[6-min read]

There has been some debate recently over the structuring of talent academies in the GAA after the extensive 2019 review and the subsequent implementation of the new GAA Player Pathway. Given how talent identification practices have been painted negatively in recent times with some systems accused of being implemented without the best interests of the holistic development of the athlete in mind. It is critically important that this area be investigated. In Part 1 of this 2-part blog, we looked at coaches’ perceptions of the attributes they assess when selecting players for youth academies. In Part 2, we’re going to be looking at the rate of attrition from youth to elite sport.

Rate of Attrition from Youth to Elite Sport

Another key area of interest is looking at the rate of attrition in sports and the number of athletes that have and can possibly make it at an elite level. There are only 35-40 available spots on most intercounty teams. Is the rate of attrition what would be expected across the GAA? Is it higher or lower relative to the current literature in this area (Sullivan et al., 2018)? What is good with respect to transfer rates from U14 academy teams to first-team settings (Mills et al., 2012)?

The National Collegiate Athletics Association (NCAA) recently published the following statistics looking at high school players’ likelihood of going pro in their respective sports:

In Baseball, of the 482,629 active high school players 6.9% will play at a collegiate level and 8.6% of college players will be drafted into by the MLB, whereby only a fraction will go on to have a substantial career.

The numbers are similar in Basketball, with 541,054 high school players, 3.4% will play in college and only 1.2% of college players will be drafted into the NBA.

The numbers are low again with American Football, 1,093,234 active high school players, 6.5% will play in college and only 1.6% of college players will be drafted into the NFL. Even in a sport with comparably low active high school numbers, the chance of going pro is very low.

With Ice hockey, 35,393 active high school players, 11.2% will play in college and only 6.8% of those college players will go on to be drafted into the NHL.

In summation the chances of going pro as a middle school (ages 11-13) student are minuscule. When you look at the rate of attrition for promising potential athletes it does not look any more promising.

Of the 4,131 draft-eligible NCAA basketball players only 52 will be drafted each year into the NBA (Ashley, 2017). In the NFL of the 16,380 draft-eligible players, only 254 will be drafted. Therefore, the probability of a high school basketballer going pro is 1 in 10,404 which is about 0.01%. American football is 0.09%, Baseball is 0.5%, Ice hockey is 0.4%, and Soccer is 0.08%. 

Of all the NCAA draft-eligible athletes only 0.7% were drafted into the pros. Of all the high school playing population only 0.04% were drafted into the pros. The odds of going pro in any professional sport appear to be incredibly unlikely.

Research conducted in Russia showed similar returns, it was reported that only 0.14% of 35,000 high-potential athletes progressed from entry-level to professional status (Ljach, 1997). A longitudinal study looking at German athletes in seven Olympic sports indicated that only 15 of 4972 (0.3%) of athletes identified at a young age as being high-potential athletes went on to success at a senior international level (Güllich and Emrich, 2006)

Looking at the rate of attrition in a sport closer to home, the following paper looked at the probability of success for academy players at different ages on being selected into an academy, the study titled “Progression from youth to professional soccer: A longitudinal study of successful and unsuccessful academy graduates” (Dugdale et al., 2021). This study found that from the 537 players selected to a club academy over a 12-year period, only 53 obtained a professional contract. Of these 53 players 68% were selected after the age of 12, while individuals selected before this age did not display a high probability of becoming professional players.

The findings from this study would suggest that selection during childhood or early adolescence may not correlate to success as an adult. This would raise concerns about the predictive utility of talent identification models (Till and Baker, 2020).

Research conducted by (Padaki et al., 2017) “Factors that drive youth specialization” highlighted some very similar trends and insights. When surveyed, a staggering 33.2% of youth athletes hope to become professional athletes one day. The overwhelming majority will never accomplish this.

Conclusion

When looking at the rate of attrition data above, it is important to look at it in the context of the GAA. How can we identify what a reasonable transition rate of youth players making it to an inter-county senior team is? Is it possible to apply what we can see in professional sports to a GAA setting? For the players transitioning to senior level, are they spending most of their youth careers in development squads or clubs or in successful school settings and how can they be best prepared irrespective of their route to senior? Is the identification of players at U14 having a positive impact on the career trajectory of that individual?

From the research collected on the identification process of talented individuals coming into academy settings. Much of the research suggests there is a formalised process of identifying objective traits with lend themselves to the identification of future potential. However, there is still a strong sense that many coaches and recruiters make decisions based on the subjective unquantifiable sense of what a player with potential is.

The ability to identify the qualities present in a youth athlete which will delineate the elite and sub-elite is an incredibly difficult process. One thing with is very apparent is that the performance of an individual does not correlate with future performance. It would be advisable for academies to have a very expansive holistic selection process that values a multitude of factors from technical, physical, cognitive, cultural, and social contexts, behaviour, willingness to learn, problem-solving, and positional awareness.

Simply basing selection off a player’s performance will heavily favour the early developers and may possibly miss out on some very talented individuals at an early juncture. This then begs a larger question, when should we start identifying individuals to come into an academy if it is so difficult to select athletes pre and circa-growth spurts? The GAA traditionally began this process due to U14 competitions but is this the most conducive time to identify players or would this process be better administered when players are older? It’s food for thought but a very interesting discussion nonetheless.

The luxury the GAA has is the concept of “As many as possible for as long as possible”. The opportunity exists for players to compete at a high level with their clubs if they are unsuccessful in making it to the elite level. This would highlight that the club is the hub for the development of the elite, sub-elite, and non-elite alike before the county begins selecting players for the senior teams. Having a concurrent system across the club and county would be very profitable for both. If you are interested in learning more about the area of talent identification in the GAA, please contact me via my details below.

References

1. Dugdale, J. H., Sanders, D., Myers, T., Williams, A. M., & Hunter, A. M. (2021). Progression from youth to professional soccer: A longitudinal study of successful and unsuccessful academy graduates. Scandinavian Journal of Medicine & Science in Sports, 31, 73-84.
2. Güllich, A., & Emrich, E. (2006). Evaluation of the support of young athletes in the elite sports system. European Journal for Sport and Society, 3(2), 85-108.
3. Ljach, W. (1997). High-performance sport of children in Russia. Leistungssport, 27, 37-40.
4. Mills, A., Butt, J., Maynard, I., & Harwood, C. (2012). Identifying factors perceived to influence the development of elite youth football academy players. Journal of sports sciences, 30(15), 1593-1604.
5. NCAA website https://www.ncaa.org/sports/2013/12/17/probability-of-competing-beyond-high-school.aspx
6. Padaki, A.S., Popkin, C.A., Hodgins, J.L., Kovacevic, D., Lynch, T.S. and Ahmad, C.S., 2017. Factors that drive youth specialization. Sports health, 9(6), pp.532-536
7. Sullivan, C., Kempton, T., Ward, P., & Coutts, A. J. (2018). Factors associated with early career progression in professional Australian Football players. Journal of sports sciences, 36(19), 2196-2201.
8. Till, K., & Baker, J. (2020). Challenges and [possible] solutions to optimizing talent identification and development in sport. Frontiers in psychology, 11, 664.

About the author

Rob Mulcahy, Head of Youth Athletic Development, Clare GAA