• DocumentCode
    1822250
  • Title

    TeamSkill and the NBA: Applying lessons from virtual worlds to the real-world

  • Author

    DeLong, Colin ; Terveen, Loren ; Srivastava, Jaideep

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Minnesota, Minneapolis, MN, USA
  • fYear
    2013
  • fDate
    25-28 Aug. 2013
  • Firstpage
    156
  • Lastpage
    161
  • Abstract
    In this paper, we build on our previous work by evaluating several approaches for assessing the skill of players and teams on the basis of both individual performance and group cohesion, or “team chemistry”, using game data from the National Basketball Association (NBA). Previously developed for skill assessment in team-based multi-player video games (e.g., Halo 3), we find that group cohesion is a predictive feature in virtual and real-world team-based games, and that methods utilizing such features can often outperform the baseline in both contexts. Additionally, we observe a strong positive correlation between the predictive accuracy of our group cohesion-based approaches and the duration of playing time between a particular configuration of players on a team and their opponents, or “match-up” length.
  • Keywords
    behavioural sciences computing; computer games; sport; virtual reality; NBA; National Basketball Association; TeamSkill; game data; group cohesion; group cohesion-based approaches; match-up length; real-world team-based games; team chemistry; team-based multiplayer video games; virtual worlds; Accuracy; Aggregates; Conferences; Games; Manganese; Market research; Social network services;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
  • Conference_Location
    Niagara Falls, ON
  • Type

    conf

  • Filename
    6785702