A machine learning approach for the classification of sports based on a coaches' perspective of environmental, individual and task requirements: A sports profile analysis.

Well-designed talent programmes in sports with a focus on talent identification, orientation, development, and transfer support the engagement of young individuals and the pursuit of elite performance. To facilitate these processes, an analysis of task, environmental and individual characteristics per sport is much needed. The aims of this study were to 1) analyse whether unique profiles per sport could be established by generic characteristics and 2) to discuss similarities and differences for the potential application in talent development and transfer. By means of a validated survey, 1247 coaches from 34 sports ranked 18 characteristics on importance to their sports (0 = not important - 10 = very important). To discriminate the responses per sport a Discriminant Analysis (DA) was carried out. To refine the DA-classification, Uniform Manifold Approximation and Projection (UMAP) with CatBoost classifier was performed. To test the performance of the CatBoost classifier-algorithm, a confusion-matrix was generated. The cross-validated DA showed that 70.2% of the coaches were correctly classified to their sport. The UMAP/CatBoost technique revealed 75.1% accuracy with correctly predicted responses per sport ranging from 18.2% (sailing) to 98.2% (soccer). With varying precision, the algorithm was able to differentiate sports by importance of its characteristics indicating similarities and differences per sport.

A Retrospective Analysis of the National Youth Teams in Volleyball: Were They Always Faster, Taller, and Stronger?

ABSTRACT: Mireille, M, Johan, P, Matthieu, L, and Pieter, V. A retrospective analysis of the national youth teams in volleyball: Were they always faster, taller, and stronger? J Strength Cond Res 36(9): 2615-2621, 2022-Although there are numerous studies comparing the characteristics of young and adult volleyball players of different levels, it remains unclear to what extent these findings can be used for performance prediction because very few are based on longitudinal or retrospective analyses. The aim of the current retrospective study was to test to what extent anthropometry, physical performance, and motor coordination can predict future selection in national youth teams. From 2012 to 2015, 1738 10- to 13-year-old boys and girls who played volleyball completed 3 anthropometric, 4 physical performance, and 3 motor coordination tests. In January 2020, 52 athletes of this sample were found to be part of one of the national youth teams of Belgium. A multivariate analysis of covariance, discriminant analyses, and logistic regression analyses were conducted to compare the test results of the selected vs. the nonselected players. Significance level was set at p ≤ 0.05. Results showed that the selected players were already taller and showed better jumping performance, and for females, they tended to have better motor coordination at the time of baseline measurement. Therefore, it seems important to focus on the development of motor coordination and jumping performance at young ages because superiority in these characteristics increases the chances to be selected for the national team 4-8 years later. Nevertheless, considering the large variation in results, selection cannot be made based on these characteristics alone. The practical implications for coaches and federations with respect to training and talent detection are discussed.

Mind, body, and shuttle: multidimensional benchmarks for talent identification in male youth badminton.

The aim of the study was to identify benchmarks for anthropometric, physical performance, motor coordination, and psychological characteristics by comparing youth badminton players of different levels through the use of a multifactorial test battery. Sixty-one male participants aged 12-18 years were divided into three groups: elite (N = 10), sub-elite (N = 24), and novice (N = 27). Standard test batteries for anthropometry (including measures to estimate biological maturity), physical performance, and motor coordination were applied, as well as the modified PCDEQ2 questionnaire for psychological characteristics of youth athletes (Hill, 2016). Multivariate analyses of covariance (MANCOVAs) with age and biological maturity as covariates were used to investigate differences between skill levels. A discriminant analysis was used to reveal to what extent participants could be correctly assigned to their skill group. Significant differences were found in physical performance (explosive power, flexibility, speed, and endurance), BMI and motor coordination. In the psychological domain, perfectionism was found to be significantly different and elites scored highest. The discriminant analysis showed that 100% of the participants were correctly classified and 80.0% were correctly cross validated. These results significantly add to the previously limited youth players' reference values, and confirm the value of a generic, i.e. without sport-specific testing, multifactorial approach to talent identification in youth badminton.

Sink or Swim? A survival analysis of sport dropout in Australian youth swimmers.

OBJECTIVES: To examine long-term participation and dropout rates in Australian youth swimming using survival analyses and to determine whether multiple individual, socio-demographic, and competition-related factors influenced dropout. DESIGN: Retrospective cohort study of registration and competitive performance data. METHODS: Part 1-Registration data from N = 17 161 female (n = 9400) and male (n = 7761) New South Wales (NSW) swimmers aged 10-15 years (inclusive). Part 2-Competition level involvement in a subsample of female (n = 1011) and male (n = 811) swimmers, aged 12-15 years, was also examined. To determine dropout rates and influential factors, Kaplan-Meier survival analyses supplemented by Cox regression were used. RESULTS: (1) Kaplan-Meier analyses identified median sustained participation rates of four years (95% CI = 3.93-4.06), with 15.9% maintaining participation over 10 years. Cox regressions identified age-group was associated with dropout (P < .001), with a 184.9% higher Hazard Rate (HR) for 10- vs 15-year-olds. Residential proximity to major cities was associated with dropout (P < .001), with urban swimmers reporting a 24.8% higher HR rate than rural swimmers. Sex and relative age were not associated with dropout. (2) The subsample median sustained participation was five years (95% CI = 4.79-5.20), with 25.3% maintaining participation for ten years. Level of competition was associated (P < .001), with an 86% higher HR when considering lower competition levels (ie, club/district v national). CONCLUSION: In a large representative sample of swimmers, survival analyses identified age-group, competition level, and city proximity were associated with increased swimming dropout rates.

Accuracy of maturity prediction equations in individual elite male football players.

BACKGROUND: Equations predicting age at peak height velocity (APHV) are often used to assess somatic maturity and to adjust training load accordingly. However, information on the intra-individual accuracy of APHV in youth athletes is not available. AIM: The purpose of this study is to assess the accuracy of predication equations for the estimation of APHV in individual youth male football players. SUBJECTS AND METHODS: Body dimensions were measured at least every three months in 17 elite youth male football players (11.9 ± 0.8 years at baseline) from the 2008-2009 through the 2011-2012 seasons. APHV was predicted at each observation with four suggested equations. Predicted APHV was compared to the player's observed APHV using one-sample-t-tests and equivalence-tests. Longitudinal stability was assessed by comparing the linear coefficient of the deviation to zero. RESULTS: Predicted APHV was equivalent to the observed APHV in none of the players. A difference with a large effect size (Cohen's d > 0.8) was noted in 87% of the predictions. Moreover, predictions were not stable over time in 71% of the cases. CONCLUSIONS: None of the evaluated prediction equations is accurate for estimating APHV in individual players nor are predictions stable over time, which limits their utility for adjusting training programmes.

Does a perceptuomotor skills assessment have added value to detect talent for table tennis in primary school children?

Talent detection intends to support lifelong sports participation, reduce dropouts and stimulate sports at the elite level. For this purpose it is important to reveal the specific profile which directs children to the sports that connect to their strengths and preferences. This study evaluated a perceptuomotor skills assessment as part of talent detection for table tennis, a sport in which perceptuomotor skills are considered essential to cope with the difficult technical aspects. Primary school children (n = 121) and gifted young table tennis players (n = 146) were assessed using the Dutch perceptuomotor skills assessment measuring "ball control" and "gross motor function". A discriminant function analysis confirmed the added value by identifying primary school children fitting the table tennis perceptuomotor profile of the young gifted table tennis players (28%). General linear model analyses for the assessment's individual test items showed that the table tennis players outperformed their primary school peers on all "ball control" items (P < 0.001). In conclusion, the assessment appears to be of added value for talent detection in table tennis at this young age. Longitudinal studies need to reveal the predictive value for sports participation and elite sports.

A coaches' perspective on the contribution of anthropometry, physical performance, and motor coordination in racquet sports.

Differences and similarities between table tennis and other racquet sports exist, but are not well documented in the literature, in spite of the relevance for talent identification. In this study we aimed at identifying the key characteristics of table tennis in comparison with tennis and badminton based upon a survey in coaches. A total of 177 licensed coaches from all across the world and with diverse professional backgrounds completed a survey on anthropometric measures, physical performance, and motor coordination skills. On a scale from 1 to 10, coaches indicated to what extent a talent characteristic was important for their sport. MANOVA identified key differences as well as similarities between all three racquet sports and a subsequent discriminant analysis allocated coaches correctly for table tennis, tennis, and badminton 81.01%, 55.6%, and 71.4% respectively. Our results show that table tennis and other racquet sport coaches are well aware of differences between the racquet sports and also the importance and value of testing and assortment of skill components. These findings can assist coaches in future talent orientation and transfer in racquet sports.

Predictive models reduce talent development costs in female gymnastics.

This retrospective study focuses on the comparison of different predictive models based on the results of a talent identification test battery for female gymnasts. We studied to what extent these models have the potential to optimise selection procedures, and at the same time reduce talent development costs in female artistic gymnastics. The dropout rate of 243 female elite gymnasts was investigated, 5 years past talent selection, using linear (discriminant analysis) and non-linear predictive models (Kohonen feature maps and multilayer perceptron). The coaches classified 51.9% of the participants correct. Discriminant analysis improved the correct classification to 71.6% while the non-linear technique of Kohonen feature maps reached 73.7% correctness. Application of the multilayer perceptron even classified 79.8% of the gymnasts correctly. The combination of different predictive models for talent selection can avoid deselection of high-potential female gymnasts. The selection procedure based upon the different statistical analyses results in decrease of 33.3% of cost because the pool of selected athletes can be reduced to 92 instead of 138 gymnasts (as selected by the coaches). Reduction of the costs allows the limited resources to be fully invested in the high-potential athletes.

Stature and jumping height are required in female volleyball, but motor coordination is a key factor for future elite success.

It was hypothesized that differences in anthropometry, physical performance, and motor coordination would be found between Belgian elite and sub-elite level female volleyball players using a retrospective analysis of test results gathered over a 5-year period. The test sample in this study consisted of 21 young female volleyball players (15.3 ± 1.5 years) who were selected to train at the Flemish Top Sports Academy for Volleyball in 2008. All players (elite, n = 13; sub-elite, n = 8) were included in the same talent development program, and the elite-level athletes were of a high to very high performance levels according to European competition level in 2013. Five multivariate analyses of variance were used. There was no significant effect of playing level on measures of anthropometry (F = 0.455, p = 0.718, (Equation is included in full-text article.)= 0.07), flexibility (F = 1.861, p = 0.188, (Equation is included in full-text article.)= 0.19), strength (F = 1.218, p = 0.355, (Equation is included in full-text article.)= 0.32); and speed and agility (F = 1.176, p = 0.350, (Equation is included in full-text article.)= 0.18). Multivariate analyses of variance revealed significant multivariate effects between playing levels for motor coordination (F = 3.470, p = 0.036, (Equation is included in full-text article.)= 0.59). A Mann-Whitney U test and a sequential discriminant analysis confirmed these results. Previous research revealed that stature and jump height are prerequisites for talent identification in female volleyball. In addition, the results show that motor coordination is an important factor in determining inclusion into the elite level in female volleyball.

A longitudinal study investigating the stability of anthropometry and soccer-specific endurance in pubertal high-level youth soccer players.

We investigated the evolution and stability of anthropometric and soccer-specific endurance characteristics of 42 high-level, pubertal soccer players with high, average and low yo-yo intermittent recovery test level 1 (YYIR1) baseline performances over two and four years. The rates of improvement were calculated for each performance group, and intra-class correlations were used to verify short- and long-term stability. The main finding was that after two and four years, the magnitudes of the differences at baseline were reduced, although players with high YYIR1 baseline performance still covered the largest distance (e.g., low from 703 m to 2126 m; high from 1503 m to 2434 m over four years). Furthermore, the YYIR1 showed a high stability over two years (ICC = 0.76) and a moderate stability over four years (ICC = 0.59), due to large intra-individual differences in YYIR1 performances over time. Anthropometric measures showed very high stability (ICCs between 0.94 to 0.97) over a two-year period, in comparison with a moderate stability (ICCs between 0.57 and 0.75) over four years. These results confirm the moderate-to-high stability of high-intensity running performance in young soccer players, and suggest that the longer the follow-up, the lower the ability to predict player's future potential in running performance. They also show that with growth and maturation, poor performers might only partially catch up their fitter counterparts between 12 and 16 years. Key pointsYoung, high-level soccer players with a relatively low intermittent-endurance capacity are capable to catch up with their better performing peers after four years.Individual development and improvements of anthropometric and physical characteristics should be considered when evaluating young soccer players.

Changes in physical fitness and sports participation among children with different levels of motor competence: a 2-year longitudinal study.

The goal of this study was to investigate differences in physical fitness and sports participation over 2 years in children with relatively high, average, and low motor competence. Physical fitness and gross motor coordination of 501 children between 6-10 years were measured at baseline and baseline+2 years. The sample compromised 2 age cohorts: 6.00-7.99 and 8.00-9.99 years. An age and sex-specific motor quotient at baseline testing was used to subdivide these children into low (MQ < P33), average (P33 ≤ MQ < P66) and high (MQ ≥ P66) motor competence groups. Measures of sports participation were obtained through a physical activity questionnaire in 278 of the same children. Repeated Measures MANCOVA and two separate ANOVAs were used to analyze differences in changes in physical fitness and measures of sports participation respectively. Children with high motor competence scored better on physical fitness tests and participated in sports more often. Since physical fitness levels between groups changed similarly over time, low motor competent children might be at risk for being less physically fit throughout their life. Furthermore, since low motor competent children participate less in sports, they have fewer opportunities of developing motor abilities and physical fitness and this may further prevent them from catching up with their peers with an average or high motor competence.

Reliability and validity of the Yo-Yo intermittent recovery test level 1 in young soccer players.

The present study investigated the test-retest reliability from the Yo-Yo IR1 (distance and heart rate responses), and the ability of the Yo-Yo IR1 to differentiate between elite and non-elite youth soccer players. A total of 228 youth soccer players (11-17 years) participated: 78 non-elite players to examine the test-retest reliability within 1 week, added with 150 elite players to investigate the construct validity. The main finding was that the distance covered was adequately reproducible in the youngest age groups (U13 and U15) and highly reproducible in the oldest age group (U17). Also, the physiological responses were highly reproducible in all age groups. Moreover, the Yo-Yo IR1 test had a high-discriminative ability to distinguish between elite and non-elite young soccer players. Furthermore, age-related standards for the Yo-Yo IR1 established for elite and non-elite groups in this study may be used for comparison of other young soccer players.

A longitudinal study of multidimensional performance characteristics related to physical capacities in youth handball.

Longitudinal research provides valuable information about change and progress towards elite performance. Unfortunately, there is a lack of longitudinal research in handball. In this study, 94 youth handball players (oldest group: n = 41; age 15-17 and youngest group: n = 53; age 13-15) were followed over a three-year period. Repeated measures ANCOVA was conducted to reveal longitudinal changes in anthropometry and physical performance between elite and non-elite players, controlling for maturation. Maturation effects were found for anthropometry (P < 0.01) and some physical performance measures in strength and speed (P < 0.05). The lack of significant interaction effects revealed that during the three years of the study the elite players did not improve their physical performance more rapidly than the non-elites. Furthermore, they had a similar anthropometric profile to the non-elites. Elite players performed better on the Yo-Yo Intermittent Recovery test (P < 0.01; on average 24.0 in the youngest group and 25.2% in the oldest group over the three years) and on the speed and coordination items (P < 0.05; shuttle run: 3.6 and 5.1%; cross hopping: 11.0 and 14.8%, handball-specific shuttle run: 7.6 and 7.7%; slalom dribble test: 10.7 and 8.9%; sprint 30 m: 4.9 and 3.9%). Additionally, Yo-Yo performance and coordination with and without a ball were the most discriminating factors between the playing levels. In conclusion, youth coaches and scouts within team handball should recognise the importance of good skills and an excellent endurance for talent identification purposes.

Can perceptuo-motor skills outcomes predict future competition participation/drop-out and competition performance in youth table tennis players? A 9-year follow-up study.

Tools that provide a fair estimate of young table tennis players' potential and their chances to succeed will support making decisions whether to commit to an extensive development program and the accompanying lifestyle. Consequently, this study included two research questions (RQ) to evaluate the capability of the Dutch perceptuo-motor skills assessment to predict competition participation/drop-out (RQ1) and competition performance (RQ2) in young table tennis players (n = 39; 7-11 years) using a tracking period of 9 years. The perceptuo-motor skills assessment consists of eight tests assessing gross motor function (i.e., sprint, agility, vertical jump) and ball control (i.e., speed while dribbling, aiming at target, ball skills, throwing a ball and eye-hand coordination). A Cox regression analysis demonstrated that a higher level of ball control was associated with a lower risk to drop-out from table tennis competition. The eye-hand coordination test appeared to be most suitable since it was the only test included in the multivariable Cox regression model (HR = .908; p = .001) (RQ1). Similarly, a multilevel regression analysis showed that a higher level of ball control was associated with a higher future competition performance. The eye-hand coordination and aiming at target tests were included in the multivariable multilevel model (p < 0.05; R2 = 36.4%) (RQ2). This evaluation demonstrates promising prospects for the perceptuo-motor skills assessment to be included in a talent development programme. Future studies are needed to obtain valid thresholds scores and clarify the predictive value in a larger sample of youth competition players.

The value of a non-sport-specific motor test battery in predicting performance in young female gymnasts.

Gymnastics talent identification focuses on the identification of young gymnasts who display characteristics for potential success in the future. The aim of this study was to identify which current performance characteristics are related to performance in competition 2 years later. Twenty-three female gymnasts aged 7-8 years completed a multidimensional test battery measuring anthropometric, physical, and coordinative characteristics and were technically evaluated by expert coaches. Two years later, the all-around competition results of those gymnasts now participating in elite (n = 12) and sub-elite (n = 11) competition were obtained. None of the initial measurements significantly correlated with the results of the sub-elite gymnasts 2 years later. For the elite gymnasts, a non-sport-specific motor test battery correlated strongly with the competition result, with more than 40% of the variation in competition performance being explained by the result on that test 2 years earlier. Neither the coaches' judgement nor the anthropometric and physical characteristics were sensitive enough to predict performance. A motor coordination test might be valuable in the early identification of gymnasts, as its discriminative and predictive qualities might be sufficiently powerful for selection within a relatively homogeneous population of gymnasts exhibiting similar anthropometric and physical profiles.

Differences in physical fitness and gross motor coordination in boys aged 6-12 years specializing in one versus sampling more than one sport.

The Developmental Model of Sports Participation proposes two pathways towards expertise in sports between 6 and 12 years of age: early specialization and early diversification. This study investigated the effect of sampling various sports and of spending many or few hours in sports on fitness and gross motor coordination. Altogether, 735 boys in three age groups (6-8, 8-10, and 10-12 years) were profiled using a fitness test battery. A computerized physical activity questionnaire was used to obtain data on sports participation. In the eldest group, (M)ANCOVA showed a positive effect of sampling various sports on strength, speed, endurance, and gross motor coordination (P < 0.05). A positive effect of many hours per week spent in sports was apparent in every age group. These data suggest an acute positive effect of many hours in sports and a latent positive effect of early sampling on fitness and gross motor coordination. Multiple comparisons revealed that boys aged 10-12 years, who spent many hours in various sports, performed better on standing broad jump (P < 0.05) and gross motor coordination (P < 0.05) than boys specializing in a single sport. Therefore, our results highlight the importance of spending many hours in sports and sampling various sports in the development of fitness and gross motor coordination.

The importance of performance in youth competitions as an indicator of future success in cycling.

ABSTRACTIn sports, outperforming your peers at young age does not guarantee a professional sports career as an adult. To gain more insight in how performance in youth cycling competitions can be an indicator for future success, the current study (a) examined differences in success rate between future achievers and future non-achievers, (b) investigated whether the relative age effect affects these career pathways and (c) explored to what extent youth competitive performance can predict success at adult age. The sample consisted of 307 male road cyclists who achieved at least one top 10 result during national and provincial youth competitions (U15, U17, U19). Thirty-two were classified as future achievers because they reached senior elite level; the remaining 275 were classed as future non-achievers. Non-parametric analyses of longitudinal data, Kruskal-Wallis and logistic regressions were applied. These analyses revealed that the future achievers started to outperform the future non-achievers from U17 onwards. While the relatively older cyclists have an advantage over other cyclists in U15, this effect was smaller in U17 and was absent in U19. Finally, the competitive success rate of U15 cyclists could not predict success at adult age. However, for U17 and U19 cyclists each additional top 10 result was associated with 3-5%, and 6% higher chance to reach elite level at adult age, respectively. Overall, these results demonstrate that estimating potential based on competition results is unpredictable in the U15 category, however, may provide a better indication of future success from U17 onwards.Highlights The competitive success rate of U15 cyclists could not predict success at adult ageFrom the U17 category onwards, future achievers had higher success rates, and success rate has some predictive value for performance at senior elite level.Competitive performance is influenced by relative age effect in the U15 category, however, this effect disappeared as the athlete progressed into older age categories.Future non-achievers experience a significant decrease in success rate when transitioning to a new competition category.

Is Motor Coordination the Key to Success in Youth Cycling?

PURPOSE: To evaluate the predictive value of a (non-)sport-specific test battery on the future success of young cyclists, test scores were compared with competition performances 2-3 years later. METHODS: Three motor coordination, 5 physical performance, and 2 cycling-specific measurements were collected in 111 U15 (13.0-14.9 y) and 67 U17 (15.0-16.9 y) male road cyclists. In addition, maturity status, relative age, and competition history were assessed. National and provincial competition results 2-3 years later, in the U17year2 and U19year2 categories, were submitted to 2 separate 4-stage hierarchical regressions. RESULTS: The results of the model of the U15 group revealed that maturity, relative age, competition history, motor coordination, physical performance, and cycling-specific performance accounted for 22.6% of the variance in competitive success. For the U15 category, only maturity and motor coordination were significant predictors of competitive success in the U17year2 category. Maturity and motor coordination each uniquely explained ±5% of the variance. However, for the U17 group-neither motor coordination, physical performance, nor cycling-specific performance could predict competitive success in the U19year2 category. CONCLUSIONS: The current study underlines the importance of general motor coordination as a building block necessary for optimal development in youth cycling. However, considering the lack of predictive value from the U17 category onward, other features may determine further development of youth athletes. Nevertheless, it is questioned why athletes need to possess a minimum level of all physical, motor coordination, and cycling-specific characteristics to experience success and enjoyment in their sport.

Primary School Pupils: Unequal GMC Developmental Pathways in a Single School Year.

Gross motor coordination (GMC) is essential for the development of specific motor skills and long-term participation in physical activities and sports. Group analysis reveals that, on average, children develop these skills gradually; however, how individuals develop GMC is less clear. The main aim of this study is to increase the understanding of developmental patterns within one school year, and whether children's grade, gender, or baseline GMC proficiency are associated with these developmental patterns. In total, 2594 Dutch children aged 6−12 years performed the modified Körper Koordinations Test für Kinder (KTK3+) twice in one school year (autumn and spring). The KTK3+ includes four subtests: walking backwards, moving sideways, jumping sideways, and eye-hand coordination (EHC) test. On average, children developed significantly on all subtests (p < 0.001). At baseline, children in higher grades scored significantly higher than children in lower grades, and children in grades 5 and 6 (age 9 and 10 years) showed most development (raw scores on average, p < 0.001). Boys outperformed girls on EHC across all grades, whereas girls outperformed boys on walking backwards. Nevertheless, both boys and girls developed similarly. Children with lower scores at baseline developed more quickly across all grades. Noteworthy is that 12.1−24% (depending on the test item) of the children scored lower in the spring than in the autumn tests. On average, children develop their GMC; however, we report large differences in their individual trajectories and note that a substantial number did not show a positive GMC development. Further research should examine GMC development with more possible influencing factors as well as over a longer time span to better understand differences in children's GMC development. This may result in more individualized programs in PE lessons, enabling children to optimally develop their GMC, and better use of GMC assessment tools to monitor children's development.

Predicting Youth Athlete Sleep Quality and the Development of a Translational Tool to Inform Practitioner Decision Making.

BACKGROUND: Identifying key variables that predict sleep quality in youth athletes allows practitioners to monitor the most parsimonious set of variables that can improve athlete buy-in and compliance for athlete self-report measurement. Translating these findings into a decision-making tool could facilitate practitioner willingness to monitor sleep in athletes. HYPOTHESIS: Key predictor variables, identified by feature reduction techniques, will lead to higher predictive accuracy in determining youth athletes with poor sleep quality. STUDY DESIGN: Cross-sectional study. LEVEL OF EVIDENCE: Level 3. METHODS: A group (N = 115) of elite youth athletes completed questionnaires consisting of the Pittsburgh Sleep Quality Index and questions on sport participation, training, sleep environment, and sleep hygiene habits. A least absolute shrinkage and selection operator regression model was used for feature reduction and to select factors to train a feature-reduced sleep quality classification model. These were compared with a classification model utilizing the full feature set. RESULTS: Sport type, training before 8 am, training hours per week, presleep computer usage, presleep texting or calling, prebedtime reading, and during-sleep time checks on digital devices were identified as variables of greatest influence on sleep quality and used for the reduced feature set modeling. The reduced feature set model performed better (area under the curve, 0.80; sensitivity, 0.57; specificity, 0.80) than the full feature set models in classifying youth athlete sleep quality. CONCLUSION: The findings of our study highlight that sleep quality of elite youth athletes is best predicted by specific sport participation, training, and sleep hygiene habits. CLINICAL RELEVANCE: Education and interventions around the training and sleep hygiene factors that were identified to most influence the sleep quality of youth athletes could be prioritized to optimize their sleep characteristics. The developed sleep quality nomogram may be useful as a decision-making tool to improve sleep monitoring practice among practitioners.