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by Jon Nichols *UPDATE: Euroleague statistics are also now included in BSPS: For more information, go to: http://basketballstatistics.com/euroleaguenowincludedintheboxscorepredictionsystem.html* One of the hardest things to project is a college player’s performance in the NBA. So many factors come into play, many of which can’t be measured. However, I have attempted to solve this problem. Using regression analysis, I have developed the Box Score Prediction System (BSPS). The system works on the basis of a player’s statistical performance at the college level. It also takes into account a player’s height, weight, and NCAA experience. With BSPS, I can input the various data about a player and it will shoot out the projected NBA numbers. Each NBA box score statistic is calculated based on some combination of the above variables and different coefficients. Certain NBA stats, such as rebounds, can be predicted using many different variables. The adjusted R^2 values (go to http://en.wikipedia.org/wiki/Coefficient_of_determination for an explanation) for the NBA stats I project are as follows: Points: 0.4557 As you can see, we can project with the most certainty blocks, rebounds, assists, free throw percentage, and threepoint percentage. Predictions regarding free throw attempts, points, field goal attempts, turnovers, and fouls are the most questionable. At this time I’m not willing to give out the exact formulas I use, but in the future I will be predicting various college players’ future performances in the NBA using their college stats. BSPS has the following limitations:
This system is still a work in progress and tweaks will inevitably be made in the future. Also, I may include projections of advanced stats such as Composite Score. If you have any comments or suggestions, please send them to [email protected].
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