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Analysis of different types of turnovers between winning and losing performances in men’s NCAA basketball

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2020, 25(7), pp.135-142
  • DOI : 10.9708/jksci.2020.25.07.135
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : July 13, 2020
  • Accepted : July 29, 2020
  • Published : July 31, 2020

Doryung Han 1,  Mark Hawkins 2,  Choi, Hyongjun 3

1경기대학교
2University of Wales
3단국대학교

Accredited

ABSTRACT

Basketball is a highly complex sport, analyses offensive and defensive rebounds, free throw percentages, minutes played and an efficiency rating. These statistics can have a large bearing and provide a lot of pressure on players as their every move can be analysed. Performance analysis in sport is a vital way of being able to track a team or individuals performance and more commonly used resource for player and team development. Discovering information such as this proves the importance of these types of analysis as with post competition video analysis a coach can reach a far more accurate analysis of the game leading to the ability to coach and correct the exact requirements of the team instead of their perceptions. A significant difference was found between winning and losing performances for different types of turnovers supporting current research that states that turnovers are not a valid predictor of match outcomes and that there is no specific type of turnover which can predict the outcome of a match as briefly mentioned in Curz and Tavares (1998). Significant differences were found between winning and tied and losing and tied performance for some types of turnovers, however due to the lack of data collected in this area they cannot be considered valid. Further research could also be conducted in other areas relating to performance indicators where there is currently minimal research in some areas such as assisted baskets, stated about the performance indicators in their own study the performance indicators are inadequate for explaining the complexities of the game suggesting that one indicator will not be constant in every game an research into performance analysis areas would be more appropriate.

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