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
Link To Document :
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