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S. Henry1, R.L. Herron2, E. Zumbro1, K.J. Weiss3, & G.A. Ryan1

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Presentation on theme: "S. Henry1, R.L. Herron2, E. Zumbro1, K.J. Weiss3, & G.A. Ryan1"— Presentation transcript:

1 S. Henry1, R.L. Herron2, E. Zumbro1, K.J. Weiss3, & G.A. Ryan1
PREDICTING 2015 NBA ROOKIE CLASS ON-COURT CONTRIBUTION USING draft COMBINE MEASUREABLES S. Henry1, R.L. Herron2, E. Zumbro1, K.J. Weiss3, & G.A. Ryan1 1Georgia Southern University, Statesboro, GA 2The University of Alabama, Tuscaloosa, AL 3Auckland University of Technology, Auckland, NZ Methods Results Abstract The National Basketball Association (NBA) conducts an annual combine to assess anthropometric/athletic measures in preparation for the draft. PURPOSE: The purpose was to determine how well the measures of the athletes invited to the 2015 NBA Combine predicted on-court contribution, as measured by Player Impact Estimate (PIE). METHODS: Data from 12 tests (six anthropometric, six performance) of 64 athletes were used for analysis. Player contribution was measured in PIE (player's overall statistical contribution against the total statistics in played games). A multiple linear regression was calculated to predict on-court contribution based on the 12 variables recorded during the NBA Combine. RESULTS: A significant regression omnibus equation was found (F(12,21) = 3.278, p = 0.041; R2 = 0.814). Three-quarter sprint performance was the most predictive of all variables (F(1,21) = 4.514, p = 0.046; R2 = 0.184). Predicted average PIE = (3/4 court sprint), 95% CIs [ , 6.854] and [0.210, ]. CONCLUSIONS: The findings of this study suggest that the performance testing conducted at the 2015 NBA Combine could partially predict on-court contribution during the 2015 NBA regular season, though R2 prediction was varied. These findings may help teams and scouts to assess performance and determine potential on-court contribution of draftees/undrafted free agents. Measures of the 2015 NBA Draft Combine, and Rookie season performance were analyzed for this study. 63 athletes were analyzed: 15 PGs, 13 SGs, 9 SFs, 20 PFs, 6 Cs Predicted on-court contribution measured by Player Impact Estimate (PIE). PIE measures a player’s overall statistical contribution against the total statistics in games they play in. Similar to other advanced statistics (e.g. PER). Data from 12 tests at done the 2015 NBA Combine were used for analysis. 6 Anthropometric tests: body fat percentage, hand length, hand width, height, standing reach, wingspan. 6 Performance tests: lane agility drill, reactive shuttle test, three-quarter court sprint, standing vertical leap, maximum vertical leap, bench max repetitions (185lb). A multiple linear step-wise regression was calculated to predict on-court contribution (PIE) based on the 12 measurables from the 2015 NBA Combine. A significant regression equation was found [Enter method]: (F(12,21) = 3.278, p = 0.041; R2 = 0.814). Three-quarter sprint performance was the only single significant predictor of all variables. Predicted average PIE = (3/4 court sprint), 95% CIs [ , 6.854] & [0.210, ]. F(1,21) = 4.514, p = 0.046 R2 = 0.184 Conclusion Data suggests that the performance testing conducted at the Combine can partially predict on-court performance. Performance/Measurables data is highly variable, due in part to a incomplete sample 20 drafted rookies did not participate in the 2015 NBA Combine. Introduction The National Basketball Association (NBA) conducts a yearly draft combine to assess the anthropometric and athletic measures of potential draftees. The Draft combine is designed to aid team scouts and general managers in deciding which athletes to draft, and where in the draft to take them. The NBA Draft is crucial for teams to build their organization, however there is limited proof that the measurements taken during the Combine translate to successful performance during the NBA season. Practical Applications Help team front offices decide who to draft, and how drafted players may perform as rookies, based off of 2015 NBA Combine measureables. Data suggests that the measures recorded are not as predictive of performance as believed.


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