Accuracy of maturity prediction equations in individual elite male football players

Teunissen, Jan Willem; Rommers, Nikki; Pion, Johan; Cumming, Sean P.; Rößler, Roland; D’Hondt, Eva; Lenoir, Matthieu; Savelsbergh, Geert J.P.; Malina, Robert M.

doi:10.1080/03014460.2020.1783360

Cited by 29 publications

(48 citation statements)

References 40 publications

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“…Parr et al 34 conducted longitudinal analysis to observe timing of PHV, and illustrated that PAH% was accurate 96% of the time, with MO correct 61% of the time. This, combined with other studies 11,18 highlight potential limitations with MO methods having a tendency to regress towards the mean which may limit their efficacy when differentiating between stages of maturation. Data from the current study would suggest that PAH % is a useful indicator of maturity status in youth team-sport players, however, it does provide maturity estimations that differ from MO methods.…”

Section: Discussionmentioning

confidence: 62%

“…Data from the current study would suggest that PAH % is a useful indicator of maturity status in youth team-sport players, however, it does provide maturity estimations that differ from MO methods. Based on the aforementioned limitations of MO methods, and in conjunction with previous findings, PAH% may offer increased accuracy, 18,34 but is not reliably comparable to MO methods. Therefore, practitioners should employ either a MO or PAH% method of maturity estimation consistently across the various facets of application (e.g.…”

Section: Discussionmentioning

confidence: 90%

“…9 Authors claim that it appears to better account for the systematic error by adopting a polynomial model and estimating a maturity ratio to better reflect the non-linear growth process. However, subsequent critique by Nevill and Burton 17 outlined potential flaws in the equation and the increased likelihood of spurious findings due to chronological age appearing on both sides of the maturity ratio, with similar concerns over accuracy also reported by Teunissen et al 18 A PAH% developed by Khamis and Roche 10 is also widely used within adolescent soccer. 19 Utilising several of the same anthropometric variables and the addition of birth parent stature to ascertain mid-parent stature, the equation can predict the progress towards adult stature as a percentage.…”

Section: Introductionmentioning

confidence: 85%

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Estimating somatic maturity in adolescent soccer players: Methodological comparisons

Salter

Cumming

Hughes

et al. 2021

International Journal of Sports Science & Coaching

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Purpose Monitoring maturation facilitates effective talent development. Various methods of maturity estimation exist with limited knowledge of concordance between methods. This study aims to establish agreement between methods of varied constructs to predict maturity status and compare concordance of methods to categorise players using established thresholds. Methods This study compared four maturity equations using anthropometrical data from 113 male adolescent soccer players (mean ±SD; age, 14.3 ± 1 years) from two academies. Conservative (±1 year) and less conservative (±0.5 years) circa-PHV thresholds were employed. Results Analysis indicates tight (±0.3 year) agreement between maturity offset methods (MO), but broader agreement between MO and predicted adult height methods (–1.5 to 1 year). However, Kappa Cohen k suggests moderate to substantial (44%–67%) and fair to moderate (31%–60%) concordance between methods when using the conservative and less conservative circa-PHV thresholds respectively. Conclusion Despite MO equation iterations claiming to reduce systematic error, they provide very similar estimations. Additionally, practitioners should not use maturity offset and predicted adult height methods interchangeably and are encouraged to apply either method consistently when looking to estimate maturity status or biologically calssify players.

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Section: Discussionmentioning

confidence: 62%

Section: Discussionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 85%

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Estimating somatic maturity in adolescent soccer players: Methodological comparisons

Salter

Cumming

Hughes

et al. 2021

International Journal of Sports Science & Coaching

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“…Validation studies of the original equations in three independent longitudinal series, the Wroclaw Growth Study [7,8], the Fels Longitudinal Study [9] and the Cracow Growth Study [10], and of the modified equations in two of the samples [10,11] have indicated major limitations of the predictions in both males and females. The validity of the prediction equations has also been questioned in longitudinal samples of female artistic gymnasts [12] and soccer players [13,14], but sample sizes in longitudinal samples tend to be limited and to some extent select as they are limited to athletes who have persisted in the respective sports [15]. Similarly, cross-sectional studies of tennis [16] and soccer [17] players have questioned maturity status classifications based on the original prediction equations [1] relative to classifications based on skeletal age.…”

Section: Introductionmentioning

confidence: 99%

Observed and predicted ages at peak height velocity in soccer players

et al. 2021

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The purpose of the study was to evaluate predicted maturity offset (time before age at PHV) and age at PHV (chronological age [CA] minus maturity offset) in a longitudinal sample of 58 under-13 club level soccer players in central Portugal for whom ages at PHV were estimated with the SITAR model. Two maturity offset prediction equations were applied: the original equation which requires CA sitting height, estimated leg length, height and weight, and a modified equation which requires CA and height. Predicted maturity offset increased, on average, with CA at prediction throughout the age range considered, while variation in predicted maturity offset and ages at PHV within CA groups was considerably reduced compared to variation in observed ages at offset and at PHV. Predicted maturity offset and ages at PHV were consistently later than observed maturity offset and age at PHV among early maturing players, and earlier than observed in late maturing players. Both predicted offset and ages at PHV with the two equations were, on average, later than observed among players maturing on time. Intra-individual variation in predicted ages at PHV with each equation was considerable. The results for soccer players were consistent with similar studies in the general population and two recent longitudinal studies of soccer players. The results question the utility of predicted maturity offset and age at PHV as valid indicators of maturity timing and status.

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“…The advanced maturity status of male adolescent athletes and the relatively narrow range of variation at the predicted ages of peak height velocity (PHV) may influence the maturity status evaluation during adolescence and may impair its utility and effectiveness on talent identification and development programs when used at a particular moment. Recently, Rommers et al ( 2020 ) have shown that none of the published equations provided an accurate prediction for individuals. However, although the stability of the predictions within individuals are poor and group classification is not exactly accurate, APHV predicted by the Mirwald equation (Mirwald et al, 2002 ) can be successfully applied among boys who are average (on time) in maturation and during the growth spurt period (~12–15 years).…”

Section: Methodsmentioning

confidence: 99%

Morphological and Fitness Attributes of Young Male Portuguese Basketball Players: Normative Values According to Chronological Age and Years From Peak Height Velocity

Ramos¹,

Massuça²,

Volossovitch³

et al. 2021

Front. Sports Act. Living

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The aims of the present study were: (i) to describe the structural and functional attributes of young male Portuguese basketball players aged 12–16 years and (ii) to generate normative data according to chronological age and years from peak height velocity. A total of 281 male Portuguese young basketball players between the ages of 12 and 16 years were assessed in this study. Chronological age, maturity parameters (maturity offset and predicted age at peak height velocity), morphological (body mass, height, and skinfolds and length), and fitness (sprint, change of direction ability, jump, and upper body strength) attributes were measured. Descriptive statistics were determined for the age and maturity status, and the 10th, 25th, 50th, 75th, and 90th percentiles were chosen as reference values. Descriptive and normative values of the players' morphological and fitness attributes, stratified by age and maturity status, are provided. The normative values of age at peak height velocity (category YAPHV = 0) showed that regional basketball players presented average values (50th percentile) of 169.8 cm for height, 173.3 cm for arm span, 55.6 kg for body mass, 3.34 s for the 20-m speed test, 10.31 s for the T-test, 4.75 m for the 2-kg medicine ball throw, 66.9 kg for the combined right and left handgrip strength, and 30.1 and 35.9 cm for jump height in the countermovement jump (CMJ) and CMJ with arm swing, respectively. In conclusion, these results may be helpful to quantify and control an athlete's performance over time and to adjust strength and conditioning programs to biological demands.

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Accuracy of maturity prediction equations in individual elite male football players

Abstract: Background: Equations predicting age at peak height velocity (APHV) are often used to assess somatic maturity and to adjust training load accordingly. However, no information is available on the intra-individual accuracy of APHV-estimations over time.

Cited by 29 publications

References 40 publications

Estimating somatic maturity in adolescent soccer players: Methodological comparisons

Estimating somatic maturity in adolescent soccer players: Methodological comparisons

Observed and predicted ages at peak height velocity in soccer players

Morphological and Fitness Attributes of Young Male Portuguese Basketball Players: Normative Values According to Chronological Age and Years From Peak Height Velocity

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