Abstract
A number of authors have noted the increasing use of policies that emphasise accountability and measurable progress in sport. One component of these policies that has received less attention is the use of metrics, despite their increasing use owing to the proliferation of new technologies generating ever more data. In this chapter, we examine three cases to engage how the assessment and valuation of individual athletes is reduced to numeric values. First, we note the way that certain measures have become fixed illustrations that instantly indicate a strong performance, such as running the 100 m sprint in under 10 seconds. Second, we examine the case of the perfect 10 in gymnastics and note the struggle to reward gymnasts with the appropriate score using the 10 as a ceiling. Finally, we discuss how in both physical ability testing and the U.S. National Football League ‘combine’ system, the reduction of athletes to numeric values is contested. We analyse these cases through Latour’s concept of the immutable mobile and Deleuze and Guattari’s concept of territorialisation. Our analysis highlights the significance of metrics as potential actors, a notion that has implications beyond sport and for further theorisation of non-human agency.
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Notes
- 1.
William and Manley’s article was published as an Advance Online Publication in 2014 and hence the publication of a critique of the article in 2015.
- 2.
Based on data reported by the International Association of Athletics Federations (www.iaaf.org/records/toplists/sprints/100-metres/men/senior, accessed 29 June 2018).
- 3.
For example, in 2017, the player selected first signed a US$30+ million contract; the 11th selection received approximately half of that. Contract values ranged from 2–7 million through the remaining selections (data from www.sportrac.com/nfl/draft/2017/, accessed 29 June 2018).
- 4.
https://operations.nfl.com/the-players/getting-into-the-game/national-scouting-combine/ (accessed 29 June 2018).
- 5.
https://thebiglead.com/2018/03/02/orlando-brown-nfl-combine-performance-40-bench-vertical/ (accessed 29 June 2018).
- 6.
https://thebiglead.com/2018/03/06/2018-nfl-combine-draft-winners-losers/ (accessed 29 June 2018).
References
Anshel, M., & Lidor, R. (2012). Talent detection programs in sport: The questionable use of psychological measures. Journal of Sport Behavior, 35, 239.
Baerg, A. (2013). Sport, analytics, and the number as a communication medium. In P. Pedersen (Ed.), The Routledge handbook of sport communication (pp. 75–83). London: Routledge.
Baerg, A. (2017). Big data, sport, and the digital divide: Theorizing how athletes might respond to big data monitoring. Journal of Sport and Social Issues, 41(1), 3–20.
Christensen, M. K. (2009). An eye for talent: Talent identification and the ‘practical sense’ of top-level soccer coaches. Sociology of Sport Journal, 26(3), 365–382.
Colás, Y. (2017). The culture of moving dots: Toward a history of counting and of what counts in basketball. The Journal of Sport History, 44(2), 336–349.
Collins, D., & Bailey, R. (2013). ‘Scienciness’ and the allure of second-hand strategy in talent identification and development. International Journal of Sport Policy and Politics, 5(2), 183–191.
Collins, D., & Cruickshank, A. (2017). Psychometrics in sport: The good, the bad and the ugly. In Psychometric testing: Critical perspectives (pp. 145–156). Hoboken, NJ: John Wiley & Sons, Ltd.
Collins, D., Carson, H. J., & Cruickshank, A. (2015). Blaming Bill Gates AGAIN! Misuse, overuse and misunderstanding of performance data in sport. Sport, Education and Society, 20(8), 1088–1099.
Cooren, F., Matte, F., Taylor, J., & Vasquez, C. (2007). A humanitarian organization in action: Organizational discourse as an immutable mobile. Discourse & Communication, 1(2), 153–190.
Deleuze, G. (1992). Postscript on the societies of control. October, 59, 3–7.
Deleuze, G., & Guattari, F. (1987). A thousand plateaus: Capitalism and schizophrenia. London: Athlone Press.
Denison, J., & Mills, J. (2014). Planning for distance running: Coaching with Foucault. Sports Coaching Review, 3(1), 1–16.
Eldridge, L. (1988, October 4). Too many ‘perfect’ scores of 10 distort Olympic gymnastics results. Christian Science Monitor. Retrieved June 21, 2018, from https://www.csmonitor.com/1988/1004/prom.html.
Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363.
Finn, J. (2016). Timing and imaging evidence in sport: Objectivity, intervention, and the limits of technology. Journal of Sport and Social Issues, 40(6), 459–476.
Gerrard, B. (2017). Analytics, technology and high performance sport. In N. Schulenkorf & S. Frawley (Eds.), Critical issues in global sport management. London: Routledge.
Grix, J., & Carmichael, F. (2012). Why do governments invest in elite sport? A polemic. International Journal of Sport Policy and Politics, 4(1), 73–90.
Guttmann, A. (1978). From ritual to record. New York: Columbia University Press.
Hutchins, B. (2016). Tales of the digital sublime: Tracing the relationship between big data and professional sport. Convergence I, 22(5), 494–509.
Kerr, R. (2006). The impact of Nadia Comaneci on the sport of women’s artistic gymnastics. Sporting Traditions I, 23(1), 87–102.
Kerr, R. (2018). The role of science in the practice of talent identification: A case study from gymnastics in New Zealand. Sport in Society, 22(9), 1–15.
Kerr, R., & Obel, C. (2015). The disappearance of the perfect 10: Evaluating rule changes in women’s artistic gymnastics. The International Journal of the History of Sport I, 32(2), 318–331.
Konoval, T. S. (2018). Moving on to practice: Exploring the impact of a Foucauldian-informed coach development collaboration. PhD thesis, Faculty of Kinesiology, Sport, and Recreation, University of Alberta.
Kuhn, T. (1961). The function of measurement in modern physical science. Isis, 52(2), 161–193.
Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Cambridge, MA: Harvard University Press.
Latour, B. (1990). Drawing things together. In M. Lynch & S. Woolgar (Eds.), Representation in scientific practice (pp. 19–68). Cambridge, MA: MIT Press.
Law, J., & Mol, A. (2001). Situating technoscience: An inquiry into spatialities. Society and Space, 19, 609–621.
Lidor, R., Côté, J., & Hackfort, D. (2009). ISSP position stand: To test or not to test? The use of physical skill tests in talent detection and in early phases of sport development. International Journal of Sport and Exercise Psychology, 7(2), 131–146.
Lyons, B. D., Hoffman, B. J., Michel, J. W., & Williams, K. J. (2011). On the predictive efficiency of past performance and physical ability: The case of the National Football League. Human Performance, 24(2), 158–172.
Macris, L. I., & Sam, M. P. (2014). Belief, doubt, and legitimacy in a performance system: National sport organization perspectives. Journal of Sport Management, 28(5), 529–550.
Majumdar, A. S., & Robergs, R. A. (2011). The science of speed: Determinants of performance in the 100m sprint. International Journal of Sports Science & Coaching, 6(3), 479–493.
Malina, R. M., Bouchard, C., & Bar-Or, O. (2004). Growth, maturation, and physical activity (2nd ed.). Champaign, IL: Human Kinetics.
Mari, L. (2003). Epistemology of measurement. Measurement, 34, 17–30.
Miller, P. K., Cronin, C., & Baker, G. (2015). Nurture, nature and some very dubious social skills: An interpretative phenomenological analysis of talent identification practices in elite English youth soccer. Qualitative Research in Sport, Exercise and Health, 7(5), 642–662.
Millington, B., & Millington, R. (2015). ‘The datafication of everything’: Toward a sociology of sport and Big Data. Sociology of Sport Journal, 32(2), 140–160.
Muller, J. (2018). The tyranny of metrics. Princeton, NJ: Princeton University Press.
Pain, M. T. G., & Hibbs, A. (2007). Sprint starts and the minimum auditory reaction time. Journal of Sports Sciences, 25(1), 79–86.
Porter, T. (1994). Making things quantitative. Science in Context, 7(3), 389–407.
Power, M. (2004). Counting, control and calculation: Reflections on measuring and management. Human Relations, 57(6), 765–783.
Rossi, G. B. (2007). Measurability. Measurement, 40, 545–562.
Sam, M. P., & Macris, L. I. (2014). Performance regimes in sport policy: Exploring consequences, vulnerabilities and politics. International Journal of Sport Policy and Politics, 6(3), 513–532.
Simperingham, K. D., Cronin, J. B., & Ross, A. (2016). Advances in sprint acceleration profiling for field-based team-sport athletes: Utility, reliability, validity and limitations. Sports Medicine, 46(11), 1619–1645.
Slawinski, J., Dumas, R., Cheze, L., Ontanon, G., Miller, C., & Mazure-Bonnefoy, A. (2012). 3D kinematic of bunched, medium and elongated sprint start. International Journal of Sports Medicine, 33(7), 555–560.
Williams, S., & Manley, A. (2016). Elite coaching and the technocratic engineer: Thanking the boys at Microsoft! Sport, Education and Society, 21, 828–850.
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Kerr, R., Rosin, C., Cooper, M. (2020). The Agency of Numbers: The Role of Metrics in Influencing the Valuation of Athletes. In: Sterling, J., McDonald, M. (eds) Sports, Society, and Technology. Palgrave Macmillan, Singapore. https://doi.org/10.1007/978-981-32-9127-0_5
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