UEFA consensus statement on menstrual cycle tracking in women’s football

Abstract

Menstrual cycle tracking is increasingly recognised as an important aspect of supporting female athletes. However, its application in football remains inconsistent and under-researched. This consensus statement, initiated by the Union of European Football Associations Medical and Anti-Doping Unit, provides evidence-informed guidance on best practices for menstrual cycle tracking in women’s football. Developed using the RAND-UCLA appropriateness method, the consensus involved a multidisciplinary expert panel that reviewed the literature and reached agreement on 82 statements across five key domains: the rationale for tracking, meaningful metrics, appropriate methods, implementation strategies and methodological considerations for research. The consensus underscores that while current evidence linking menstrual cycle phases to performance or injury risk remains inconclusive, tracking can support athlete well-being by identifying menstrual irregularities, managing symptoms and enhancing player education and autonomy. Practical recommendations are provided for measuring cycle characteristics, ovulation, hormonal profiles and symptoms, whereas ethical and cultural considerations are emphasised. This statement aims to promote standardised, athlete-centred tracking protocols and establish priorities for practice and future research in female football.

Background

The relationship between the menstrual cycle and athletic performance or injury risk has been a subject of ongoing debate. In recent years, tracking the menstrual cycle (ie, monitoring physical and emotional well-being across different menstrual cycle phases) has become a helpful practice for some female athletes, offering valuable insights into training and recovery plans (eg, determining the timing of adverse menstrual cycle symptoms to target specific management strategies). However, despite increasing research interest, the evidence base regarding the physiological effects of the menstrual cycle on performance and injuries remains fragmented and incomplete and perpetuates misconceptions, such as assumptions that all players experience performance dips during the luteal phase or that injury risk universally increases around ovulation, without robust supporting evidence.¹,³ These knowledge gaps and fallacies hinder efforts to optimise performance and implement strategies to protect the well-being of female athletes.

Most stuides have focused on traditional endurance sports (eg, long-distance running, cycling and rowing), often excluding team sports such as football that combine aerobic and anaerobic demands.² Technical precision, tactical decision-making and intermittent high-intensity performance are key components of the women’s gamein football⁴,⁶. Understanding these specific demands in relation to the menstrual cycle would facilitate football-specific training and performance strategies and improve our broader understanding of player health in the women’s game.

To investigate (ie, for research or applied purposes) the effects of fluctuations in oestrogen and progesterone across the menstrual cycle on football performance, injuries and health, the menstrual cycle must be tracked using robust and consistent processes. An informal survey, conducted during the 2022–2023 season, among 12 elite teams across eight countries participating in the Union of European Football Associations (UEFA)’s Women Elite Club Injury Study, highlighted the variability in menstrual cycle tracking protocols. The survey revealed substantial differences in the reasons, methods and approaches employed for menstrual cycle monitoring, emphasising the need for standardisation in this area. The UEFA Medical & Anti-Doping Unit has developed a consensus statement to address these gaps. This initiative aims to provide practical, evidence-informed recommendations for menstrual cycle tracking in football, identify knowledge gaps and establish research priorities for female football players.

Intended audience and scope

This consensus statement is intended for practitioners, researchers and stakeholders supporting female football players across all levels of play. Although the recommendations are relevant to players at any competitive level, they are likely most applicable to elite and high-performance environments, where structured monitoring and individualised support can be more effectively integrated into training and medical practice. As such, this document primarily serves the needs of medical professionals, sports scientists, coaches and performance staff responsible for player health and performance, offering evidence-informed guidance on best practices for menstrual cycle tracking in football. These recommendations apply to players who are naturally menstruating; menstrual patterns in those using hormonal contraception differ and were not the focus of this consensus.

With this consensus, this study emphasises the importance of context-specific and appropriate tracking practices tailored to the resources and goals of each setting. Importantly, we do not propose specific thresholds or cut-off values to function as screening tools or indicators of health concerns. Neither do we provide diagnostic or treatment guidance in the case of abnormal findings. The interpretation of data and any subsequent clinical follow-up remains the responsibility of qualified medical professionals.

To support players in understanding their cycle patterns more effectively, we have developed, based on the recommendations in this consensus, a basic menstrual cycle and symptom diary for personal use (online supplemental 1).

Methods

Consensus development approach

This Menstrual Cycle Tracking (MCT) consensus statement was developed using the RAND-UCLA appropriateness method (RAM).^{7 8} The RAM integrates evidence synthesis with expert judgement to evaluate the appropriateness of healthcare practices.

A core panel of authors was convened based on documented scientific or practical expertise in female athlete health, gynaecological health, female athlete physiology or the menstrual cycle in athletes. The panel was deliberately composed to represent various genders, geographic regions, disciplines and career stages to ensure diversity. It included five sports medicine physicians, five sports scientists, of whom two had extensive qualitative research experience, four physiotherapists, one endocrinologist and one gynaecologist. Panellists were based in Europe, North America, South America and Oceania, ensuring broad geographic representation.

Each panel member was assigned to a working group that addressed one of the key questions underpinning this consensus. Panel members were assigned to working groups based on their subject matter expertise and professional background to ensure balanced input. To ensure a comprehensive approach, two panellists, one with research expertise and the other with practical expertise, co-chaired each group.

Guiding questions

The consensus addressed the following five guiding questions:

1. Why: what evidence exists about the relationship between the menstrual cycle and player performance and health?

2. What: which menstrual cycle measures are used to track player performance and health?

3. How: what methods are valid, reliable and practical for tracking the menstrual cycle in players?

4. Use: what are the best practices for disseminating and implementing menstrual cycle tracking in football?

5. Study: what research and statistical methods are relevant for menstrual cycle analyses, considering intra- and inter-variability among players?

Working groups prepared referenced summaries of the existing literature to synthesise current knowledge and identify gaps. Evidence was sourced from various sports and contextualised for relevance to football. Evidence statements were drafted from these summaries by the co-chairs of each group, for confidential online voting using a modified Delphi method.

Consensus process

Before the in-person meeting, statements were distributed for confidential electronic voting to all core panel members. Five additional voting members, consisting of clinicians and researchers not involved in drafting, were invited to ensure external validation and reduce bias during the voting phase. Voting responses were scored on a 5-point scale, ranging from ‘strongly disagree’ to ‘strongly agree’. Consensus thresholds were defined as follows:

• Agreement: ≥80% agreement without any dissent.

• Minority disagreement: ≥80% agreement with one or more dissenting votes.

• Disagreement: <80% agreement.

The panel discussed the results of the first round of voting during an in-person meeting at UEFA Headquarters in Nyon, Switzerland (February 2024). Statements that failed to meet consensus thresholds were revised and subjected to a second round of electronic voting. Minority opinions were documented where applicable.

Post-meeting procedures

Outcomes from the voting rounds and meetings were synthesised, with final recommendations and their supporting evidence included in this consensus statement. All panel members were given the opportunity to share a dissenting opinion on these final recommendations, but none did. Full details of voting statements, outcomes and decisions are available in onlinesupplemental 24.

Voting results

During the first round of online voting, 85 evidence statements were presented to the expert panel. Of these, 44 statements achieved agreement. The actions taken after in-person discussions to address the remaining statements are detailed in table 1.

Table 1. Results of the online Delphi survey and subsequent actions taken.

	Total	Agreement*	Minority disagreement†	Disagreement‡
Round 1 voting	85	44	19	22
Action taken
No action	37	32	5	–
Removed	20	2	3	15
Reworded with revote	10	–	5	5
Reworded without revote	16	10	6	–
Revote	2	–	–	2
Added	17
Round 2 voting	29	18	11	–
Action taken
No action	13	11	2	–
Removed	–	–	–	–
Reworded with revote	–	–	–	–
Reworded without revote	16	7	9	–

^*Agreement: ≥80% agree without disagreement but potentially includes ‘undecided’ votes.

^†Minority disagreement: ≥80% agree but with one or more disagreeing opinions.

^‡Disagreement: <80% agreement.

In the second round of voting, 29 statements were presented to the panel. This included 12 previously presented statements that had not achieved consensus in the first round and required a revote, and 17 new statements generated during the in-person discussions.

By the end of the second round, all voting statements had reached agreement or minority disagreement, resulting in 82 agreed-upon statements. Among these, 11 statements still had minority disagreement.

Why track the menstrual cycle in football

Tracking the menstrual cycle in football offers opportunities to address practical and scientific considerations, though it requires a nuanced and evidence-based approach.⁹

Many claims link menstrual cycle phases to players’ performance, injury risk, recovery and health, although such claims often lack robust evidence.^{1 2} For meaningful application, tracking the menstrual cycle must consider the unique demands of football, including team dynamics, frequent matches, training loads, travel and recovery schedules.

Current evidence remains insufficient to confirm or refute significant relationships between menstrual cycle phases and aspects such as injury risk, performance benefits, or recovery and rehabilitation outcomes in football players. Nonetheless, tracking offers value in understanding a player’s typical cycle patterns, distinguishing between normal and abnormal patterns and associated symptoms, particularly related to physical and mental health.¹⁰ This supports players in better understanding their bodies and identifying actionable strategies for symptom management and health optimisation.⁹

A central rationale for tracking is the ability to distinguish between expected variations and potential abnormalities in menstrual patterns. Identifying disruptions, such as missed cycles, irregular bleeding or recurring symptoms, can prompt further evaluation and facilitate early recognition of conditions, such as low energy availability, hormonal imbalances or other health issues with implications for athlete safety and performance.¹¹ Table 2 provides an overview of terminology and operational definitions.

Table 2. Operational terms related to the menstrual cycle (adapted from Elliott-Sale et al¹³ and Oleka et al.¹⁴.

Terminology	Operational definition
Naturally menstruating	Not using hormonal contraception or any other medications known to affect the menstrual cycle
Regularly menstruating	Cycle lengths between 21 and 35 days without any additional cycle-related details
Eumenorrheic cycles	Cycle lengths between 21 and 35 days, with evidence of ovulation and sufficient progesterone
Amenorrhoea	Primary amenorrhoea: failure of onset of menstruation by the age of 15 years Secondary amenorrhoea: absence of menstrual periods for more than three consecutive months in an individual who has had at least one spontaneous menses
AUB-frequent (formerly known as polymenorrhoea)	Menstrual cycle lengths of <21 days
AUB-infrequent (formerly known as oligomenorrhoea)	Menstrual cycle lengths >35 days
Menorrhagia (formerly heavy menstrual bleeding)	Excessive bleeding (>80 mL per cycle) from the uterine corpus that may interfere with the physical, emotional, social and material qualities of life

AUB, abnormal uterine bleeding.

From a science-oriented perspective, menstrual cycle tracking aims to enhance understanding of how cyclical fluctuations in endogenous hormones such as oestrogen and progesterone affect performance, recovery, injury risk and health outcomes.¹² It also supports efforts to identify individual and environmental modifiers, such as psychological stress, nutritional status or training load, that may interact with hormonal patterns. These insights may help differentiate between modifiable and non-modifiable factors, offering a clearer path towards personalised strategies for health and performance optimisation.

Which menstrual cycle measures are meaningful in tracking player performance and health?

A hierarchy of metrics was established to identify meaningful menstrual cycle measures about player performance and health. These include (a) regularity and characteristics of bleeding, (b) type, intensity and frequency of cyclical symptoms, (c) ovulation and (d) ovarian hormone levels. For tracking to be deemed meaningful, data should initially cover at least three consecutive cycles, with subsequent single-cycle assessments employed when needed (eg, if a player’s cycle length changes outside of their normal range or to randomly test that the documented cycle characteristics from the initial assessment are still valid).

Regularity and characteristics of bleeding

Monitoring the regularity, duration and volume of menstrual bleeding gives players insights into their cycle length and patterns without needing ovulation or ovarian hormone assessment. Tracking menstrual cycle length (ie, the time from the first day of bleeding to the start of the next bleed, which should be between 21 and 35 days) can help identify conditions, such as abnormal uterine bleeding (AUB)-frequent (ie, polymenorrhea, <21 days), AUB-infrequent (ie, oligomenorrhea, >35 days) or secondary amenorrhoea (>90 days).¹³ Variations in menstrual cycle length (ie, deviations exceeding 7 days or 1 SD from the player’s individual norm) may indicate menstrual disturbances, low energy availability or stress-related adaptations.¹⁴,¹⁶ Sudden or gradual changes in cycle length can also signify increased physical or psychological stress. Monitoring the duration and volume of blood loss can help identify menorrhagia (ie, heavy menstrual bleeding), which is linked to iron deficiency and fatigue,¹⁷ and anovulatory cycles, which are often characterised by prolonged or heavy menstruation.¹⁸

Type, intensity and duration of cyclical symptoms

Cyclical symptoms (ie, those occurring predictably in specific phases) offer valuable insights when tracking their type, intensity and duration. This tracking allows players to determine if their experiences are typical, develop symptom-management strategies and seek medical advice for recurrent, debilitating symptoms, which may indicate underlying clinical disorders. Common symptoms, such as fatigue, pain, mood fluctuations, appetite changes, breast pain and sleep disturbances, have been described in other sports to influence perceived and actual performance and physical capacities.^{10 19 20} Monitoring these wellness metrics may empower players to anticipate patterns and optimise their training and recovery through effective symptom management strategies.²¹

Ovulation

Ovulation is a marker of ovarian hormone and endocrine health and is critical for ensuring adequate circulating levels of oestrogen and progesterone.²² Monitoring ovulation reflects a player’s reproductive health and is relevant, for instance, for identifying relative energy deficiency in sport.¹¹

Ovarian hormone levels

Ovarian hormone profiling offers a more detailed and specific understanding of a player’s physiological state throughout the menstrual cycle. Blood sampling can confirm hormone levels during specific phases (figure 1). In Phase 4, a threshold of >16 nmol∙l^-1 is typically set for progesterone levels.¹² The pulsatile nature of progesterone might influence this measurement. However, previous studies have indicated that this conservative, single-measurement limit should reduce the risk of including AUB-O (ie, anovulatory) or AUB-E (luteal phase deficient) cycles.²³ Alternatively, daily serum progesterone samples could be obtained during the luteal phase and combined to produce an integrated luteal progesterone value.²⁴ Although this approach is improbable in an applied sports setting, it is not impossible and should be given proper logistical consideration. Such assessments confirm phase-specific hormone levels, indicating a healthy hormonal environment that is supportive to a player’s overall health, performance and recovery in sports.

Figure 1. Menstrual cycle phases and corresponding hormonal profiles. Phase 1 (early follicular): low oestrogen and low progesterone. Phase 2 (late follicular): peak oestrogen with a slight rise in progesterone. Phase 3 (early luteal): oestrogen levels higher than Phase 1 but lower than those in Phases 2 and 4, with moderately increased progesterone. Phase 4 (mid-luteal): oestrogen levels higher than those in Phases 1 and 3 but lower than that in Phase 2, with progesterone level >16 nmol∙L⁻¹.

How to measure the menstrual cycle in football

Various methods are available to track the menstrual cycle and its components, and the chosen approach should balance resources, practicality and the need for standardised protocols. Accurate measurement requires avoiding assumptions about menstrual cycle phases and establishing them along a continuum of four confirmed phases.⁹ In onlinesupplemental 57, we have provided menstrual cycle and symptom diaries for each level of recommendations.

The responsibility for menstrual cycle tracking must be shared between the club and the players to collect accurate and meaningful data. For this reason, it is necessary to assign a suitably qualified professional from the club, such as a sports medicine physician or experienced physiotherapist, to oversee data collection, provide the required materials, instruct players on the monitoring schedule and processes and facilitate sample collection. On the players’ part, they must actively collaborate and accept shared responsibility by taking joint ownership of the required tasks.

When frequent collection of biological samples (eg, blood, urine or saliva) is necessary, note that these samples are obtained from players who have private lives and routines outside of their club. In particular, travelling and sleeping away from home can pose challenges for collecting biological samples. Players must ensure they have the appropriate kits at home or while travelling to collect biological samples or should communicate with the club if biological samples cannot be collected at specific times. When players are collecting biological samples themselves, they should strictly follow the manufacturer’s instructions. Blood samples should only be taken by qualified healthcare professionals, following specified health and safety requirements. Attending appointments on the designated days is critical if imaging is required, as imaging results are often day-dependent.

Determination of bleeding versus non-bleeding days

Tracking the regularity, duration and volume of bleeding over at least three consecutive cycles is essential for meaningful assessment. Self-reporting is encouraged, enabling players to log bleeding and non-bleeding days accurately. This can be accomplished using a calendar, diary or a customised form designed for this purpose. Such tracking allows for a comprehensive understanding of individual cycle patterns and variability. The estimated bleeding volume is typically self-reported by players and best assessed using a pictorial blood assessment chart or a menstrual pictogram.²⁵

Determination of the point of ovulation and hormonal profiles

Depending on the available resources and purposes, identifying ovulation and hormonal profiles should be conducted using minimal, best-practice or gold-standard methodologies. These standards, outlined in table 3, offer practical guidelines for research settings and applications to ensure robust and reliable tracking of ovulatory events, reflecting the combined use of diagnostic methods, including but not limited to one methodology for measurement. Adhering to the gold-standard guidelines is preferred for research purposes, although it may not always be feasible. In such cases, reporting any limitations and their implications is crucial.

Table 3. Recommended standards to determine the point of ovulation and hormonal profiles.

	Determination of the point of ovulation in practice and research	Determination of hormonal profiles in practice	Research approach for naturally menstruating women before testing outcome measures	Research approach for naturally menstruating women when testing outcome measures
Minimum standard	One cycle of: Self-reporting the onset of bleeding (ie, to establish menstrual cycle length≥21 and ≤ 35 days); and Daily LH urine sticks from 3 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge.	One cycle of: self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days); and Daily LH urine sticks from 3 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge; and One saliva sample, for the determination of progesterone (>50 pg/mL), provided +7 (± 1) days after the LH surge has been confirmed.	One cycle of: Self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days); and Daily LH urine sticks from 5 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge; and One blood sample for the determination of progesterone (≥16 nmol∙L-1) provided +7 (± 1) days after confirmation of the LH surge.	One cycle of: Self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days) to schedule Phase 1 testing; and Daily LH urine sticks from 5 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge to schedule Phase 2 and 3 testing; and One blood sample for the determination of progesterone (≥16 nmol∙L-1) provided +7 (± 1) days after confirmation of the LH surge to schedule Phase 4 testing.
Best practice	Three cycles of Self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤ 35 days); and Daily LH urine sticks from 3 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge; and Check daily changes in cervical mucus from the end of menstruation to mark the end of ovulation (ie, when it changes to a stretchy consistency that resembles raw egg whites and is slippery and very wet).	Three cycles of: Self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days); and Daily LH urine sticks from 3 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge; and Check daily changes in cervical mucus from the end of menstruation to mark the end of ovulation (ie, when it changes to a stretchy consistency that resembles raw egg whites and is slippery and very wet); and One saliva sample for the determination of progesterone (>50 pg/mL), provided +7 (± 1) days after the LH surge has been confirmed.	Three cycles of self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days); and Three cycles of daily LH urine sticks from 5 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge; and One blood sample for the determination of progesterone (≥16 nmol∙L-1) provided +7 (± 1) days after confirmation of the LH surge in at least one of the tracked cycles.	One cycle of: Self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days) to schedule Phase 1 testing; and A day 1, 2, 3 or 4 blood sample for the determination of 17 beta-oestradiol and progesterone to confirm Phase 1; and Daily LH urine sticks from 5 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge to schedule Phase 2 and 3 testing; and A blood sample 48–24 hours before the predicted ovulation for the determination of 17 beta-oestradiol and progesterone to confirm Phase 2; and A blood sample 24–48 hours after the predicted ovulation for the determination of 17 beta-oestradiol and progesterone to confirm Phase 3; and One blood sample for the determination of progesterone (≥16 nmol∙L-1) provided +7 (± 1) days after confirmation of the LH surge to confirm Phase 4.
Gold standard	Three cycles of self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days); and Daily LH urine sticks from 3 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge; and Check daily changes in cervical mucus from the end of menstruation to mark the end of ovulation (ie, when it changes to a stretchy consistency that resembles raw egg whites and is slippery and very wet); and Transvaginal ultrasound (ie, gynaecologist assessment on day 20 or 21 of the menstrual cycle), for at least one of the three tracked cycles.	Three cycles of: Self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days); and Daily LH urine sticks from 3 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge; and Check daily changes in cervical mucus from the end of menstruation to mark the end of ovulation (ie, when it changes to a stretchy consistency that resembles raw egg whites and is slippery and very wet); and One blood sample for the determination of progesterone (≥16 nmol∙L-1), provided +7 (± 1) days after confirmation of the LH surge for at least one of the three tracked cycles.	Three cycles of self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days); and Three cycles of daily LH urine sticks from 5 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge; and A blood sample for the determination of progesterone (≥16 nmol∙L-1) provided +7 (± 1) days after confirmation of the LH surge in the majority of the tracked cycles (ie, in at least two of the three tracked cycles).	More than one cycle of: Self-reporting the onset of bleeding (ie, to establish menstrual cycle length ≥21 and ≤35 days) to schedule Phase 1 testing; and A day 1, 2, 3 or 4 blood sample for the determination of 17 beta-oestradiol and progesterone to confirm Phase 1; and Daily LH urine sticks from 5 days before the estimated day of ovulation (ie, the halfway point of the cycle) until confirmation of the LH surge to schedule Phase 2 and 3 testing; and A blood sample 48–24 hours before the predicted ovulation for the determination of 17 beta-oestradiol and progesterone to confirm Phase 2; and A blood sample 24–48 hours after the predicted ovulation for the determination of 17 beta-oestradiol and progesterone to confirm Phase 3; and One blood sample for the determination of progesterone (≥16 nmol∙L-1) provided +7 (± 1) days after confirmation of the LH surge to confirm Phase 4.

Please note that the schedule for a research approach for naturally menstruating women before and when testing outcome measures can be adapted based on which phases are under investigation. For example, if Phase 3 testing is not used, the measures associated with Phase 3 can be excluded.

LH, luteinising hormone.

Determination of symptoms

Cyclical symptoms should be self-reported for at least three consecutive menstrual cycles to identify patterns and their association with different phases of the menstrual cycle (table 4). Data on the type, intensity and duration of symptoms can be collected using a diary or a specially designed form, enabling players and practitioners to better understand and respond to the cyclical nature of symptomatology.

Table 4. Recommended standards for determining menstrual cycle symptoms in practice and research.

Minimum standard	Three consecutive cycles of self-reporting symptoms in bleeding (Phase 1) and non-bleeding days
Best practice	Three consecutive cycles of self-reporting symptoms in bleeding days (Phase 1) and non-bleeding days, wherein symptoms reported during ovulation can be specified as Phase 2 symptoms.
Gold standard	Three consecutive cycles of self-reporting symptoms in bleeding (Phase 1) and non-bleeding days, wherein symptoms reported during ovulation can be specified as Phase 2 symptoms and symptoms reported during the high progesterone days can be specified as Phase 4 symptoms.

What are the best practices for disseminating and implementing useful menstrual cycle tracking in football?

While menstrual cycle tracking may support athletes’ well-being and knowledge, potential unintended consequences must also be considered. These include privacy concerns, discomfort or stigma around discussing menstruation, cultural barriers or, more seriously, risks of interpersonal harm or coercion. Athletes may also fear negative consequences, such as team selection bias or judgement if sensitive information is disclosed.²⁶ These concerns must be acknowledged and addressed through voluntary participation, robust confidentiality safeguards and clear communication about data use and access. Players should also be able to opt out at any time without fear of reprisals related to team selection or playing time.

Best practices for implementing menstrual cycle tracking in football emphasise the importance of education, informed consent, ethical compliance and cultural sensitivity. Cultural beliefs about menstruation vary widely across cultures and individuals.²⁷ In some contexts, it is openly discussed, wheras in others, it is considered private or taboo. Implementing tracking protocols requires sensitivity to these differences to avoid stigma or discomfort, not only for players, but also for medical staff members.²⁷

Before initiating tracking, players should receive comprehensive education on menstrual health and the objectives of monitoring their cycles. This education should explain the purpose and potential benefits of tracking symptoms and phases. Additionally, players and staff must be informed about the individuals who will access their menstrual health data, including coaching, performance and medical staff. Consent for data sharing must be obtained from players in advance.

Data handling must strictly adhere to local General Data Protection Regulations to safeguard privacy and security. Players should receive regular updates on menstrual cycle trends tailored to their preferences. Tracking methods should be as affordable and minimally intrusive as possible, ensuring a balance between practicality and player comfort.

Conducting menstrual cycle tracking with a clear purpose is essential, ensuring that any adverse findings are addressed with adequate resources and action plans. Ethical considerations, such as obtaining clearance from relevant committees when necessary, must be considered.²⁸ Ethical approval from relevant committees may be required for research studies; however, clinical monitoring for health and performance does not typically require approval from the institutional review board. Above all, participation in menstrual cycle tracking should remain voluntary, allowing players to opt in and keep their information private.²⁸

Methodological considerations when studying the menstrual cycle

This section is intended for researchers who study menstrual cycle patterns and their association with football performance and injury risk. When studying the menstrual cycle, reliable and precise data collection methods must be used to gather essential information such as cycle length, ovulation and ovarian hormone levels. Determining the appropriate sample size through power analyses ensures that the study has sufficient statistical power to detect meaningful effects. Additionally, strategies to address missing data, such as when players fail to report menstrual cycle information, should be planned to maintain the integrity of the analysis.

To account for individual variability among participants, statistical techniques such as mixed-effects models with random effects are valuable, allowing for subject-specific modelling. The relationships between menstrual cycle phases and performance metrics can be explored using statistical approaches such as correlation, mediation and moderator analysis. However, statistical associations do not necessarily imply causation. Researchers must also consider confounding variables that influence menstrual cycle patterns and athletic performance, such as nutrition, sleep, stress levels and training intensity. Moreover, concurrent data on potential confounding factors should also be recorded during the entire tracking period.

Menstrual cycle phases can be treated as categorical predictors, similar to comparing performance between the follicular (first half) and luteal (second half) phases. However, it is also advisable to model ovarian hormone fluctuations as continuous predictors to capture their nuanced effects on performance and health. For longitudinal data, specialised statistical methods are necessary for repeated measurements of the same individuals. Repeated-measures analysis of variance is suitable when measurements are evenly spaced and consistent across participants. Mixed-effects or hierarchical linear models are more appropriate when there are unequal measurements or missing data. Additionally, generalised estimating equations can be employed to estimate population-averaged effects, providing an alternative to subject-specific modelling.

Discussion

This consensus on menstrual cycle tracking in women’s football represents a significant step toward integrating evidence-based practices into player health and performance management. By synthesising current knowledge and consulting expert opinions, the consensus addresses gaps where empirical evidence may be insufficient, ensuring that recommendations are practical and actionable.

The consensus process revealed several key findings. First, while claims about the effect of menstrual cycle phases on performance and injury risk are prevalent, the evidence supporting these claims remains inconclusive.^{12 29},³² This is partly due to inconsistent methodologies, heterogeneous samples, invalid measurements and differing definitions of menstrual phases.⁹ This emphasises the need for individualised approaches considering player-specific factors, including physical, psychological and contextual variables. The consensus statements emphasise the importance of striking a balance between scientific rigour and practical applicability, particularly in the context of high-performance team sports, where effective implementation is central.

The panel’s recommendations for meaningful menstrual cycle measures, such as regular bleeding, symptom tracking, ovulation and ovarian hormone levels, provide a comprehensive framework for understanding and monitoring menstrual health in football. These measures offer insights into a player’s physiological status and can help identify potential health concerns, such as menstrual irregularities or hormonal imbalances, which may affect performance and well-being. Notably, the panel emphasised the importance of prioritising player education, informed consent and cultural sensitivity to ensure ethical and respectful implementation.

A key strength of this consensus lies in its rigorous methodology. The RAM provided a structured approach to integrating evidence with expert judgement, enabling robust decision-making. The iterative Delphi rounds, complemented by in-person discussions, ensured a comprehensive evaluation and refinement of the evidence statements. Despite variations in initial agreement, achieving consensus on 82 statements underscores the effectiveness of this collaborative approach.

However, the process also revealed areas where further research is needed. Current evidence lacks sufficient coverage of the variability in menstrual cycle experiences among athletes and fails to fully elucidate the relationships between menstrual phases, performance metrics and injury risks. This highlights the importance of prioritising research investigating these complex interactions using high-quality, longitudinal and individualised methodologies. Such studies should consider physiological factors and external influences, such as training and match load, travel schedules and psychosocial dynamics, which are particularly pertinent in football.

The recommendations outlined in this consensus serve as a foundation for future efforts to integrate menstrual cycle tracking into routine practice. However, the implementation of these recommendations will require a multifaceted approach. Education and capacity-building among coaches, medical staff and players are essential for understanding and acceptance of menstrual health as a fundamental aspect of athlete care. Additionally, practical tools and resources, such as standardised tracking protocols and user-friendly monitoring platforms, will be essential to facilitate adoption and ensure data consistency. Looking ahead, integrating psychological and sociological perspectives may further enhance the application of these recommendations, ensuring that future approaches address not only physiological and practical aspects but also the broader biopsychosocial context of player well-being.

Furthermore, the panel emphasised the significance of maintaining player autonomy and safeguarding data privacy throughout the tracking process. Participation should remain voluntary, with clear communication about how data will be used and protected. Ethical considerations, including cultural and individual differences, must stay at the forefront of implementation efforts to ensure that menstrual cycle tracking supports players’ well-being rather than imposing on it.

Conclusion

This consensus provides a comprehensive and evidence-based framework for menstrual cycle tracking in women’s football. It emphasises the potential of monitoring to enhance player health, well-being and performance while pointing out the need to address significant knowledge gaps and research priorities. This consensus is a foundation for advancing female athlete care and promoting equity in sports science and medicine by fostering collaboration among researchers, practitioners and players.