Accuracy in predicting repetitions to task failure in resistance exercise: a scoping review and exploratory meta-analysis.
Open accessAbstract
Background Prescribing repetitions relative to task failure is an emerging approach to resistance training. Under this approach, participants terminate the set based on their prediction of the remaining repetitions left to task failure. While this approach holds promise, an important step in its development is to determine how accurate participants are in their predictions. That is, what is the difference between the predicted and actual number of repetitions remaining to task failure, which ideally should be as small as possible.Objective The aim of this study was to examine the accuracy in predicting repetitions to task failure in resistance exercises.Design Scoping review and exploratory meta-analysis.Search and inclusion A systematic literature search was conducted in January 2021 using the PubMed, SPORTDiscus, and Google Scholar databases. Inclusion criteria included studies with healthy participants who predicted the number of repetitions they can complete to task failure in various resistance exercises, before or during an ongoing set, which was performed to task failure. Sixteen publications were eligible for inclusion, of which 13 publications covering 12 studies, with a total of 414 participants, were included in our meta-analysis.Results The main multilevel meta-analysis model including all effects sizes (262 across 12 clusters) revealed that participants tended to underpredict the number of repetitions to task failure by 0.95 repetitions (95% confidence interval [CI] 0.17-1.73), but with considerable heterogeneity (Q(261) = 3060, p < 0.0001, I 2 = 97.9%). Meta-regressions showed that prediction accuracy slightly improved when the predictions were made closer to set failure (β = - 0.025, 95% CI - 0.05 to 0.0014) and when the number of repetitions performed to task failure was lower (≤ 12 repetitions: β = 0.06, 95% CI 0.04-0.09; > 12 repetitions: β = 0.47, 95% CI 0.44-0.49). Set number trivially influenced prediction accuracy with slightly increased accuracy in later sets (β = - 0.07 repetitions, 95% CI - 0.14 to - 0.005). In contrast, participants' training status did not seem to influence prediction accuracy (β = - 0.006 repetitions, 95% CI - 0.02 to 0.007) and neither did the implementation of upper or lower body exercises (upper body - lower body = - 0.58 repetitions; 95% CI - 2.32 to 1.16). Furthermore, there was minimal between-participant variation in predictive accuracy (standard deviation 1.45 repetitions, 95% CI 0.99-2.12).Conclusions Participants were imperfect in their ability to predict proximity to task failure independent of their training background. It remains to be determined whether the observed degree of inaccuracy should be considered acceptable. Despite this, prediction accuracies can be improved if they are provided closer to task failure, when using heavier loads, or in later sets. To reduce the heterogeneity between studies, future studies should include a clear and detailed account of how task failure was explained to participants and how it was confirmed.
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There is insufficient evidence to quantify exact RIR and perceived exertion targets.
“While training to failure is not obligatory for optimizing results, there is insufficient evidence to quantify exact RIR and perceived exertion targets (189,190,197,198).”
From American College of Sports Medicine Position Stand. Resistance Training Prescription for Muscle Function, Hypertrophy, and Physical Performance in Healthy Adults: An Overview of Reviews (2026) · cites this paper as [197]
The Key Points section says the prediction accuracy needed for effective RIR use remains undetermined, and the Discussion calls for studies comparing different RIR endpoints. This supports uncertainty about exact RIR targets, but the paper does not establish whether evidence is sufficient to quantify perceived-exertion targets. Page numbers are unavailable in our copy. (LLM, conf=0.82)
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References 66 · Cited by 76
Research works printed but not linked: 4
- Hoeger WW, Barette SL, Hale DF, Hopkins DR. Relationship between repetitions and selected percentages of one repetition maximum. J Strength Cond Res. 1987;1(1):11-3.
- Sousa CA. Assessment of accuracy of intra-set rating of perceived exertion in the squat, bench press, and deadlift [Master's thesis]. Boca Raton: Florida Atlantic University; 2018.
- Servais B. Regulating resistance exercise intensity using percep- tual response and the "anticipatory feedback" model [Master's thesis]. Arcata: Humboldt State University; 2015.
- Grgic J, Schoenfeld BJ, Orazem J, Sabol F. Effects of resistance training performed to repetition failure or non-failure on muscular strength and hypertrophy: a systematic review and meta-analysis. J Sport Health Sci. 2021. https:// doi. org/ 10. 1016/j. jshs. 2021. 01. 007. · DOI · Paper page
- Authors
- Halperin, I., Malleron, T., Har-Nir, I., Androulakis-Korakakis, P., Wolf, M., Fisher, J., & Steele, J.
- Affiliations
- Tel Aviv University (IL)
- Southampton Solent University (GB)
- Corresponding author
- Halperin, Israel
- Venue
- Sports Medicine
- Published
- 2021-09-20
- Volume
- 52
- Issue
- 2
- Pages
- 377-390
- ISSN
- 0112-1642 (ISSN-L)
- 1179-2035
- OpenAlex
- W3201571937
- Cited by
- 76
- References
- 66
- Citations by year
- 2026: 7 · 2025: 16 · 2024: 23 · 2023: 17 · 2022: 10 · 2021: 3
- FWCI
- 2.83
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Sports Medicine (publishedVersion)
- PubMed (publishedVersion)
- Solent University Research Portal (Solent University) (publishedVersion, other-oa)
- SportRxiv (OSF Preprints) (submittedVersion, cc-by)
- SportRxiv (OSF Preprints) (submittedVersion)
- Topics
- Health Sciences › Medicine › Orthopedics and Sports Medicine › Sports Performance and Training
- Health Sciences › Medicine › Complementary and alternative medicine › Cardiovascular and exercise physiology
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Keywords
- resistance training, prediction accuracy, self-prediction, training load prescription, training status, healthy volunteers, meta-regression, training load monitoring, training load variability, training load
- MeSH terms
- Exercise Therapy, Humans, Exercise, Muscle Strength, Resistance Training
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