Can team statistics predict performance in Olympic men's basketball?
Leicht, A., Spinks, W., and Lukins, J. (2005) Can team statistics predict performance in Olympic men's basketball? In: Promoting Innovation Measuring Success: program & abstracts of 2005 Australian Conference of Science and Medicine in Sport, Fifth National Physical Activity Conference and Fourth National Sports Injury Prevention Conference, p. 65. From: 2005 Australian Conference of Science and Medicine in Sport, 13-16 October 2005, Melbourne, VIC, Australia.
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Traditionally, game statistics (eg field goal percentage, rebounds, turnovers, fouls) have been examined to evaluate game performance in basketball. However, little is known about the predictive capabilities of game statistics for performance, particularly for elite international competitions. The purpose of this study was to examine the relationship between game team statistics and performance (ie win/loss or medallist/non-medallist) for basketball during the 2004 Athens Olympic Games. Team statistics for each of the 42 games played in the mens competition were examined with relationships between variables determined by correlations. Significant (p<0.05) differences between medallists and non-medallists, and game winners and losers were determined by independent t-tests. Categorisation of medallist and non-medallists, and winners and loser were determined by Discriminant Function Analysis (DFA). Winners exhibited better team statistics (78% of variables) than losers while medallists exhibited similar statistics to non-medallists for 70% of variables. Moderate correlations (0.50-0.52) were obtained for two point shot percentage and win/loss, defensive rebounds and win/loss, and medallist/non-medallist and number of game wins. Team score was significantly greater for winners compared with losers at the 20 minute mark of the game while there was no significant difference between medallist and non- medallists at any stage of the game. Using game statistics, DFA correctly classified approximately 97% of winners and 76% of medallists. The current results indicate that game team statistics can assist in the prediction of winners at elite international basketball competition however are less effective in predicting Olympic medallists. Factors other than game statistics contribute to Olympic success.
|Item Type:||Conference Item (Presentation)|
|Keywords:||sport, athlete, prediction|
|Date Deposited:||22 Nov 2011 23:29|
|FoR Codes:||11 MEDICAL AND HEALTH SCIENCES > 1106 Human Movement and Sports Science > 110699 Human Movement and Sports Science not elsewhere classified @ 100%|
|SEO Codes:||97 EXPANDING KNOWLEDGE > 970111 Expanding Knowledge in the Medical and Health Sciences @ 100%|