Network Competition and Team Chemistry in the NBA

Abstract–We consider a heterogeneous social interaction model where agents interact with peers within their own network but also interact with agents across other (non-peer) networks. To address potential endogeneity in the networks, we assume that each network has a central planner who makes strategic network decisions based on observable and unobservable characteristics of the peers in her charge. The model forms a simultaneous equation system that can be estimated by quasi-maximum likelihood. We apply a restricted version of our model to data on National Basketball Association games, where agents are players, networks are individual teams organized by coaches, and competition is head-to-head. That is, at any time a player only interacts with two networks: their team and the opposing team. We find significant positive within-team peer-effects and both negative and positive opposing-team competitor-effects in NBA games. The former are interpretable as “team chemistries” which enhance the individual performances of players on the same team. The latter are interpretable as “team rivalries,” which can either enhance or diminish the individual performance of opposing players.

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PID https://www.doi.org/10.6084/m9.figshare.12849749
PID https://www.doi.org/10.6084/m9.figshare.12849749.v1
PID https://www.doi.org/10.1080/07350015.2020.1773273
URL http://dx.doi.org/10.1080/07350015.2020.1773273
URL https://www.tandfonline.com/doi/pdf/10.1080/07350015.2020.1773273
URL https://experts.syr.edu/en/publications/network-competition-and-team-chemistry-in-the-nba
URL https://academic.microsoft.com/#/detail/3009805122
URL https://ideas.repec.org/p/max/cprwps/226.html
URL https://amstat.tandfonline.com/doi/full/10.1080/07350015.2020.1773273
URL http://dx.doi.org/10.6084/m9.figshare.12849749
URL https://www.tandfonline.com/doi/full/10.1080/07350015.2020.1773273
URL http://dx.doi.org/10.6084/m9.figshare.12849749.v1
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Author Horrace, William C.
Author Hyunseok Jung
Author Sanders, Shane
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Collected From Datacite; figshare; Crossref; Microsoft Academic Graph
Hosted By Journal of Business and Economic Statistics; figshare
Publication Date 2020-01-01
Publisher Taylor & Francis
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Language UNKNOWN
Resource Type Other literature type; Article
keyword FOS: Sociology
keyword keywords.Statistics, Probability and Uncertainty
keyword FOS: Biological sciences
keyword FOS: Mathematics
system:type publication
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Source https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::f6fcf2d8a889d2ae9cbd9b2a7c0d627b
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Last Updated 22 December 2020, 23:56 (CET)
Created 22 December 2020, 23:56 (CET)