Coaches are an integral part of talent identification in sport and are often used as the “gold standard” against which scientific methods of talent identification are compared. However, their decision-making during this process is not well understood. In this article, we use an ecological approach to explore talent identification in combat sports. We interviewed twenty-four expert, international-level coaches from the Olympic disciplines of boxing, judo, and taekwondo (age: 48.7 + 7.5 years; experience: 20.8 + 8.3 years). Findings indicated that when coaches identify talent they rely on “gut instinct”: intuitive judgements made without conscious thought, used to direct attention to particular athletes or characteristics. Our analysis revealed four major contributors to coaches’ intuition: experiential knowledge, temporal factors, seeing athletes in context, and what can be worked with. Our findings demonstrate that i) athlete selections may be influenced by the coaches’ perceived ability to improve certain athletes (rather than solely on athlete ability); and ii) “instinctual” decisions are the result of years of experience, time spent with the athlete, and the context surrounding the decision. Based on these findings, we recommend that future research focuses on the duration and conditions that are required for coaches to confidently and reliably identify talented athletes.

A typical assumption found in talent identification literature is that different coaches, given the same athletes and circumstances, will identify the same subset of athletes as “talented”. However, while coaches play a major role during talent identification in practical sport settings, there is limited empirical research exploring the processes which underpin this. The purpose of this study was to explore the reliability of “the coach's eye” during the assessment of talent in a group of athletes. Specifically, this project compared inter-coach agreement between nine judo coaches (ages 35.8 ± 10.6 years) with varying levels of experience (12.9 ± 8.9 years) in the evaluation of 24 talented cadet judo athletes (13–15 years) at seven timepoints throughout a 4-day development training camp. Without discussion of their scores with other coaches, coaches provided a single score representing each athlete's “potential for future performance” on an 11-point Likert scale at each timepoint. Scores from each coach were converted into rankings from 1 to 24 to create a normalized scale to facilitate comparison of athletes. Based on their rankings at each timepoint, athletes were placed into one of three evenly distributed groups (high, medium, and low rank). Inter-coach agreement at each timepoint was determined by the number of coaches who ranked each athlete in the same group, categorized at three levels: 50, 75 or 100% agreement. Overall results showed that at completion of the camp, coaches reached 100% agreement on only two athletes, both of whom were in the high rank group. When inter-coach agreement was set at 50%, 15 athletes (62.5%) were placed into like groups. The first timepoint at which coaches were able to differentiate between the majority of athletes was Timepoint 3 (end of day 2). The findings suggest that, in isolation, coaches do not agree on the talent or potential of athletes. This indicates that the “coach's eye” is subjective and variable, and, given the same context, there is poor inter-coach agreement in the identification of talented athletes. In turn, these findings may have significant implications for both future talent identification research and athlete selection processes by sport organizations.

Objectives: The aim of this review was to summarise the existing literature concerning the implementation of menstrual cycle tracking in applied sport settings. Methods: For this scoping review, database searches were conducted in ProQuest, PubMed, Scopus, SportDISCUS, and Web of Science. Screening was performed by two independent reviewers to identify academic publications that related to the concept of menstrual cycle tracking in applied sport settings. Results: Twenty-six articles published between 2001 and 2024 fulfilled the inclusion criteria. These were most commonly original research articles (n = 19) and published in the last two years (n = 20). One research protocol paper and six opinion articles published in academic journals were also included. Twelve of the 26 publications recommend implementing tracking in sport settings; many publications also encourage providing education (n = 13) and facilitating more open communication (n = 10) on menstrual-related topics. Where tracking was conducted, this was done using calendar-based methods alone (n = 5) or in conjunction with urinary (n = 3), capillary blood (n = 2) and venous blood (n = 1) hormone measures, and ovulation test kits (n = 1). Conclusions: Menstrual cycle tracking may be a useful tool for promoting self-awareness, identifying menstrual dysfunction, and managing menstrual symptoms. However, in practice there are potential risks, such as loss of privacy or misuse of data. There is also a need for ecologically valid tracking tools that can identify subtle menstrual disturbances, to make tracking more beneficial and efficient.

Purpose: A novel 4-task Athlete Introductory Movement Screen was developed and tested to provide an appropriate and reliable movement screening tool for youth sport practitioners. Methods: The overhead squat, lunge, push-up, and a prone brace with shoulder touches were selected based on previous assessments. A total of 28 mixed-sport junior athletes (18 boys and 10 girls; mean age = 15.7 [1.8] y) completed screening after viewing standardized demonstration videos. Athletes were filmed performing 8 repetitions of each task and assessed retrospectively by 2 independent raters using a 3-point scale. The primary rater reassessed the footage 3 weeks later. A subgroup (n = 11) repeated the screening 7 days later, and a further 8 athletes were reassessed 6 months later. Intraclass correlation coefficients (ICC), typical error (TE), coefficient of variation (CV%), and weighted kappa (k) were used in reliability analysis. Results: For the Athlete Introductory Movement Screen 4-task sum score, intrarater reliability was high (ICC = .97; CV = 2.8%), whereas interrater reliability was good (intraclass correlation coefficient = .88; CV = 5.6%). There was a range of agreement from fair to almost perfect (k = .31–.89) between raters across individual movements. A 7-day and 6-month test–retest held good reliability and acceptable CVs (≤ 10%) for sum scores. Conclusion: The 4-task Athlete Introductory Movement Screen appears to be a reliable tool for profiling emerging athletes. Reliability was strongest within the same rater; it was lower, yet acceptable, between 2 raters. Scores can provide an overview of appropriate movement competencies, helping practitioners assess training interventions in the athlete development pathway.