Does early maturation offer the same advantage for girls as it does for boys in player evaluation & selection?

Recent evidence has shown that maturation in girls may have a different and more complicated narrative than boys.

For boys, earlier maturation increases muscle mass, giving significant advantages of power, speed and endurance over later maturers. From the age of 12 the growth spurt becomes increasingly important in determining ongoing selection (1). But is it the same for girls?

Girls mature around two years before boys in the age range 10-14. The average age of the fastest part of the growth spurt for girls is 11.9 and is known as Peak Height Velocity (PHV). A study of over 600 Australian swimmers (2) showed the average age at PHV in age groups 10-12 was 11.7 whereas in age groups 14-15 it was 12.2. These findings replicate a study of 300 Australian netballers (3) where a change of 0.8 in average PHV age was found from age 12 to 15 (from 11.6 to 12.4). Both studies suggest before age 13 being an early maturer is beneficial but from around age 13 being a late maturer may seem to offer a selection advantage, but why?

The growth spurt in girls can initially give a physical advantage through extra muscle mass at around 50% the level of boys. But around 0.5-1 years after PHV girls, & boys, reach Peak Weight Velocity (PWV) naturally adding mass. However while boys add muscle mass, girls add a higher % of fat than muscle. This can negatively affect power, speed & endurance and hence perceived athleticism, risking deselection.

With fast growing limbs comes challenges with movement control, with agility and coordination suddenly more difficult. This ‘Adolescent Awkwardness’ can negatively affect performance and  players are at a heightened risk of deselection during this phase. 

How does this map onto girls age group cricket?

Although some progressive counties are starting to introduce single year age groups for girls, many still have just four age groups, U11, U13, U15 & U18.

The growth spurt lasts around 2 years with peak height being attained on average age at 11.9. So, for normal distribution, around 70% of girls will be 1 year either side of this (10.9-12.9). 15% will be early, before age 10.9 and 15% will be late, after age 12.9. So, in theory for normal distribution, most girls will go through the growth spurt during the U13s and the last year of U11s, assuming the experience of Australian swimmers & netballers maps to English/Welsh cricket (not a given).

How do we get to an U15 cohort with more late maturers? Some possible explanations:

• Later maturers selected at U11 and/or U13 are ‘more’ likely, than earlier maturers, to survive until U15.
• More later maturers than earlier maturers are joining the pathway at U13 upwards.
• Potentially some early maturers have self de selected (dropped out) of the pathway/sport.

Early maturers will go through the growth spurt in the U11s and may not reach the U13s through reduced athleticism and/or adolescent awkwardness. Late maturers will not go through these challenges until U15.

Perhaps when players are older (14 or 15) they are able to ‘mask’ the inevitable changes brought about by the growth spurt because they are a. naturally stronger and b. have more developed skills by this stage. In contrast, for early maturers, in say the U11s, these changes have more relative impact.

Late maturers that were able to be selected and survive the U11s and U13s may possess some other ‘counterbalancing’ factor such as being relatively older within the year group (Relative Age), or have genetic advantages, or more experience (Training Age). 

Practical implications.

1. Measure growth to know where each player is in their natural physical development otherwise comparing apples and oranges.
2. Pay special attention to early maturers within the younger age groups. They may need some ‘leeway’ to be retained in the pathway.
3. Potentially look for less physically developed players at younger age group selection.
4. Maturation selection bias for girls is highly likely to NOT be the same as for boys.

Notes

Both studies (2) & (3) use the Mirwald Maturity Offset method which has been shown to overpredict age at PHV at older adolescent ages. More research is required with other methods (e.g. Khamis Roche) or for longitudinal measurement to show that these are not findings from methodological effects.

We don’t know what the level of maturation selection bias is in English/Welsh girls cricket because it’s not been studied. We only know that no late maturers and 2x expected early maturers were selected for the boys regional U15 festival of 2023 (Bunbury). We also know there are very high levels of Relative Age Effects in English/Welsh girls cricket.

Studies (2) & (3) were cross sectional and not longitudinal.

Issues around maturation selection bias mainly relate to physicality and motor control. Other body components such as the neurological system develop at different times. This may partly explain why RAE is a large issue for girls cricket and it increases (like boys maturation bias) as you go up through the age groups and competitive levels.

This article has mainly focussed on just maturation. Other confounding factors, e.g. Relative Age, Training Age & genetics should also be accounted for when discussing youth development.

References

1. Amanda Johnson et al (2017) Skeletal maturation status is more strongly associated with academy selection than birth quarter. Science and Medicine in Football. Volume 1, 2017 - Issue 2.
2. Hogan C, Abbott S, Halaki M, Torres Castiglioni M, Yamauchi G, Mitchell L, Salter J, Romann M, Cobley S. Maturation-based Corrective Adjustment Procedures (Mat-CAPs) in youth swimming: Evidence for restricted age-group application in females. PLoS One. 2022 Oct 7;17(10):e0275797. doi: 10.1371/journal.pone.0275797. PMID: 36206228; PMCID: PMC9543692.
3. Hackett DA, Tran DL, Way KL, Sanders RH. Effects of Age and Playing Position on Field-Based Physical Fitness Measures in Adolescent Female Netball Players. Pediatr Rep. 2024 Jan 12;16(1):77-87. doi: 10.3390/pediatric16010008. PMID: 38251317; PMCID: PMC10801501.