Measure what matters!

    Retention and Training Age

    Metrics That Shape the Future of Our Sports

    Understanding the demographic framework behind a sport's registration and participation numbers is essential to managing talent development within the athlete pool. Since we can quantify practically anything nowadays national sport governing bodies (NGBs) should be able to calculate athlete retention and training age metrics directly from annual registration data. Retention rates and average training ages are predictive of future overall NGB performance, thus 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.

    As I have written before, time is the most important factor when it comes to creating athletic ability. Coaching, facilities, and probably a dozen other things are all important in their own way and time, but the most significant determinant to talent creation and high performance is simply: How long have athletes been engaged with the sport? NGBs can measure this with retention and training age metrics.

    Retention measures how long athletes remain engaged from the time they first join a club or team. The critical time for NGBs to work on retaining athletes is during the first few years of participation. Efforts should be directed at making it easier for families to overcome early excuses for leaving such as "didn't like it", "wasn't having fun", "it took too much time", etc.

    Higher retention rates mean that 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.

    Athlete training age measures retention at the individual level. Each additional year an athlete is involved in a sport adds to that athlete's training age. As a general proposition, athletes with higher training ages have higher skill levels and more experience. By combining the average training age of the 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.

    Why is retention important?

    Let's face it, when most sport administrators talk about retention they do it from a financial perspective. Clubs, for example, need to hold on to their athletes to stay in business. This is a valid concern but in this letter I'm talking about a demographic perspective and how NGBs can use strategies to keep youngsters involved in their sport to boost long-term performance.

    New athletes and their families are not invested in the sport at first. They may join for many reasons but once enrolled NGBs, usually through the club system, need to find ways of keeping them involved. If they don't enjoy their first- (or even their second- or third-) year experiences or if they perceive little value from their participation then there is nothing holding them in the sport and the decision to leave and try something else is an easy one -- they're out of there!

    Investment can mean a lot of different things though. Sport administrators err when they organize grassroots programs on the assumption that athletes join with dreams of Olympic glory. The reasons why youngsters get involved with sport initially are based on fun, convenience, fitness, friends -- almost anything except the sport itself.

    Investment occurs after the athlete gains some of the necessary skills, becomes fit enough to actually play the game, and participates often enough to gain experience. 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.

    NGBs, of course, can't make investment happen but they can shape the environment within which their programs are conducted. The Canadian Long-Term Athlete Development (LTAD) model and the American Development Model (ADM) both offer frameworks that NGBs can adapt to their own sports. Long-term participation is a key factor in both of these models and, if thoughtfully implemented, they can have a positive effect on retention rates.

    Just like restaurants and airlines, NGBs want their athlete-customers to return. They want athletes to enjoy the sport and continue their participation year after year. This means creating an environment where athletes leave practices with a smile on their face and looking forward to coming back the next day.

    Losing an athlete often means losing money for the coach, club, or NGB. But the sport also loses experience when youngsters quit.

    Annual athlete turnover in youth sport is certainly not news. NGBs that lose significant numbers of athletes each year may be able to replace them with new athletes the following year. While this churning of membership numbers may delay financial problems it masks significant reduction of average training age.

    When dealing with retention and training age it's easy to get lost in the numbers and lose sight of what they mean. NGBs with flat or decreasing retention rates are losing experienced athletes.

    When a youngster joins a sport for the first time he has a training age of zero, just like a newborn baby. When he has been in the sport for a year his training age becomes, you guessed it, one. But along with that training age of one he also has a full year's experience in the sport; experience that is worth hanging on to, experience that is valuable not only to the athlete but to the club, NGB, and the sport overall. It might be intangible but it has long-term value.

    If our 1-training-year-old athlete quits the sport and is replaced by a new athlete (with zero experience) we keep the numbers but lose the experience. Think about what that means over time as the constant diminishing of experience spreads throughout the NGB.

    High membership growth and low retention rates often mask low training age. Membership growth is easy to see and report. Retention is difficult to calculate and understand, and is rarely reported, if it ever is. So analysis of these numbers should be reported routinely as with growth and renewal rates and all administrators should be familiar with these important metrics.

    Retention is also an issue when discussing early- and late-maturing athletes but I plan to examine this in a later newsletter.

    How is retention calculated?

    The NGBs I communicated with before writing this article tracked membership renewal but not actual retention. A renewal rate reports how many athletes renewed their membership in the NGB for another year. It's a good business statistic but it's not really retention and doesn't offer much information about the athlete pool.

    Measuring retention by registration cohort counts the number of athletes in each cohort and how long they've been involved. This would yield 1-year, 2-year, 3-year, etc. rate for each new group of athletes. Calculating this rate over a period of 3 to 5 years makes sense. Once past the 5-year mark the metric loses relevance because athletes are invested by then or they've already left the sport. More on this in a moment.

    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%. Figure 1 also shows a 2-year rate of 58% and so on until we reach a 5-year retention rate of 29%.

    Each NGB should decide how long to measure annual retention keeping in mind that the goal of tracking it in the first place is to hang on to athletes to where they develop their own internal motivations for participating. In the Figure 1 example the period is five years but that's just because our software produces this report automatically. In reality three years is probably enough.

    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 15 year age range, maybe up to 18 years in some sports.

    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.

    Looking at retention in this way helps answer questions like this:

    • What registration age is the most common for athletes to drop out of the sport?

      In Figure 2 athletes who joined when they were 7-years-old had the best 5-year retention rate. Two possible reasons for this outcome immediately come to mind:

      First, 7-years-old may be the perfect age to begin parkour since it looks like it may be easier to hold on to very young traceurs. Second, extra efforts can be made to specifically target the 8- and 9-year-old sub-cohorts when designing retention strategies.

    • Are there anomalies that exist between retention characteristics of different ages?

      An example of something that might cause this would be offering the same type of program for different ages. Practices designed for 14-year-olds are not likely to be appropriate for 8-year-olds. The result of this will eventually appear in the retention rates for the sub-cohorts.

    What do the numbers mean? That is the real question!

    Only after several years of calculating cohort retention will an NGB be able to decide what their rate is and how they might improve it. If an NGB already has a registration system in place then retention can be calculated retroactively.

    The take-away here is that NGBs should know what their cohort retention rate is so that they can monitor and develop their athlete pool. Athlete and sport development is a management problem so ending with Peter Drucker's famous quote regarding business management is appropriate, If you can't measure it, you can't improve it.


    Bill Price (price@sportkid.asia) is the owner and Chief Data Scientist at Sportkid Metrics.

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