Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Prior shared success predicts victory in team competitions

An Author Correction to this article was published on 13 March 2019

This article has been updated

Abstract

Debate over the impact of team composition on the outcome of a contest has attracted sports enthusiasts and sports scientists for years. A commonly held belief regarding team success is the superstar effect; that is, including more talent improves the performance of a team1. However, studies of team sports have suggested that previous relations and shared experiences among team members improve the mutual understanding of individual habits, techniques and abilities and therefore enhance team coordination and strategy2,3,4,5,6,7,8,9. We explored the impact of within-team relationships on the outcome of competition between sports teams. Relations among teammates consist of two aspects: qualitative and quantitative. While quantitative aspects measure the number of times two teammates collaborated, qualitative aspects focus on ‘prior shared success’; that is, whether teamwork succeeded or failed. We examined the association between qualitative team interactions and the probability of winning using historical records from professional sports—basketball in the National Basketball Association, football in the English Premier League, cricket in the Indian Premier League and baseball in Major League Baseball—and the multiplayer online battle game Defense of the Ancients 2. Our results show that prior shared success between team members significantly improves the odds of the team winning in all sports beyond the talents of individuals.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Team as an aggregation of players and relationship among players.

Similar content being viewed by others

Data availability

Raw data of NBA, EPL and MLB games are available from the ESPN website. IPL data are available from the Cricinfo website. Derived data used in the study are available at GitHub: https://github.com/smukherjee0305/Skills_Shared_Success_Sports.

Change history

  • 13 March 2019

    In the version of this article initially published, errors occurred in the Acknowledgments.

References

  1. Ready, D. A. & Conger, J. A. Make your company a talent factory. Harvard Business Review https://hbr.org/2007/06/make-your-company-a-talent-factory (2007).

  2. Chudoba, K. & Maznevski, M. Bridging space over time: global virtual team dynamics and effectiveness. Organ. Sci. 11, 473–492 (2000).

    Article  Google Scholar 

  3. Skinner, B. The price of anarchy in basketball. J. Quant. Anal. Sports https://doi.org/10.2202/1559-0410.1217 (2010).

  4. Hackman, J. R. in Handbook of Organizational Behavior (ed. Lorsch, J. W.) 315–342 (Prentice-Hall, Englewood Cliffs, 1987).

  5. Contractor, N. Some assembly required: leveraging Web science to understand and enable team assembly. Phil. Trans R. Soc. A 371, 20120385 (2013).

    Article  Google Scholar 

  6. Duch, J., Waitzman, J. S. & Amaral, L. A. N. Quantifying the performance of individual players in a team activity. PLoS ONE 5, e10937 (2010).

    Article  Google Scholar 

  7. Fewell, J. H., Armbruster, D., Ingraham, J., Petersen, A. & Waters, J. S. Basketball teams as strategic networks. PLoS ONE 7, e47445 (2012).

    Article  CAS  Google Scholar 

  8. Lusher, D., Robins, G. & Kremer, P. The application of social network analysis to team sports. Meas. Phys. Educ. Exerc. Sci. 14, 211–224 (2010).

    Article  Google Scholar 

  9. Arrow, H. & Mcgrath, J. E. Membership matters: how member change and continuity affect small group structure, process, and performance. Small Group Res. 24, 334–361 (1993).

    Article  Google Scholar 

  10. Sibanda, M. Analysts hail teamwork as Germany rule Brazil. CAJ News Africa (14 July 2014).

  11. Swaab, R. I., Schaerer, M., Anicich, E. M., Ronay, R. & Galinsky, A. D. The too-much-talent effect: team interdependence determines when more talent is too much or not enough. Psychol. Sci. 25, 1581–1591 (2014).

    Article  Google Scholar 

  12. Bell, S. T. Deep-level composition variables as predictors of team performance: a meta-analysis. J. Appl. Psychol. 92, 595–615 (2007).

    Article  Google Scholar 

  13. Humphrey, S. E., Morgeson, F. P. & Mannor, M. J. Developing a theory of the strategic core of teams: a role composition model of team performance. J. Appl. Psychol. 94, 48–61 (2009).

    Article  Google Scholar 

  14. Yukelson, D. Principles of effective team building interventions in sport: a direct services approach at Penn State University. J. Appl. Sport Psychol. 9, 73–96 (1997).

    Article  Google Scholar 

  15. Harrison, D. A., Mohammed, S., Mcgrath, J. E., Florey, A. T. & Vanderstoep, S. W. Time matters in team performance: effects of member familiarity, entrainment, and task discontinuity on speed and quality. Pers. Psychol. 56, 633–669 (2003).

    Article  Google Scholar 

  16. Montjoye, Y.-A., de, Stopczynski, A., Shmueli, E., Pentland, A. & Lehmann, S. The strength of the strongest ties in collaborative problem solving. Sci. Rep. 4, 5277 (2014).

    Article  Google Scholar 

  17. Joshi, A. & Roh, H. The role of context in work team diversity research: a meta-analytic review. Acad. Manage. J. 52, 599–627 (2009).

    Article  Google Scholar 

  18. Cummings, J. N. & Kiesler, S. Who collaborates successfully? Prior experience reduces collaboration barriers in distributed interdisciplinary research. In Proc. 2008 ACM Conf. Computer Supported Cooperative Work 437–446 (ACM, 2008).

  19. Goodman, P. S. & Leyden, D. P. Familiarity and group productivity. J. Appl. Psychol. 76, 578–586 (1991).

    Article  Google Scholar 

  20. Gruenfeld, D. H., Mannix, E. A., Williams, K. Y. & Neale, M. A. Group composition and decision making: how member familiarity and information distribution affect process and performance. Organ. Behav. Hum. Decis. Process. 67, 1–15 (1996).

    Article  Google Scholar 

  21. Hinds, P. J., Carley, K. M., Krackhardt, D. & Wholey, D. Choosing work group members: balancing similarity, competence, and familiarity. Organ. Behav. Hum. Decis. Process. 81, 226–251 (2000).

    Article  CAS  Google Scholar 

  22. Cummings, J. N. & Cross, R. Structural properties of work groups and their consequences for performance. Soc. Netw. 25, 197–210 (2003).

    Article  Google Scholar 

  23. Hong, L. & Page, S. E. Groups of diverse problem solvers can outperform groups of high-ability problem solvers. Proc. Natl Acad. Sci. USA 101, 16385–16389 (2004).

    Article  CAS  Google Scholar 

  24. Guimerà, R., Uzzi, B., Spiro, J. & Amaral, L. A. N. Team assembly mechanisms determine collaboration network structure and team performance. Science 308, 697–702 (2005).

    Article  Google Scholar 

  25. Uzzi, B., Mukherjee, S., Stringer, M. & Jones, B. Atypical combinations and scientific impact. Science 342, 468–472 (2013).

    Article  CAS  Google Scholar 

  26. Balkundi, P. & Harrison, D. A. Ties, leaders, and time in teams: strong inference about network structure’s effects on team viability and performance. Acad. Manage. J. 49, 49–68 (2006).

    Article  Google Scholar 

  27. Lungeanu, A., Huang, Y. & Contractor, N. S. Understanding the assembly of interdisciplinary teams and its impact on performance. J. Informetr. 8, 59–70 (2014).

    Article  Google Scholar 

  28. Mukherjee, S. Complex network analysis in cricket: community structure, player’s role and performance index. Adv. Complex Syst. 16, 1350031 (2013).

    Article  Google Scholar 

  29. Clemente, F. M., Martins, F. M. L., Kalamaras, D., Wong, P. D. & Mendes, R. S. General network analysis of national soccer teams in FIFA World Cup 2014. Int. J. Perform. Anal. Sport 15, 80–96 (2015).

    Article  Google Scholar 

  30. Tesluk, P. E. & Jacobs, R. R. Toward an integrated model of work experience. Pers. Psychol. 51, 321–355 (1998).

    Article  Google Scholar 

  31. Dunn, J. R. & Schweitzer, M. E. Feeling and believing: the influence of emotion on trust. J. Pers. Soc. Psychol. 88, 736–748 (2005).

    Article  Google Scholar 

  32. Romero, D. M., Uzzi, B. & Kleinberg, J. Social networks under stress. In Proc. 25th International Conf. World Wide Web 9–20 (International World Wide Web Conferences Steering Committee, 2016).

  33. Scarf, P., Shi, X. & Akhtar, S. On the distribution of runs scored and batting strategy in test cricket. J. R. Stat. Soc. Ser. A Stat. Soc. 174, 471–497 (2011).

    Article  Google Scholar 

  34. Raftery, A. E. Bayesian model selection in social research. Sociol. Methodol. 25, 111–163 (1995).

    Article  Google Scholar 

  35. Silver, N. The Signal and the Noise (Penguin, New York, 2012).

  36. Lewis, M. M. Moneyball: The Art of Winning an Unfair Game (W. W. Norton & Company, New York, 2003).

  37. Liang, D. W., Moreland, R. & Argote, L. Group versus individual training and group performance: the mediating role of transactive memory. Pers. Soc. Psychol. Bull. 21, 384–393 (1995).

    Article  Google Scholar 

  38. Lee, J.-Y., Bachrach, D. G. & Lewis, K. Social network ties, transactive memory, and performance in groups. Organ. Sci. 25, 951–967 (2014).

    Article  Google Scholar 

  39. Bloom, M. The performance effects of pay dispersion on individuals and organizations. Acad. Manage. J. 42, 25–40 (1999).

    Google Scholar 

  40. Halevy, N., Chou, E. Y., Galinsky, A. D. & Murnighan, J. K. When hierarchy wins: evidence from the National Basketball Association. Soc. Psychol. Personal. Sci. 3, 398–406 (2012).

    Article  Google Scholar 

  41. McEwan, D. & Beauchamp, M. R. Teamwork in sport: a theoretical and integrative review. Int. Rev. Sport Exerc. Psychol. 7, 229–250 (2014).

    Article  Google Scholar 

  42. Grund, T. U. The relational value of network experience in teams: evidence from the English Premier League. Am. Behav. Sci. 60, 1260–1280 (2016).

    Article  Google Scholar 

  43. Pobiedina, N., Neidhardt, J., Moreno, M. d C. C., Grad-Gyenge, L. & Werthner, H. On successful team formation: statistical analysis of a multiplayer online game. In 2013 IEEE 15th Conf. Business Informatics 55–62 (IEEE, 2013).

  44. Neter, J., Kutner, M. H., Nachtsheim, C. J. & Wasserman, W. Applied Linear Statistical Models (Irwin, New York, 1990).

Download references

Acknowledgements

This research was funded by grants from the Northwestern University Clinical and Translational Sciences Institute (NUCATS), the Northwestern University Institute for Complex Systems (NICO), the National Institutes of Health (1R01GM112938-01), the US Army Research Laboratory and US Army Research Office Grant W911NF-15-1-0577, the Army Research Laboratory (grant W911NF-09-2-0053), and the Army Research Office (grant W911NF-14-10686). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

S.M. and N.C. designed the research. S.M., Y.H. and J.N. analysed the data. S.M., B.U., N.C., J.N. and Y.H. wrote the paper. All authors approved the final manuscript.

Corresponding author

Correspondence to Satyam Mukherjee.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Tables 1–61, Supplementary Figures 1 and 2, Supplementary Methods

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mukherjee, S., Huang, Y., Neidhardt, J. et al. Prior shared success predicts victory in team competitions. Nat Hum Behav 3, 74–81 (2019). https://doi.org/10.1038/s41562-018-0460-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-018-0460-y

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing