Progressive statistics for studies in sports medicine and exercise science.

By W. Hopkins, S. Marshall, A. Batterham, J. Hanin. Medicine & Science in Sports & Exercise, 2009

8,614 citations recorded by the source corpus.

Subfields: Orthopedics and Sports Medicine, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/0a66086a2f23ef968f65395f88cdb2f4d458923a

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In Orthopedics and Sports Medicine

In Statistics and Probability

Citations in the corpus

Running economy: measurement, norms, and determining factors (2015, background): “The SWC, calculated as a proportion of the effect size, represents the magnitude of improvement in a variable as a function of the betweenathlete standard deviation of the particular cohort [66,67].”
High-Intensity Interval Training, Solutions to the Programming Puzzle (2013, neutral): “2 and [2 are considered small, medium-large and very-large effects, respectively [30].”
Training load monitoring in elite English soccer: a comparison of practices and perceptions between coaches and practitioners (2018, methodology): “To obtain a magnitude based inference (Hopkins et al. 2009) for the between-group differences, a proportion ratio was calculated and assessed against the following magnitude scale: 1.”
Monitoring training status with HR measures: do all roads lead to Rome? (2014, background): “…to practitioners is whether the training-related change in HR measures could be important, i.e., whether their magnitude is actually greater than the smallest practical or meaningful change/effect (the so-called smallest worthwhile change, SWC) (Batterham and Hopkins, 2006; Hopkins et al., 2009).”
Comparing external total load, acceleration and deceleration outputs in elite basketball players across positions during match play (2018, background): “Quantitative chances of higher or lower changes were evaluated qualitatively as follows: <1%, almost certainly not; 1-5%, very unlikely; 5-25%, unlikely; 25-75%, possible; 75-95%, likely; 95-99%, very likely; >99%, almost certain (Hopkins et al., 2009).”
Effectiveness of High-Intensity Interval Training (HIT) and Continuous Endurance Training for VO2max Improvements: A Systematic Review and Meta-Analysis of Controlled Trials (2015, methodology): “2 standard deviations (SDs), respectively [24] and derived by averaging appropriate between-subject variances for baseline VO2max.”
High-Intensity Interval Training, Solutions to the Programming Puzzle (2013, neutral): “2 and[2 are considered ‘small’, ‘medium’, ‘large’ and ‘very large’ effects, respectively [42].”
Effects of manipulations of player numbers vs. field dimensions on inter-individual coordination during small-sided games in youth football (2015, neutral): “5 Data analysis The effective relative space per player, radius of free movement, spatial distribution variability and numerical relations were analysed for practical significance using magnitude-based inferences (Buchheit and Mendez-Villanueva, 2014 ; Hopkins et al., 2009).”
Strength and Hypertrophy Adaptations Between Low- vs. High-Load Resistance Training: A Systematic Review and Meta-analysis (2017, background): “08) indicates a likely benefit in favor of heavier loading, albeit of a relatively small magnitude (23).”
Identifying keys to win in the Chinese professional soccer league (2016, methodology): “The two-SD increase stands for the change in a variable from a typical low value (-SD) to a typical high value (+SD) (Hopkins et al., 2009; Higham et al., 2014; Liu et al., 2015a; 2016).”