1. P REDICTION OF NBA G AME P ACE Fa Wang

2. I NTRODUCTION Possession based NBA game prediction dominates What is Pace? Total score = ASPM (points/possession) * Pace(possession) Example 20131210 Brooklyn vs Boston with Pace: 92 20131203 Houston vs Utah with Pace: 98

3. F LOW C HART

4. D ATA S OURCE & F EATURES Play by Play(PBP) Data Team Average Attack/Defense Time Real-time Score Difference Game Stats Data History Pace Rest Info Altitude Injury

5. PBP data: http://stats.nba.com/http://stats.nba.com/ Game stats: http://www.basketball- reference.com/http://www.basketball- reference.com/

6. E XPERIMENT :F INAL MSE R ESULT Feature Set One: History Pace Feature Set Two: One + Attack/Defense Time Feature Set Three: Two + Rest + STD + Altitude…

7. C ONCLUSION & F UTURE W ORK Big data technology simplify programming as well improve efficiency Feature Engineering is essential Much to be done with PBP data

8. Q & A