Sport Science 101

Colloquial speak and the literature offer many definitions for “sport science” simply because there is currently no legislation restricting the terms usage or definition. Therefore, many definition’s and usages are allowed and will be used. Here are some options with the first three being colloquially used definition’s and those after being research-based definitions:

Sport Science is the study of sport.

Sport Science is a field.

(“field” – a particular branch of study or sphere of activity or interest)

Sport Science is an industry.

(“industry” – a particular form or branch of economic or commercial activity)

Sport Science can be defined as the study of maximizing competitive athletic performance.

Haff, G. G. (2010). Sport Science. Strength and Conditioning Journal, 32(2), 33-45. doi:10.1519/SSC.0b013e3181d59c74

Sport Science is concerned with the enhancement of sports performance through the application of scientific methods and principles.

Stone, M. H., Sands, W. A., & Stone, M. E. (2004). The Downfall of Sports Science in the United States. Strength and Conditioning Journal, 26(2), 72-75.

Sport Science is a multi-disciplinary field concerned with the understanding and enhancement of human sporting performance. Sport science can be thought of as a scientific process used to guide the practice of sport with the ultimate aim of improving sporting performance.

Bishop D. An applied research model for the sport sciences. Sports Med. 2008;38(3):253-63. Review. PubMed PMID: 18278985.

Sport Science is a discipline of science that is related to the improvement of sports performance and may range from applied sport science to basic sport science.

Haff, G. G. (2010). Sport Science. Strength and Conditioning Journal, 32(2), 33-45. doi:10.1519/SSC.0b013e3181d59c74

PHYSICAL training focuses on speed, agility, strength, explosiveness, flexibility, sport-specific conditioning, etc. Physical training is what you do at PRECISION’s facility. SKILL training focuses on ball dribbling, stick handling, offensive/defensive tactics, plays, etc. Skill training is what you do with your sport coach at practice/games. Physical training and Skills training require different expertise and generally take place in different places at different times – one at the field/court/ice (skill training) and the other at PRECISION’s facility (physical training). Skill training and physical training are also done with different frequencies. The amount of time spent doing each depends on the level of athlete and time of year.

Only quantification and objectification can allow us to begin answering questions like:

“How do I know which physical qualities to train?”
“How do I know when to start and stop different training methods?”
“Is my physical training transferring to my performance in the game/competition?”

At PRECISION, we use progressive statistics and data science methods to help answer these questions as well as others. Training programs, results, and progress need to be objectively tracked, giving the athletes and their financial supporters the ability to trust in results that actually matter.

References:

Mujika I. The alphabet of sport science research starts with Q. Int J Sports Physiol Perform. 2013 Sep;8(5):465-6. PubMed PMID: 24058942.

Borresen J, Lambert MI. The quantification of training load, the training response and the effect on performance. Sports Med. 2009;39(9):779-95. doi: 10.2165/11317780-000000000-00000. Review. PubMed PMID: 19691366.

Davison RC, Williams AM. The use of sports science in preparation for Olympic competition. J Sports Sci. 2009 Nov;27(13):1363-5. doi:10.1080/02640410903448226. PubMed PMID: 20183011.

Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009 Jan;41(1):3-13. doi: 10.1249/MSS.0b013e31818cb278. Review. PubMed PMID: 19092709.

“Specialization” means the athlete only practices and competes in one single sport for most or all of the year and no others. “Early” and “late” do not refer to specific ages but rather the relativity of when an athlete specializes during the human growth years (i.e. childhood vs adolescence). “Early specialization” refers to an athlete choosing to specialize during the childhood years and “late specialization” refers to an athlete choosing to specialize during the adolescent years. Retrospective research studies were done to identify when the current world’s best athletes specialized (earlier or later) in order to make recommendations for up and coming youth athletes. It was found that in most team sports, specializing later maximized sporting outcomes whereas for individual sports specializing earlier maximized the athletes’ sport outcomes.

The reverse is also true: if an athlete plays a team sport (i.e. a “late specialization sport”) yet chooses to specialize early (in childhood) the athlete is LESS likely to maximize their athletic potential long term and are more likely to sustain injury.

References:

Talent Development & Excellence. Oct2013, Vol. 5 Issue 2, p85-100. 16p. 3 Charts. Moesch, Karin; Hauge, Marie-Louise Trier; Wikman, Johan M.; Elbe, Anne-Marie

Malina RM. Early sport specialization: roots, effectiveness, risks. Curr Sports Med Rep. 2010 Nov-Dec;9(6):364-71. doi: 10.1249/JSR.0b013e3181fe3166. PubMed PMID: 21068571.

The developmental model of sport participation: 15 years after its first conceptualization Science & Sports, Volume 29, Issue null, Pages S63-S69 J. Côté, M. Vierimaa

Read PJ, Oliver JL, De Ste Croix MB, Myer GD, Lloyd RS. The scientific foundations and associated injury risks of early soccer specialisation . J Sports Sci. 2016 Apr 27:1-8. [Epub ahead of print] PubMed PMID: 27120711.

Data science is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured. It combines contributions from mathematics, statistics, and computer science that is applied to a range of different domains in business, government, and academia such as sport science. Data scientists can collect, explore, visualize, and analyze data to answer research questions, test hypotheses, and make predictions about sports performance. Examples of data science include data visualizations, predictive algorithms, analyses of massive quantities of data, evaluating the results of training programs for athletes, evaluating the transfer of said results to actual game day performance, and profiling athletes.

References:

Data science. (2016, June 28). In Wikipedia, The Free Encyclopedia. Retrieved 21:52, July 20, 2016, from https://en.wikipedia.org/w/index.php?title=Data_science&oldid=727407111

Dhar, V. (2013). “Data science and prediction”. Communications of the ACM 56 (12): 64. doi:10.1145/2500499.

Jeff Leek (2013-12-12). “The key word in “Data Science” is not Data, it is Science”. Simply Statistics