An updated look at athlete retention and training age
USA Swimming is ramping up its statistical reporting. It's time for NGBs to get real retention numbers into their data mix.
USA Swimming recently published a statistical analysis of its 2023 Club Excellence program. In this program the top 200 clubs in the country are determined by a points scheme based on athlete performance. The report correlated variables such as coaching experience, club size, number of meets attended, etc. with the overall club excellence scores in an effort to identify factors that might help explain the success of these award winning clubs.
If you're interested in the actual findings you can read the report by clicking the link above. You can find more info about the USA Swimming Club Excellence Program itself by clicking here.
Retention: A stat that could be tracked but wasn't
One of the stats used in the report was retention rate. This ranged from 81% to 85%. However, in recent podcasts and YouTube interviews USA staffers noted that this number is a simple membership renewal rate, not actual retention. It measures how many athletes re-register with a club from one year to the next; it's primarily a financial metric. It's difficult to see how any significant demographic information could be derived from a renewal rate.
In the very first article I wrote for this newsletter in 2021 I noted that if clubs and national sport governing bodies (NGBs) calculated real retention data and coupled it with average training age they could better understand the dynamics of their athlete pool and the sport's long-term, future performance. As I said at the time:
“Retention rates and average training ages are predictive of future overall NGB performance, and are probably the two most informative metrics for sport administrators. Rising retention rates and higher average training ages are good indicators of future elite performance and the often talked about talent that goes with it.”
The data needed for these calculations already exists within NGB databases. USA Swimming recently completed an almost total rebuild of its data systems focusing not only on membership management but also performance tracking. The key data point in tracking both retention and training age is the date of an athlete's first registration with the NGB. All retention and training age calculations are based on that date and subsequent annual registration counts.
Beginning in the late 1990s, USA Swimming saw an explosion of youngsters in the sport. When I was coaching there were over 300,000 registered athletes and by the time I left the deck in 2008 there were close to 400,000 athletes churning up and down pools throughout the country. Swimming officials were delighted, growth is good, new athletes joining the sport is always good. But to gain insight on performance we have to know how many of those new athletes are sticking around (retention) and for how long (training age).
Time is the most important factor when it comes to creating athletic ability, so understanding retention and training age data is key to long term sport performance.
Retention
Retention measures how long athletes remain engaged from the time they first join the sport. The critical time for measuring retention is during the first few years of participation. Clubs should do what they can to make it easy for families to overcome early excuses for leaving such as "didn't like it", "wasn't having fun", "took too much time", etc. with the knowledge that re-registration during the first few years is critical to long term participation. Eventually athletes will either become invested in the sport, making it unlikely that they will leave, or they will decide the sport is not for them and dropout.
Retention, however, eventually loses relevance; it doesn’t have to be tracked forever. NGBs need to decide what tracking period is appropriate. Three to five years is probably the useful range but NGBs could decide differently based on their own needs. Athletes who stay involved with a sport for five years are invested in the activity and are unlikely to dropout.
Retention is tracked in cohorts. For example, all athletes joining USA Swimming for the first time in 2024 would be assigned to the 2024 cohort. The 1-year retention rate would be the percentage of the 2024 cohort who re-register for 2025. The 2-year retention rate for the 2024 cohort would count those athletes who re-register for 2026, and so on year-by-year.
A cohort is an identifiable group of athletes. Retention tracks specific cohorts, not just numbers. This is what distinguishes retention rates from renewal rates.
Figure 1 shows what cohort tracking looks like for the fictional Malaysian Parkour Association (MPA). 1500 new athletes were registered with the MPA in 2016. In 2017, 69% of those 1500 athletes re-registered, so the 1-year retention rate for the 2016 cohort is 69%. The 2-year rate is 58% and so on until we reach a 5-year retention rate of 29%.
Each year a new registration cohort is formed and tracked. The 1-year rate for the 2017 cohort is 72% and so on up until the 2020 cohort (when this chart was made), which has a 1-year rate of 77%.
Note: The 2017 cohort is a completely different group of athletes from those who initially registered in 2016. Cohorts are tracked as separate groups.
Further atomicity is achieved by extending the calculation to include age breakdowns within the cohort. Setting a sensible range for this sub-cohort analysis keeps the numbers relevant. While it may be possible to track all ages in a dedicated application it doesn't make much sense to look outside the 7 to 16 year age range.
Figure 2 shows what adding the age dimension looks like for our fictional Parkour Association:
In Figure 2 the registration age of each athlete is their age at the time they first registered, so a 7-year-old in 2016 though obviously aging over the five years covered in Figure 2 is counted as part of the 2016, 7-year-old sub-cohort for this report and likewise for the other ages listed. This allows a much more granular look at retention within the larger cohort.
In other words, 7-year-olds in the 2016 cohort are a specific group of people and are tracked as such even as they age. Cohorts and their age sub-cohorts are discrete groups. Sometimes it's hard to get your mind around this concept but working with this kind of information, even for a little while, makes it easier.
Retaining athletes is the key to investment in the sport. Higher retention rates mean athletes are engaged longer. Longer engagement creates an athlete pool with greater experience, higher levels of skill, and better competitive performance overall. By being involved longer, young athletes are doing exactly what expertise research says they should be doing: Practicing more, gaining experience, and developing their own reasons for being there, or in other words, becoming invested.
Training age
Athlete training age is a proxy for experience. An athlete's training age is calculated simply by counting the number of years they have been involved in a sport. Unlike retention, which is more of a population metric i.e. tracked in groups, training age is tracked for each individual athlete.
As a general proposition, athletes with higher training ages have higher skill levels and more experience. By combining the average training age of a registration cohort with retention rates NGBs can turn simple registration data into useful predictive metrics as well as providing a snapshot of the overall strength of the athlete pool. In other words, if the average training age is rising then the athlete pool is growing in experience and ability.
Experience in the athlete pool is worth hanging on to. It’s valuable not only to the athlete but to the club and NGB as well. It might be intangible but it has long-term value.
If an athlete with a training age of 1, 2 or 3 quits the sport and is replaced by a new athlete with no experience at all, the NGB may keep the membership numbers but it loses the experience. Think about what that means if the experience level diminishes over time and throughout the athlete pool.
Membership growth is a good thing. But it’s possible that high growth masks both low retention and low or dropping training age. Membership growth is easy to see and report. Retention is rarely calculated and is usually reported incorrectly, membership renewal often masquerades as retention, for example.
This is why it's important to understand the differences between retention, training age, growth, and renewal rates. They provide important information but they all measure different things.
For more about training age and how it is measured and used check out this article.
Investment
Young athletes become invested in a sport only after they acquire some necessary skills, become fit enough to actually play the game, and participate often enough to gain experience. In other words, these factors allow youngsters to enjoy the activity, thus making it more likely they will continue participating.
Parents also become invested mostly due to their child's interest but also because of aspects affecting other parts of family life.
If NGBs can consistently give families a reason to stay involved they will. But enjoyment is subjective, and sport administrators err when they organize grassroots programs on the assumption athletes join with dreams of Olympic glory. Youngsters get involved with sport initially because they’re fun and their friends also play. Parents get involved because the sport is convenient and it provides a wholesome fitness activity for their children.
Olympic medals, professional contracts, and college scholarships may be good aspirational goals, but they are not the reason youngsters join sport programs.
Reporting retention and training age metrics should be done routinely as with growth and renewal rates, and all administrators should be familiar with what these important numbers mean.
The data needed to calculate retention and training age metrics are already part of membership management systems. It’s a simple database function that does nothing more than count. There’s no complicated math involved.