciences Professor and Associate Dean Bruce Bukiet has published his model's projections of how the standings should look at the end of Major League Baseball's regular season in 2019. For more than 20 years, Bukiet has applied mathematical models to compute the number of regular season games each Major League Baseball team should win. His mathematically derived projections have consistently compared well with those of so-called experts.

Bukiet bases his projections on a mathematical model he started developing in the late 1980s and has gone through several revisions. Among the many data points is a model of runner advancement. There are a possible 24 scenarios in which a batter may face a pitcher: three "out" situations (zero outs, one out, or two outs), and eight baserunner situations (no man on, man on first base, man on second base, man on third base, men on first and second base, men on second and third base, men on first and third base, and bases loaded). Calculating the probabilities of batter outcomes against opposing pitchers with the runner advancement model can enable one to forecast the results for each game, and thus the season.

For this season, Bukiet's projections for the American League (AL) and National League (NL) are:
  • AL East - Yankees (105 wins)

  • AL Central - Indians (98 wins)

  • AL West - Astros (103 wins)

  • NL East - Nationals (99 wins)

  • NL Central - Brewers (90 wins)

  • NL West - Dodgers (105 wins)

His results have been noted in many publications and he has been predictions champion at baseballphd.net several times. See more results for his baseball modeling, including the projected wins for each of the Major League Baseball teams at http://web.njit.edu/~bukiet/baseball/baseball.html and at http://www.egrandslam.com.

Professor Bukiet's video detailing his predictions can be viewed at https://www.youtube.com/watch?v=XYyj55MUxjQ.
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New Jersey Institute of Technology

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