Statistical Analysis in Sport & Exercise Science

Recommended Reading

Altman, D. G., & Bland, J. M. (1995). Statistics notes: Absence of evidence is not evidence of absence. Bmj, 311(7003), 485. 

Amrhein, V., Greenland, S., & McShane, B. (2019). Scientists rise up against statistical significance. Nature, 567(7748), 305-307. 

Atkinson, G., & Nevill, A. M. (1998). Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Medicine, 26(4), 217-238.

Bailey, C. (2019). Longitudinal Monitoring of Athletes: Statistical Issues and Best Practices. Journal of Science in Sport and Exercise, 1-11. 

Bishop, C., Shrier, I., & Jordan, M. (2023). Ratio data: Understanding pitfalls and knowing when to standardise. Symmetry, 15(2), 318. 

Brysbaert, M. (2019). How many participants do we have to include in properly powered experiments? A tutorial of power analysis with reference tables. Journal of cognition. 

Conway, B. (2017) Smallest Worthwhile Change - 

Drake, D., Kennedy, R., & Wallace, E. (2018). Familiarization, validity and smallest detectable difference of the isometric squat test in evaluating maximal strength. Journal of sports sciences, 36(18), 2087-2095.

Flanagan, E. P. (2013). The effect size statistic—Applications for the strength and conditioning coach. Strength & Conditioning Journal, 35(5), 37-40. 

Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. European journal of epidemiology, 31(4), 337-350. 

Supplementary Reading

Halsey, L. (2019) The reign of the p-value is over: what alternative analyses could we employ to fill the power vacuum? Biol. Lett. 15: 20190174 

Hanel, P. H., Maio, G. R., & Manstead, A. S. (2018). A new way to look at the data: Similarities between groups of people are large and important. Journal of personality and social psychology. 

Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological Methods, 17(2), 137. 

Lakens, D. (2021). The practical alternative to the p-value is the correctly used p-value. Perspectives on Psychological Science 

Nead, K. T., Wehner, M. R., & Mitra, N. (2018). The use of “trend” statements to describe statistically nonsignificant results in the oncology literature. JAMA Oncology, 4(12), 1778-1779. doi:10.1001/jamaoncol.2018.4524 

Perugini, M., Gallucci, M., & Costantini, G. (2018). A practical primer to power analysis for simple experimental designs. International Review of Social Psychology, 31(1). 

Rafi, Z., & Greenland, S. (2020). Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise. BMC medical research methodology, 20(1), 1-13. 

Sauret, J. (2018) Reliability - 

Spiegelhalter, D. (2019) The Art of Statistics: Learning from Data. Pelican Books

Stark, P. B., & Saltelli, A. (2018). Cargo‐cult statistics and scientific crisis. Significance, 15(4), 40-43. 

Sullivan, G. M., & Feinn, R. (2012). Using effect size—or why the P value is not enough. Journal of graduate medical education, 4(3), 279-282. 

Till, K., Morris, R., Emmonds, S., Jones, B., & Cobley, S. (2018). Enhancing the evaluation and interpretation of fitness testing data within youth athletes. Strength & Conditioning Journal, 40(5), 24-33. doi: 10.1519/SSC.0000000000000414 

Turner, A. (2022). But did my athlete improve!? Assessing performance changes when N= 1. Professional Strength & Conditioning.

Turner, A. N., Jones, B., Stewart, P., Bishop, C., Parmar, N., Chavda, S., & Read, P. (2019). Total score of athleticism: Holistic athlete profiling to enhance decision-making. Strength & Conditioning Journal, 41(6), 91-101. doi: 10.1519/SSC.0000000000000506 

Turner, A., Brazier, J., Bishop, C., Chavda, S., Cree, J., & Read, P. (2015). Data analysis for strength and conditioning coaches: Using excel to analyze reliability, differences, and relationships. Strength & Conditioning Journal, 37(1), 76-83. 

Funder, D. C., & Ozer, D. J. (2019). Evaluating effect size in psychological research: Sense and nonsense. Advances in Methods and Practices in Psychological Science, 2515245919847202. 

Wasserstein, R. L., & Lazar, N. A. (2016). The ASA statement on p-values: context, process, and purpose. The American Statistician, 70(2), 129-133. 

Weissgerber, T. L., Winham, S. J., Heinzen, E. P., Milin-Lazovic, J. S., Garcia-Valencia, O., Bukumiric, Z., ... & Milic, N. M. (2019). Reveal, don’t conceal: transforming data visualization to improve transparency. Circulation, 140(18), 1506-1518.  

Weir, J. P. (2005). Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. The Journal of Strength & Conditioning Research, 19(1), 231-240. DOI: 10.1519/15184.1

Williams, S., Carson, R., & Tóth, K. (2023). Moving beyond P values in The Journal of Physiology: A primer on the value of effect sizes and confidence intervals. The Journal of Physiology 


Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage [google books]

Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: data mining, inference, and prediction, New York: Springer. [full text]

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning: with applications in R. New York: Springer. [full text]

Maxwell, S. E., Delaney, H. D., & Kelley, K. (2017). Designing experiments and analyzing data: A model comparison perspective. Routledge. [preview]

Dienes, Z. (2008). Understanding psychology as a science: An introduction to scientific and statistical inference. Macmillan International Higher Education. 

Further Reading/Resources

Further Resources

Getting Started with SPSS - Free Online OU Course 

FutureLearn - Data to Insight: An Introduction to Data Analysis and Visualisation - Free Online Course

Bayesian Statistics (an introduction) - Free Online OU Course

Excel Tricks for Sports - A YouTube Channel - 

Improving Your Statistical Questions - 

Improving your Statistical Inferences - 

Watch a video

Adam Virgile has a growing collection of videos on the use of MS Excel for Sport & Exercise Science

Anthony Turner has produced some excellent videos to complement some of his publications on the use of statistics in Strength & Conditioning and the full set can be found here. Below are a few choice videos. 

Which Stats Test: A Sage ResearchMethods Resource