The Study
With Great Power Comes Great Responsibility: Common Errors in Meta-Analyses and Meta-Regressions in Strength & Conditioning Research
This study didn't test any new exercises or treatments — it looked at 20 older research papers and found that many of them made math mistakes. It tells us: 'Hey, these papers got some numbers wrong!' But it doesn't prove those mistakes changed how people train or got hurt — just that the math was messy.
Analysis score
Maximum 100 for a systematic review with meta-analysis.
Where the score came from
Scientists checked 20 popular fitness studies that combined results from many other studies, and found most had math mistakes.
Where does this study sit?
Reviews of RCTs (Meta-analyses)
Max 100Randomized Trials
Max 90Reviews of Cohort Studies
Max 85Cohort Studies
Max 72Reviews of Case-Control Studies
Max 63Case-Control Studies
Max 58Cross-Sectional & Case Series
Max 50Expert Opinion
Max 540 / 100
Quality score
The highest quality evidence. Systematic reviews and meta-analyses that pool randomized controlled trials, giving the most reliable summary of experimental evidence.
Key takeaways
Summary
Based on the study abstract and findings.
- 1Yes — these mistakes made strength gains look way bigger than they really were, which could mislead coaches and athletes.
- 285% had mistakes; 45% used the wrong math to calculate strength gains; 59% of crazy-high results (like 11x improvement) were due to this error.
Score breakdown, methodology, conflicts of interest, evidence analysis & raw study data
Publication
Journal
Sports Medicine (Auckland, N.z.)
Year
2022
Authors
D. Kadlec, Kristin L. Sainani, Sophia Nimphius
Related Content
Claims (6)
A big review found that in most top-rated studies about strength and fitness training, about 85% made at least one common math mistake—like using the wrong numbers to show results or including results that seem way too extreme.
In nearly half of the most popular science reviews on strength and fitness, researchers made a math mistake—they used the wrong number to calculate how strong an exercise or supplement’s effect was. This made the effects look way bigger than they really were, and most of the super huge effects (over 3.0) were just due to this error.
A lot of big studies that combine other studies on strength and fitness didn’t properly handle cases where the same people were measured multiple times or when one study had several groups — this made their results look more precise and important than they really were.
A lot of the most popular fitness studies only looked at how people improved on their own after a workout or supplement, not how they did compared to people who didn’t do anything — which might make those treatments seem way more effective than they really are.
When scientists combine results from lots of fitness studies, sometimes they get really big numbers—bigger than 3.0—and this claim says almost 6 out of 10 of those huge numbers are probably mistakes because they used the wrong math formula.
In fitness research, nearly half of the big summary studies ignored how reliable each individual study was and treated them all the same — even tiny, shaky studies got the same weight as big, solid ones, which can mess up the final conclusion.
Not medical advice. For informational purposes only. Always consult a qualified healthcare professional before making health decisions.