Examining the Effect of NCAA Systems in the NBA Examining the Effect of NCAA Systems in the Stanford Sports Analytics Club NBA Draft

Framework Regression Stanford Sports Analytics Club Analysis

Clustering Analysis Eli Shayer, Travis Chen, Nicholas Canova, and Ryan Chen

Play Type Homogeneity 2016 Analytics Summit Play Types

Results & Conclusions

1 Overview

Examining the Effect of NCAA Systems in the NBA Draft 1 Framework Stanford Sports Analytics Club 2 Regression Analysis

Framework

Regression 3 Clustering Analysis Analysis

Clustering Analysis 4 Play Type Homogeneity Play Type Homogeneity

Play Types 5 Play Types

Results & Conclusions 6 Results & Conclusions

2 Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis Framework Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

3 Framework

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework Framework to Assess NCAA Offensive Systems Regression Analysis Metric selection Clustering Definition of “star” & “bust” Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

4 Framework to Assess NCAA Offensive Systems

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

5 Framework to Assess NCAA Offensive Systems

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

6 Framework to Assess NCAA Offensive Systems

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

7 Framework to Assess NCAA Offensive Systems

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

8 Metric Selection

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

9 Metric Selection

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

10 Metric Selection

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

11 Stars and Busts

Examining the Effect of NCAA Systems in the NBA Draft Star Player Pick # Total WS Bust Player Pick # Net WS Stanford 2 38.3 Adam Morrison 3 -19.3 Sports 1 37.9 1 -17.4 Analytics Club Brandon Roy 6 35.4 2 -15.4 Damian Lillard 6 34.6 6 -14.9 Framework 3 33.7 Wesley Johnson 4 -12.3 3 33.3 Joe Alexander 8 -11.7 Regression 5 31.6 Thomas Robinson 5 -11.5 Analysis Derrick Rose 1 30.0 Patrick O’Bryant 9 -10.9 Blake Griffin 1 29.6 Dion Waiters 4 -10.8 Clustering Rajon Rondo 21 29.1 Corey Brewer 7 -10.7 Analysis ...... Play Type ...... Homogeneity 31 21.4 Luke Babbitt 16 -6.4 Ryan Anderson 21 20.9 14 -6.3 Play Types Brook Lopez 10 20.3 8 -6.1 Results & Conclusions

12 Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis Regression Analysis Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

13 Projections for Chad Ford’s Big Board

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Rank Name eWS 95% CI Rank Name eWS 95% CI Sports 1 16.4 (4.0, 28.8) 16 Skal Labissiere -7.0 (-19.4, 5.4) Analytics Club 2 3.1 (-7.2, 13.4) 17 11.6 (-2.5, 25.7) 3 Intl. – 18 -2.5 (-14.9, 9.9) 4 11.4 (-4.0, 26.8) 19 Timothe Luwawu Intl. – Framework 5 14.3 (-1.1, 29.7) 20 Intl. – 6 2.4 (-7.9, 12.7) 21 -1.7 (-10.3, 6.9) Regression 7 10.7 (-3.4, 24.8) 22 Ante Zizic Intl. – Analysis 8 1.8 (-8.5, 12.1) 23 Wade Baldwin IV 6.1 (-2.5, 14.7) Clustering 9 -2.1 (-17.5, 13.3) 24 2.1 (-12.0, 16.2) Analysis 10 Jakob Poeltl 11.5 (-0.9, 23.9) 25 DeAndre Bembry 7.4 (-8.1, 22.8) 11 9.0 (-1.3, 19.3) 26 Thomas Bryant -1.3 (-13.7, 11.1) Play Type 12 Ivan Rabb 9.5 (-0.8, 19.8) 27 Jonathan Jeanne Intl. – Homogeneity 13 Intl. – 28 7.8 (-4.6, 20.2) 14 13.9 (-1.5, 29.4) 29 16.1 (5.8, 26.4) Play Types 15 13.5 (3.2, 23.8) 30 Grayson Allen 14.8 (-0.6, 30.2)

Results & Conclusions

14 Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis Clustering Analysis Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

15 Cluster Analysis

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

16 Representative Players by Cluster

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Cluster Star Bust Description T S B Net WS/P Sports UF ’11 UConn ’09 Analytics Club 1 () (Hasheem Thabeet) Balanced 22 2 2 -0.105 Mich. St. ’12 Kansas ’12 –Iso 2 (Draymond Green) (Thomas Robinson) +P&R +Handoff 49 3 2 -0.082 Framework Marquette ’11 L’ville ’09 3 () () +Transition 62 4 5 -0.263 Regression Arizona St. ’09 UF ’07 Analysis 4 (James Harden) (Corey Brewer) +Spot-Up 43 5 1 1.058 Morehead St. ’11 Syracuse ’09 –P&R –Iso –Off-Screen Clustering 5 () (Jonny Flynn) +Cut +Spot-Up 13 1 4 -2.138 Analysis Texas ’07 Duke ’12 –Spot-Up 6 (Kevin Durant) (Austin Rivers) +Hand-Off +Iso 48 4 2 2.592 Play Type Davidson ’06 Gonzaga ’06 Homogeneity 7 () (Adam Morrison) +Iso 59 9 6 1.912 Fresno St. ’10 Kansas ’10 –P&R –Iso Play Types 8 (Paul George) (Cole Aldrich) +Post-Up 34 2 5 -0.976

Results & Conclusions

17 Net WS vs. Cosine Similarity of NCAA/NBA Systems

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

18 Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis Play Type Homogeneity Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

19 Play Type Homogeneity

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports All players average Euclidean distance: 0.1142 Analytics Club Position Star Average Dist Bust Average Dist

Framework All 0.1093 0.1426 Regression PG 0.1014 0.1813 Analysis SG 0.1107 0.1627 Clustering Analysis SF 0.0727 0.0904 Play Type PF 0.1325 0.0982 Homogeneity

Play Types C 0.0942 0.1764

Results & Conclusions

20 Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis Play Types Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

21 Stars vs. Busts Team Play Type Differential - Guards

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

Star PGs come from systems that emphasize transition and pick and roll passing 22 Stars vs. Busts Team Play Type Differential - Shooting Guards

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

Bust SGs tend to come from teams that emphasize post up and don’t spot up 23 Stars vs. Busts Team Play Type Differential - Small Forwards

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

The proportion of isolation and spot-up plays differentiates star and bust SFs 24 Stars vs. Busts Team Play Type Differential - Power Forwards

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

Star PFs come from systems that de-emphasize isolation & spot-up shooting and emphasize post-up scoring 25 Stars vs. Busts Team Play Type Differential - Centers

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

Star Cs tend to come from teams that transition often, perhaps as a result of defensive play, and fewer P&R Ball Handler plays 26 Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis Results & Conclusions Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

27 Thank you!

Examining the Effect of NCAA Systems in the NBA Draft Questions? Stanford Sports Analytics Club

Framework Eli Shayer [email protected] Regression Analysis Travis Chen [email protected] Clustering Nicholas Canova [email protected] Analysis Ryan Chen [email protected] Play Type Homogeneity Play Types stanfordsportsanalytics.com Results & Conclusions

28 Appendix A: Actual vs. Expected WS – 1st Round

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

29 Appendix B: Actual vs. Expected WS – Top 10

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

30 Appendix C: Actual vs. Expected WS: International Players

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

31 Appendix D: NCAA/Intl./HS Coach Comparison

Examining the Effect of NCAA Systems in the NBA Draft

Stanford 95% CI of Sports µWS σWS µE[WS] Analytics Club µNetWS International 3.0 5.3 4.4 -1.3 ± 0.9 Framework High School 9.3 12.6 8.2 1.1 ± 5.3 Regression Analysis NCAA 7.3 9.0 6.4 0.9 ± 0.8 Clustering Analysis w/ Top Coach 8.1 9.1 7.6 0.5 ± 1.3

Play Type w/o Top Coach 6.6 8.9 5.4 1.2 ± 1.1 Homogeneity

Play Types µNetWS = µWS − µE[WS] Results & Conclusions

32 Appendix E: Stars vs. Busts Individual Play Type Differential - Point Guards

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

33 Appendix F: Stars vs. Busts Individual Play Type Differential - Shooting Guards

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

34 Appendix G: Stars vs. Busts Individual Play Type Differential - Small Forwards

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

35 Appendix H: Stars vs. Busts Individual Play Type Differential - Power Forwards

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

36 Appendix I: Stars vs. Busts Individual Play Type Differential - Centers

Examining the Effect of NCAA Systems in the NBA Draft

Stanford Sports Analytics Club

Framework

Regression Analysis

Clustering Analysis

Play Type Homogeneity

Play Types

Results & Conclusions

37