By Dr. Pieter Vansteenkiste, postdoctoral researcher in sports science (Ghent University), expert in motor control and talent development, and Jonas Desloovere, Honours student Physical Education (Ghent University).

Introduction

Predicting the adult height of youth athletes can help coaches and sports organizations to make more informed decisions about developmental pathways, talent identification, and players’ positions. Furthermore, the predicted adult height is a cornerstone metric for the ‘Percentage of Predicted Adult Height (%PAH) that is often used as a proxy for biological age in youth athletes. Read more about the importance of monitoring growth and maturity here.

Based on biological principles such as genetics, anthropometry, and skeletal maturation, several methods have been developed to estimate adult height of youth athletes. Each method varies in the required input variables, practicality, accuracy, and invasiveness. Below we provide a short overview of some of the most common methods to estimate adult height for youth athletes.

Skeletal age

HOW IT WORKS By taking an X-ray of the hand and wrist, the degree of ossification of the growth plates can be compared to reference images to determine skeletal age. As skeletal age is strongly associated with biological maturity, reference tables (Bayley & Pinneau, 1952) or prediction equations (Roche et al, 1975) can subsequently be used to predict the adult height. This method is historically considered the gold standard for height prediction.

The skeletal age method is commonly used for children between 5 and 18 years old and is often applied during puberty, when interindividual differences in growth rates are large. Some of the most common methods to determine skeletal age and subsequently predict adult height are Greulich-Pyle (Greulich & Pyle, 1959), Tanner-Whitehouse (Tanner et al, 1975), Fels (Chumela et al, 1989), and BoneXpert (Thodberg et al, 2009). More recent methods tested the use of ultrasound instead of X-rays (Cumming et al, 2024), and apply AI or deep learning systems to evaluate the radiographs (Suh et al, 2023).

ACCURACY The TW3 method has a Root mean Squared error (RMSE) of 3.3cm, while it is 2.8 cm for the BoneXpert method, with small variations according to population and sex (Thodberg et al, 2012; Martin et al, 2016; Lolli et al, 2021; BoneXpert ahp whitepaper 2021). However, accuracy of the predicted adult height increases significantly after puberty (see Figure 2).

Studies in boys and girls with delayed puberty (late mature) have shown that skeletal age methods work reasonably well in this population as well (Bramswig et al, 1990; Kağızmanlı et al, 2025; Yigit et al 2025). For late-maturing boys, the Roche-Wainer-Thissen method seems to result in the most accurate predictions, while Bayley-Pineau tends to overestimate the final height, and the BoneXpert method tends to underestimate the final height (Kağızmanlı et al, 2025).

ADVANTAGES Still considered the gold standard with highest accuracy. Useful in children with atypical growth patterns.

DISADVANTAGES Requires medical intervention (X-ray). Impractical for frequent screening. No information about growth velocity. Interpretation has to be performed by a trained professional.

Maturity offset methods

HOW IT WORKS Maturity offset methods such as Mirwald et al (2002), Moore et al (2015), or Fransen et al (2018) rely on the biological principle that the leg length reaches a peak growth velocity earlier than sitting length (Figure 3). The ratio between leg length and sitting height can therefore be used to estimate maturational status, and subsequently how many years a child is away from the Age at Peak Height Velocity (APHV).

Based on the APHV, a reference table can then be used to estimate the remaining growth (Sherar et al, 2005). Alternatively, knowing that APHV occurs at approximately 90% of our adult height, adult height can be predicted using this percentage and the current height (Sanders et al 2017).

The maturity offset method uses anthropometric variables: chronological age, body height, sitting height, leg length (derived from the previous measures), and body weight. This method is typically applied around the age of peak height velocity (APHV). It is most appropriate for boys aged 12-16 years, and girls aged 10-14 years.

ACCURACY The maturity offset method has 95% error bounds of ±5.3 cm in boys and ±6.8 cm in girls (Sherar et al, 2005). However, multiple studies have questioned the reliability of these maturity offset methods (Teunissen et al, 2020; Carvalho et al, 2025). Furthermore, validity of this method decreases significantly in children who are further away from the APHV, and are late or early maturing (Kozieł 2018).

ADVANTAGES Useful during PHV. Provides insight into biological maturation timing.

DISADVANTAGES Individual and ethnic variations in leg length vs stature proportion can bias the result. Very accurate input of sitting height needed. Less accurate for early and late maturers. Misclassification of maturity timing (pre-circa-post PHV) is rather common.

Khamis-Roche method

HOW IT WORKS The Khamis-Roche method is a somatic method that was developed to predict adult height based on genetic and anthropometric data (Khamis & Roche, 1994). The following variables are required: current height, body mass, chronological age, and average height of biological parents (mid-parent height).

It is a non-invasive method that is often used in sports sciences and paediatrics. This method is applicable to children between 4.0 and 17.5 years old and is considered one of the most accurate approaches for predicting adult height without measuring skeletal age. This method is often considered the best practice standard for routine height predictions in sports settings, and for estimating maturity using Percentage of Predicted Adult Height (%PAH; Monasterio et al, 2024).

ACCURACY This method has 90% error bounds of ±5.3cm in boys and ±4.3cm in girls (Khamis & Roche, 1994). However, this error can increase in 11-15 year olds due to differences in maturation rate (see figure 4), and may increase even more for children in extreme growth percentiles, or who show an atypical growth pattern (e.g. early or late puberty). Some studies have reported that the Khamis-Roche formula has a tendency to underestimate the adult height, especially in late maturing children (Zarow, 1996; Fragoso et al, 2014; Fragoso et al, 2026). Unfortunately, no large prospective study has independently tested the accuracy of this method.

ADVANTAGES Relatively high accuracy without skeletal age. Usable for a wide age range. Easy to apply (no specialist equipment).

DISADVANTAGES Height of both parents needed. Large error for children with atypical growth patterns. Less accurate during PHV. Concerns that the equation might be less useful outside of the original (white) population.

Longitudinal method

HOW IT WORKS The growth curve comparison (GCC) method (Mlakar et al, 2023) predicts adult height by analysing an individual’s longitudinal growth trajectory rather than relying on a single measurement. This method requires repeated height measurements across multiple years, which are then compared to a large reference dataset of growth curves from other children.

Using similarity metrics, the individual growth curve is matched with those of children showing the most similar growth patterns. The model then identifies a subset with comparable growth patterns and uses their observed adult heights and growth increments to estimate the future height of the child

This method is currently not (yet) available on the Hylyght platform, but can be used via SloFit website.

ACCURACY The GCC method has a 95% confidence interval of about 4.3cm for boys, and 3.8 for girls. The prediction error is relatively high in prepubertal ages, due to uncertainty in pubertal timing, but accuracy improves significantly once children enter puberty and growth patterns become more informative (see Figure 5).

ADVANTAGES Captures timing and tempo of growth, including variability in the onset PHV, without measuring biological maturity.

DISADVANTAGES Accuracy is lower in pre-pubertal children, requires longitudinal data, accuracy strongly depends on reference dataset.

AI-based method

HOW IT WORKS Recent advances in artificial intelligence (AI) have enabled the development of AI-based models for predicting adult height (Chun et al 2025). This approach used machine learning on large-scale longitudinal datasets containing anthropometric and body composition data. This method is currently not available on the Hylyght platform.

ACCURACY RMSE of 2.51cm for boys, 2.28cm for girls.

ADVANTAGES High accuracy without the need for X-ray. Generates estimated growth trajectory.

DISADVANTAGES Requires longitudinal input of body composition from bioelectrical impedance. Based on a Korean dataset.

Summary table

FAQ

What is the most accurate method to predict adult height?

Bone age assessment using an X-ray of the left wrist is still considered the most accurate method, with a typical prediction error of ±2.8 cm. However, its use is limited by the need for medical imaging and expert interpretation. More recent methods using longitudinal models might result in similar or even better predictions without the need of X-ray.

Which method is most practical in a sports setting?

Non-invasive methods such as the Mirwald and Khamis-Roche methods are most practical in field settings. They require only basic anthropometric measurements and can be applied quickly without medical equipment. Khamis-Roche is the easiest to apply as it requires only basic anthropometric measurements (height and weight) and parental data, avoiding the need for specialized sitting-height. This also reduces both the measuring error and the time needed to test the athletes. Longitudinal methods show promising but, so far, have seldom been applied in sports settings.

Can adult height be predicted accurately before puberty?

Prediction before puberty is less accurate for all methods because the timing and intensity of the pubertal growth spurt are still unknown. Accuracy improves significantly once children enter, or are past, Peak Height Velocity.

Why is biological maturity important in height prediction?

Children of the same chronological age can differ substantially in biological maturity. Methods that account for maturation (e.g. bone age or Mirwald) provide better insight into remaining growth potential and timing of growth spurts. Learn more about the importance of tracking growth and maturity here.

Which method should be used for early or late maturing children?

Bone age assessment is preferred in early or late maturers because it directly evaluates skeletal maturity. Methods like Mirwald and Khamis-Roche are less reliable in these populations.

How to use the Khamis-Roche method when the height of one or both of the parents is unknown?

If parental height is unknown, the average height of men and women of the country of origin of the parents can be used. However, this can reduce prediction accuracy considerably. If possible, use another method instead.

Why are longitudinal methods like GCC more accurate over time?

Growth curve comparison methods use repeated measurements, allowing them to capture individual growth patterns and pubertal timing. This improves prediction accuracy, especially during and after puberty.

Are AI-based methods better than traditional methods?

AI-based methods can achieve high accuracy by modelling complex growth patterns. However, their performance depends on data quality, and they are less transparent and less validated in practical sports settings.

What should be done if different methods give different predicted adult heights?

It is common for different methods to produce slightly different predictions, as each approach is based on different assumptions (e.g. skeletal maturity, genetics, or growth patterns). In such cases, results should be interpreted within their context. If you have a measure of bone age, this result should be most reliable. If bone age is not available, Khamis-Roche should be more reliable than Mirwald for very tall or short athletes, while Mirwald might be more reliable close to the age of peak height velocity for normal maturing boys.

In any case it is good practice to give a range estimation rather than a single number (e.g. “predicted between 178 and 182” rather than “predicted 180”). If the estimations are far apart, this might indicate an atypical profile such as tall/short for their age combined with being early/late mature. Follow-up on this athlete to see how the estimations of adult height evolve.

References

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About the Author

Dr. Pieter Vansteenkiste is a sports scientist and postdoctoral researcher at Ghent University, specializing in physical education, motor control, and performance data. With a PhD focused on visual information in movement steering, he has authored numerous peer-reviewed scientific papers on sports performance, motor development, analytical methods and talent identification.

Dr. Vansteenkiste’s work bridges academic research and practical sports science, supporting innovative projects like SportKompas and SPOKI. Discover his publications and research via Ghent University and connect on LinkedIn.

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