Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 64

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Why We Must Stop Assuming and Estimating Menstrual Cycle Phases in Laboratory and Field-Based Sport Related Research

Elliott-Sale, Kirsty Jayne, Altini, Marco, Doyle-Baker, Patricia, Ferrer, Eva, Flood, Tessa Rose, Harris, Rachel, Impellizzeri, Franco Milko, de Jonge, Xanne Janse, Kryger, Katrine Okholm, Lewin, Gary, Lebrun, Constance M., McCall, Alan, Nimphius, Sophia, Phillips, Stuart M., Swinton, Paul A., Taylor, Madison, Verhagen, Evert, Burden, Richard James·2025·Sports Medicine

Abstract

The increased growth, popularity, and media interest in women’s sport has led to calls for greater prioritisation of female-specific research and innovation. In response, science and medicine researchers have increased the volume of sport-related studies investigating female-specific matters, such as the menstrual cycle. Whilst the accelerated rate of published studies with female participants is welcome, the emerging trend of using assumed or estimated menstrual cycle phases to characterise ovarian hormone profiles is a significant concern. Replacing direct measurements of key characteristics of the menstrual cycle (e.g. the surge in luteinising hormone prior to ovulation via urine detection and sufficient luteal phase progesterone via blood or saliva sampling) with assumptions or estimates (i.e. no measurements) is proposed to be a pragmatic and convenient way of generating data, particularly in field-based research (i.e. elite athlete environments), where time, resources, and athlete availability are sometimes constrained. Using assumed or estimated phases, however, amounts to guessing the occurrence and timing of ovarian hormone fluctuations and risks potentially significant implications for female athlete health, training, performance, injury, etc., as well as resource deployment. The positive intentions of researchers and scientific journals in this space are not in question. The aim of this Current Opinion is to explain why using assumed or estimated menstrual cycle phases is an approach that has little scientific basis and lacks the rigour and appropriate methodological quality to produce valid and reliable data. In doing so, we provide evidence-based responses to common speculation points and offer recommendations for future research.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s40279-025-02189-3

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 5 references

Research works printed but not linked: 32

  1. Campa F, Levi Micheli M, Pompignoli M, Cannataro R, Gulisano M, Toselli S, Greco G, Coratella G. The influence of menstrual cycle on bioimpedance vector patterns, performance, and flexibility in elite soccer players. Int J Sports Physiol Perform. 2022;17(1):58–66. https://doi.org/10.1123/ijspp.2021-0135. · DOI
  2. Carmichael MA, Thomson RL, Moran LJ, Dunstan JR, Nelson MJ, Mathai ML, Wycherley TP. A pilot study on the impact of menstrual cycle phase on elite Australian football athletes. Int J Environ Res Public Health. 2021;18(18):9591. https://doi.org/10.3390/ijerph18189591. · DOI
  3. Julian R, Skorski S, Hecksteden A, Pfeifer C, Bradley PS, Schulze E, Meyer T. Menstrual cycle phase and elite female soccer match-play: influence on various physical performance outputs. Sci Med Footb. 2021;5(2):97–104. https://doi.org/10.1080/24733938.2020.1802057. · DOI
  4. Martin D, Timmins K, Cowie C, Alty J, Mehta R, Tang A, Varley I. Injury incidence across the menstrual cycle in international footballers. Front Sports Act Living. 2021;3: 616999. https://doi.org/10.3389/fspor.2021.616999. (Erratum in: Front Sports Act Living. 2021;3:745792. 10.3389/fspor.2021.745792). · DOI
  5. Igonin PH, Rogowski I, Boisseau N, Martin C. Impact of the menstrual cycle phases on the movement patterns of sub-elite women soccer players during competitive matches. Int J Environ Res Public Health. 2022;19(8):4465. https://doi.org/10.3390/ijerph19084465. · DOI
  6. Dupuit M, Meignié A, Chassard T, Blanquet L, LeHeran J, Delaunay T, Bernardeau E, Toussaint JF, Duclos M, Antero J. On-field methodological approach to monitor the menstrual cycle and hormonal phases in elite female athletes. Int J Sports Physiol Perform. 2023;18(10):1169–78. https://doi.org/10.1123/ijspp.2022-0287. · DOI
  7. Gasperi L, Sansone P, Gómez-Ruano MÁ, Lukonaitienė I, Conte D. Female basketball game performance is influenced by menstrual cycle phase, age, perceived demands, and game-related contextual factors. J Sports Sci. 2023. https://doi.org/10.1080/02640414.2023.2285119. · DOI
  8. Abbott W, Exall Z, Walsh L, Clifford T. Menstrual cycle and situational match variables: effects on well-being in professional female soccer players. Res Q Exerc Sport. 2024. https://doi.org/10.1080/02701367.2023.2298443. · DOI
  9. Barlow A, Blodgett JM, Williams S, Pedlar CR, Bruinvels G. Injury incidence, severity, and type across the menstrual cycle in female footballers: a prospective three season cohort study. Med Sci Sports Exerc. 2024;56(6):1151–8. https://doi.org/10.1249/MSS.0000000000003391. · DOI
  10. Carlin H, Dupuit M, Storme F, Chassard T, Meignié A, Sachet I, Brunet E, Toussaint JF, Antero J. Impact of menstrual cycle or combined oral contraception on elite female cyclists’ training responses through a clustering analysis of training sessions. Front Sports Act Living. 2024;6:1307436. https://doi.org/10.3389/fspor.2024.1307436. · DOI
  11. Jones BP, L’Heveder A, Bishop C, Kasaven L, Saso S, Davies S, Chakraverty R, Brown J, Pollock N. Menstrual cycles and the impact upon performance in elite British track and field athletes: a longitudinal study. Front Sports Act Living. 2024;6:1296189. https://doi.org/10.3389/fspor.2024.1296189. · DOI
  12. Juillard E, Douchet T, Paizis C, Babault N. Impact of the menstrual cycle on physical performance and subjective ratings in elite academy women soccer players. Sports (Basel). 2024;12(1):16. https://doi.org/10.3390/sports12010016. · DOI
  13. Ronca F, Blodgett JM, Bruinvels G, Lowery M, Raviraj M, Sandhar G, Symeonides N, Jones C, Loosemore M, Burgess PW. Attentional, anticipatory and spatial cognition fluctuate throughout the menstrual cycle: Potential implications for female sport. Neuropsychologia. 2024;206:108909. https://doi.org/10.1016/j.neuropsychologia.2024.108909. · DOI
  14. Scott D, Bruinvels G, Norris D, Lovell R. The dose–response in elite soccer: preliminary insights from menstrual-cycle tracking during the FIFA women’s world cup 2019. Int J Sports Physiol Perform. 2024;19(4):331–9. https://doi.org/10.1123/ijspp.2022-0282. · DOI
  15. Burden RJ, Altini M, Ferrer E, Flood TR, Lewin G, Nimphius S, Phillips SM, Elliott-Sale KJ. Measure do not guess: a call to action to end assumed and estimated menstrual cycle phases in research. BMJ Open Sport Exerc Med. 2024;10(2): e002095. https://doi.org/10.1136/bmjsem-2024-002095. · DOI
  16. Allaway HC, Southmayd EA, De Souza MJ. The physiology of functional hypothalamic amenorrhea associated with energy deficiency in exercising women and in women with anorexia nervosa. Horm Mol Biol Clin Investig. 2016;25(2):91–119. https://doi.org/10.1515/hmbci-2015-0053. · DOI · Paper page
  17. De Souza MJ, Toombs RJ, Scheid JL, O’Donnell E, West SL, Williams NI. High prevalence of subtle and severe menstrual disturbances in exercising women: confirmation using daily hormone measures. Hum Reprod. 2010;25(2):491–503. https://doi.org/10.1093/humrep/dep411. · DOI · Paper page
  18. Lewis-Beck M, Bryman A, Futing LT, editors. The SAGE encyclopaedia of social science research methods. USA: Sage Publishing; 2004.
  19. Stylianides GJ, Stylianides AJ. Promoting elements of mathematical knowledge for teaching related to the notion of assumptions. Math Think Learn. 2003;26:382–410. https://doi.org/10.1080/10986065.2023.2172617. · DOI
  20. Muthén BO. Latent variable modelling in epidemiology. Alcohol Res Health. 1992;16(4):286.
  21. Briggs DC. Historical and conceptual foundations of measurement in the human sciences: credos and controversies. 1st ed. New York: Routledge; 2021. · DOI
  22. Kloprogge P, Van der Sluijs JP, Petersen AC. A method for the analysis of assumptions in model-based environmental assessments. Environ Model Softw. 2011;26(3):289–301. · DOI
  23. https://dictionary.cambridge.org/
  24. Colenso-Semple LM, D’Souza AC, Elliott-Sale KJ, Phillips SM. Current evidence shows no influence of women’s menstrual cycle phase on acute strength performance or adaptations to resistance exercise training. Front Sports Act Living. 2023;5(1–9):1054542. https://doi.org/10.3389/fspor.2023.1054542. · DOI
  25. Taylor MY, Osborne JO, Topranin VM, Engseth TP, Solli GS, Valsdottir D, Andersson E, Øistuen GF, Flatby I, Welde B, Morseth B, Haugen T, Sandbakk Ø, Noordhof DA. Menstrual cycle phase has no influence on performance-determining variables in endurance-trained athletes: the FENDURA project. Med Sci Sports Exerc. 2024. https://doi.org/10.1249/MSS.0000000000003447. · DOI
  26. Fehring RJ, Schneider M, Raviele K. Variability in the phases of the menstrual cycle. J Obstet Gynecol Neonatal Nurs. 2006;35(3):376–84. https://doi.org/10.1111/j.1552-6909.2006.00051.x. · DOI · Paper page
  27. Prior JC, Naess M, Langhammer A, Forsmo S. Ovulation prevalence in women with spontaneous normal-length menstrual cycles - a population-based cohort from HUNT3, Norway. PLoS ONE. 2015;10(8): e0134473. https://doi.org/10.1371/journal.pone.0134473. · DOI
  28. Alliende ME. Mean versus individual hormonal profiles in the menstrual cycle. Fertil Steril. 2002;78(1):90–5. https://doi.org/10.1016/s0015-0282(02)03167-9. · DOI
  29. D’Souza AC, Wageh M, Williams JS, Colenso-Semple LM, McCarthy DG, McKay AKA, Elliott-Sale KJ, Burke LM, Parise G, MacDonald MJ, Tarnopolsky MA, Phillips SM. Menstrual cycle hormones and oral contraceptives: a multimethod systems physiology-based review of their impact on key aspects of female physiology. J Appl Physiol (1985). 2023;135(6):1284–99. https://doi.org/10.1152/japplphysiol.00346.2023. · DOI
  30. McIntosh JE, Matthews CD, Crocker JM, Broom TJ, Cox LW. Predicting the luteinizing hormone surge: relationship between the duration of the follicular and luteal phases and the length of the human menstrual cycle. Fertil Steril. 1980;34(2):125–30. · DOI
  31. Costello JT, Bieuzen F, Bleakley CM. Where are all the female participants in sports and exercise medicine research? Eur J Sport Sci. 2014;14(8):847–51. https://doi.org/10.1080/17461391.2014.911354. · DOI · Paper page
  32. Cowley ES, Olenick AA, McNulty KL, Ross EZ. “Invisible sportswomen”: the sex data gap in sport and exercise science research. Women Sport Phys Activity J. 2021;29(2):146–51. https://doi.org/10.1123/wspaj.2021-0028. · DOI · Paper page

Cited by

Metadata

Authors
Elliott-Sale, K. J., Altini, M., Doyle-Baker, P., Ferrer, E., Flood, T. R., Harris, R., Impellizzeri, F. M., de Jonge, X. J., Kryger, K. O., Lewin, G., Lebrun, C. M., McCall, A., Nimphius, S., Phillips, S. M., Swinton, P. A., Taylor, M., Verhagen, E., & Burden, R. J.
Venue
Sports Medicine
Published
2025-03-14
Volume
55
Issue
6
Pages
1339-1351
ISSN
  • 0112-1642
  • 1179-2035
Cited by
64
References
5
Language
en
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.