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NBA All-Star Game Prediction

NBA All-Star Game Prediction. Pouya Fatemi Alex Wu Zinnia Horne. Why do we care?. $3.57 Billion in Revenue in the ‘07-’08 season 1 Games broadcasted in over 215 countries and territories 2 Fans in New York paid $74 million for tickets in the ’04-’05 season 2

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NBA All-Star Game Prediction

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  1. NBA All-Star Game Prediction Pouya Fatemi Alex Wu Zinnia Horne

  2. Why do we care? • $3.57 Billion in Revenue in the ‘07-’08 season1 • Games broadcasted in over 215 countries and territories 2 • Fans in New York paid $74 million for tickets in the ’04-’05 season 2 1http://www.plunkettresearch.com/Industries/Sports/SportsStatistics/tabid/273/Default.aspx 2http://www.forbes.com/2005/12/22/nba-team-valuations_cz_mo_1222nbaintro.html

  3. Probem • How can we most accurately predict the winner of the NBA All-Star Game? • What is the probability distribution of the points scored by an NBA All-Star team?

  4. Variables • Pw = total points scored by Western Conference = ∑ POSi • N = number of possessions per team per game • POSi , discrete random variable with possible values [0,1,2,3,4] – This represents the possible number of points scored in each possession

  5. Model Formulation • Most likely outcome (mode) after a possession is to score 0 points. • The next likely outcome is scoring two points. • The average number of points scored is 1.0973, with a standard deviation of 1.1074.

  6. Normal Approximated Distribution for Pw • Mean = N * [E(POSi)] = 90 * 1.0973 = 98.757 • Standard Deviation = (√N) * STD of POSi = (√90) * 1.1074 = 10.506 • Assumption: N (# of possessions team obtains in a game = 90)

  7. Sensitivity Analyses • Relationship between # of possessions (x-axis) and expected # of points scored (y-axis). • Assumed value in our model was N = 90 • Relationship between percentage of 2-pointers (x-axis) and expected # of points (y-axis).

  8. Possible Extensions • Effect of momentum • Treat seconds spent each possession as a random variable bounded by 0 < seconds spent <24

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