Written by James Baker, UAE, Paul Read, UK, Philip Graham-Smith, Qatar, Marco Cardinale, Qatar, Thomas W. Jones, UK
Category: Sports Medicine

Volume 13 | Targeted Topic - Sports Medicine in Athletics | 2024
Volume 13 - Targeted Topic - Sports Medicine in Athletics

– Written by James Baker, UAE, Paul Read, UK, Philip Graham-Smith, Qatar, Marco Cardinale, Qatar, Thomas W. Jones, UK



Track & field is a sport that consists of running, jumping, and throwing events that are underpinned by high levels of strength, speed, power, and endurance. National competitions are available in most countries from the age of 14 and international competitions (continental, World championships and Youth Olympics) between 14-16 years. However, at youth level athletes of a similar age can vary considerably in biological maturation which has important implications for competition, talent identification and training1. Natural growth and development positively affect these key physical qualities, giving a distinct advantage to athletes that mature earlier than their peers within their age group.

Research examining national rankings in track and field has highlighted that early success is not a prerequisite for senior success2-4. In many events it has been reported that the progression in results of athletes with early success slows down dramatically after the age of 18, compared with individuals who did not experience success earlier. This has also been observed in swimming5 suggesting that in sports dominated by physical attributes, early success due to advanced maturation might not translate into success at adult level.

Peak Height Velocity (PHV) is defined as a period of rapid growth during adolescence, occurs on average at 11-12 years for girls, and 13-14 years for boys but there are vast differences in the timing between individuals. Athletes who mature earlier are afforded significant advantages in size, speed, power, and strength. These inter-individual differences are greatest between the ages of 13-15 years of age for boys but are largely reduced or disappear by the age of 16-18 years old6. This has also been observed in female athletes, but with a better transition from junior to senior level after the age of menarche2,3. While in most studies maturation data has not been included with a focus on competition results only, it is reasonable to speculate that growth and maturation has an influence on why some athletes fail to maintain their success into the senior ranks. The data presented in this article will help the reader better understand the performance implications and risk of injury and illness associated with monitoring growth and maturation. We will also propose ideas on how to effectively conduct assessments and adjust training interventions to ensure knowledge transfer and practical application.



The assessment of maturity status is not commonplace in track and field due to the predominant amateur status. In other sports settings, such as professional football academies, it is measured regularly as part of the on-going athlete monitoring processes. A practical guide to measuring growth and maturation status and utilising data has been published previously7. Somatic measures of maturity8,9 combining measures of stature, body mass, sitting height, age, and gender with the relevant regression equations offer the most practical measurements of maturity status for youth sport settings at relatively low cost.

The outcome measures provided by such an approach are maturity offset (i.e. years from peak height velocity [YPHV])8 or the percentage of predicted adult height9. Both methods are not immune from errors of estimate and can be population specific as recently reported by other authors10. They also do not provide information about skeletal age which can only be obtained with the analysis of hand x-rays, ultrasound and/or MRI scans. It is best practice to combine the estimates with longitudinal growth data (collected approx. every 3 months) that allow for the determination of the actual changes in stature and body mass, to confirm the estimates and to report the growth rates being experienced by the athletes. In our experience, a large variability occurs also within the same ethnic group and therefore, when the gold standards methods for skeletal age determination are not available, growth progression and prediction of adult height should be considered, taking into account the potential errors of estimates and interpreting data being aware of the variability already identified with individuals with low adult height.



Utilising a consistent data-driven approach with measurement of growth and maturation has allowed us to examine performance at different maturity statuses in track and field sprinting and jumping events. From this, normative data can be generated to provide objective performance evaluations for different stages of maturity and inform talent identification/selection.

Observations from our data (Figure 1) indicate significant improvements in sprint time between approaching-, circa- and post-PHV groups11 grouped according to specific thresholds of percentage predicted adult height (PPAH) as suggested by (1) and outlined in table 1. In the long jump (Figure 2), there were significant increases in jump distance with advancing maturity; however, there was no difference between the approaching- and circa-PHV athletes’ which may be due to greater variability in movement strategies and development of physical characteristics in this stage of maturity. Comparisons between both approaching- and circa-PHV group performances with the post-PHV showed significant increases in long jump performance. These data indicate that more mature athletes (i.e., post-PHV) have significant advantages over athletes that are less mature (i.e., pre, approaching- or circa-PHV). Our observations highlight the importance of interpreting performance alongside the maturity status of individual athletes for a more accurate interpretation. This is of further importance when large inter-individual differences in maturity status exist within athletes engaged in youth level competitions.


To move beyond the limitations of solely using chronological age, normative data are required to interpret performance according to maturity status12. Table 2 includes 60m sprint performance standards for an Arabic national development academy and provides a simple tool for coaches to compare the performance of athletes at a similar stage of maturity utilising the PPAH grouping outlined by Cumming et al.1.

More advanced approaches have been developed to address the inter-individual differences in youth sports competition and testing, some of which are easier to apply with large sets of data and might provide a better approach than a simple comparison to a normative data table. These include bio-banding which involves grouping athletes according to maturity status for competition, rather than age1; correction procedures that can remove age and maturity biases from competitions’ times and distances13 and the evaluation of fitness testing using rolling averages14 using regression equations generated from the data sets.

Figure 3 shows the application of the maturity correction procedure to a set of 60m competition results. The correction applied utilises the maximum maturity status within the sample (99% PAH) but can also be applied using the mean of the group, if preferred. Correcting to the maximum maturity status may allow some insight into how fast the athletes could become when they reach a more mature state. From initial feedback from track and field coaches this approach resonated more than the mean correction method. This was because when correcting to the mean maturity status, the fastest athletes’ times were slowed down which is somewhat counterintuitive in an event where faster is better. In the figure below, the light blue line displays the actual performance time (60m raw score) and the dark blue line shows the maturity corrected 60m time for each athlete based on their maturity status.

What we can see is that when times are corrected for maturity, there is a considerable change in rank for several of the athletes. Table 3 shows the top 6 athletes according to the maturity corrected rank and their actual rank. If common selection procedures were applied (i.e., selecting the fastest athletes in their age group) it is likely that four of the top six athletes would’ve been overlooked, given they finished fifteenth, sixteenth, eighteenth and twenty-fourth.



Periods of rapid growth can also have implications for injury, with heightened risk observed in the period of peak height velocity15. This can have a detrimental effect on an athlete’s development, progression, and future health. The British Association of Sport and Exercise Sciences (BASES) expert statement on child trainability has recommended ceasing the common practice of intensifying training during proposed ‘developmental windows of opportunity’ around the time of puberty16. Therefore increasing training intensity on the basis of perceived accelerated improvement may be counterproductive and increase the risk of injury, overtraining or burnout16.

Different types of injuries have been shown to occur with greater frequency at different maturity statuses. Specifically, incidence of growth-related injuries such as Sever’s and Osgood-Schlatters (<88%), Anterior Inferior Iliac Spine injuries circa-PHV (88-95%) is highest in the pre-PHV period; whereas, spondylosis, muscle and ligament injuries are more common when athletes are post-PHV (>95%)17. Furthermore, when high growth rates (>7.2cm/year) are experienced, there is greater incidence and burden of injury, compared to when growth rates are moderate (3.5-7.2cm/year) or low (<3.5cm/year)18.



Targeted interventions are recommended to address physical deficiencies resulting from rapid growth, and modification of training and competition loads to further reduce injury risk19. Practitioners should monitor growth and estimate maturity status, whilst considering their interaction to manage injury risk. This requires a coordinated approach between the athletes, parents, coaches, teachers, and sport scientists. Talented athletes that are selected to represent schools, clubs and various representative levels (i.e. district, regional, national) can be exposed to excessively high training and competition loads that may lead to injury if not managed correctly. Therefore, it is important that all stakeholders understand the entirety of the athlete’s training and competition schedule.

With maturity status estimated, and longitudinal growth measurements available, four ‘red flag’ questions can be used to assess injury risk:

  1. Is the athlete’s maturity status circa-PHV?
  2. Is their current growth rate >7 cm/year?
  3. Is there a growth-related injury present?
  4. Is there a meaningful change in their movement characteristics?

Being circa-PHV alone is not necessarily an indication of increased risk, some athletes will pass through this phase at a relatively low growth rate and experience few issues. But when accompanied by a high growth rate (e.g., >7 cm/year) and/or there is a growth-related injury present (e.g., Severs, Osgood-Schlatter’s) adapting the athletes training should be considered. This may include reducing impact by using softer surfaces (e.g., grass); reducing training frequency to increase rest between high intensity/high impact sessions; or seeking alternative training modalities entirely. Similarly, if periods of rapid growth have been observed in accordance with alterations in movement characteristics (adolescent awkwardness), targeted interventions may be warranted to re-establish fundamental movement patterns.



This case study highlights an example of two athletes in the same chronological age group (under 16). If we compare their performances to one another as it would happen in age group competition, it is clear to see large differences in performance. Specifically, athlete A is 1.61 seconds slower in the 60m and has a 2.17m shorter long jump PB. It is easy to understand why Athlete B would be selected, and Athlete A might be deselected for competitions and/or overlooked in a talent ID programme.

When we consider the performances in the context of their maturity status, we can see these are at very different stages of maturity (Athlete A is approaching-PHV (88% PAH) and Athlete B post-PHV (99%). Observation of their physical capacities also reveal that Athlete B’s advanced maturity status is accompanied by significant increases in size, strength, power, and speed. However, Athlete A is a late developer, and therefore is yet to experience the same physical development that is associated with advanced maturation. This is reflected in their lower stature, body mass and physical capacities. Given the key role these physical qualities in being successful in track and field, it is unsurprising that the performance differences exist in the 60m and long jump.

Using the maturity benchmarks specific to each athlete’s maturity status (see Table 1) a different perspective emerges around Athlete A’s performance level. His 60m performance is rated “good” and his long jump performance is “average”. If we compare him to the post-PHV benchmarks he would be rated “poor” in both events. Athlete B’s is rated “excellent” in both events against the post-PHV, he is obviously talented, and his selection would be justified. In athlete A’s case, we still don’t know how good he is going to be, and he needs to be monitored and tracked as he matures. But what we do know is that if he gets deselected based on his current performance level, the decision would’ve been made before he had realised his full potential.



In conclusion, the natural process of growth and maturation can impact performance in youth track and field and has the potential to increase injury risk. Monitoring growth and maturation during adolescence is recommended to enhance coaches, athletes, and other stakeholders’ ability to interpret current performance level, and identify when athletes may be at increased risk of injury. Subsequently, this information can be used to adapt training to manage injury risk and improve talent identification processes so that athletes are not deselected before reaching their full potential.


Recommendations for the application of growth and maturation assessments in youth track and field


The authors recommend the following steps:

  1. Estimate individual athlete’s maturity status and measure height and body mass on at least a quarterly basis.
  2. Calculate current rates of change in height (cm/year) and body mass (kg/year) to validate estimated maturity status.
  3. Highlight athletes experiencing high rates of growth (>7 cm/year) that may be at increased risk of injury.
  4. Practitioners should then report this information for all athletes to their coaches, parents and other relevant stakeholders then discuss the implications for performance, injury risk, training, and competition.
  5. All stakeholders should work collaboratively to develop appropriate training programmes for each athlete. Considering training load that appears outside of the main sport also, for example within school sports programmes.
  6. Ensure that the maturity assessment is measured within ±30 days of the desired competition and testing to accurately evaluate performance.
  7. Develop a database including maturity data with the competition results and/or testing data to allow the interpretation and analysis of the results in the described manner.
  8. To be able to perform more advanced analysis methods (i.e. maturity correction procedures) and establish benchmarks, a commitment must be made to collect the maturity data consistently over time.


James Baker B.Sc. (Hons) ASCC1,2,3


Paul Read Ph.D.4,5,6


Philip Graham-Smith Ph.D.2


Marco Cardinale Ph.D.7


Thomas W. Jones Ph.D.3



1       Elite Sport UAE

Dubai, United Arab Emirates


2      Aspire Academy for Sports Excellence,

Doha, Qatar


3      Department of Sport Exercise and Rehabilitation, Northumbria University

Newcastle upon Tyne, UK


4      Faculty of Sport, Allied Health and Performance Science, St Mary’s University

London, United Kingdom


5      School of Sport and Exercise University of Gloucestershire

Gloucester, United Kingdom


6      Division of Surgery and Interventional Science, University College London

London, United Kingdom


7      Aspetar Orthopaedic and Sports Medicine Hospital,

Doha, Qatar





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Header image by Pixabay (Cropped)

Figure 1: 60m sprint performance by maturity status (age range of the athletes 12-16 years).
Figure 2: Long Jump performance by maturity status (age range of the athletes 12-16 years).
Table 1: Maturity Status groups according to % predicted adult height method adapted from Cumming et al1.
Table 2: Performance benchmarks for the indoor 60m sprint by maturity status for males.
Figure 3: Maturity based corrective procedures applied to 60m sprint results.
Table 3: A comparison of corrected and actual rank.
Table 4: A comparison of U16 age group athletes of different maturity statuses.


Volume 13 | Targeted Topic - Sports Medicine in Athletics | 2024
Volume 13 - Targeted Topic - Sports Medicine in Athletics

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