Two years ago, I did a benchmarking study on the cross country data that was available at the time on milesplit. Back then, we only had freshman through senior data available for one class, the class of 2011. We now have freshman through senior data available for the classes of 2011, 2012, and 2013 (three times as much data). The additional data gives us more insight as to what can improve a cross country program’s chances of success.
Now let’s review what we learned two years ago, as those findings remain applicable. The “what’s old” comments below review the 2011 findings. The “what’s new” offers some confirmation and additional insight. We will elaborate on the what’s new in some follow-up articles.
Freshman Recruitment Rate
What’s old:
The most important factor was getting freshmen to join the team. The teams that had won the 2010 state championship had all gotten more freshman boys out for their team in 2007 than had any other team in their respective classifications. The winning teams had each gotten at least 5% of the freshman boys to join the team. Successful private schools had done even better than their public school counterparts, often achieving a 10%+ freshman recruitment rate.
What’s new:
The teams that recruit the most freshmen do not always win the state championship (their nets do not always contain enough big fish), but their chances are considerably better than those who recruit fewer freshmen.
Runner Development Rate
What’s old:
This was the second most important factor from the 2011 analysis. Successful programs will take 19:30 freshmen and have them approaching 16:00 by their senior seasons. Less successful programs may struggle to get those same 19:30 freshman under 18:00 in the ensuing three years.
What’s new:
Rather than only studying elite (sub-20:00) freshmen as I did two years ago, I studied all freshmen. This remains the second most important factor in determining a team’s success, but studying all runners does change the identity of the benchmarks here.
School size (within classification)
What’s old:
This is a metric that I should have studied two years ago but did not. It is logical that if the percent of freshmen recruited is important, the size of the freshman class would also be important.
What’s new:
The 2013 data confirms that the freshman class size is important. Of the 24 teams that reached the 2012 podium (excludes A-public), almost all of them were in the upper half of their classifications with respect to school size. My hat is off to Wesleyan, who placed second in AA in 2012 despite being one of the smallest AA schools.
Runner Retention Rate
What’s old:
Most programs retain about two thirds of their freshman runners through their junior years. Whereas there was enough data to detect a slight edge in this metric for the more successful programs, there was not enough data to detect one program that stood out amongst all of its peers.
What’s new:
One thing I did not notice two years ago is that (not surprisingly), the faster runners are more likely than slower runners to return for their sophomore and junior years. Once the data is normalized for individual speed, there is not much difference between the stronger and weaker programs. Unfortunately, the weaker teams have fewer fast runners to begin with, and the stronger teams can more easily afford the loss of some of their faster runners.
Sophomore Recruiting
What’s old:
Although there have been many excellent runners who began their cross country careers as sophomores (Tommy George, Alec Klassen and Stephen Spevacek come to mind), runners who begin as sophomores never quite catch up, on average, to those who began their cross country careers a year earlier. Whereas we understood this two years ago, there was not enough data to determine which programs were the best at sophomore recruiting or even to get a confirmation that the more successful programs outperformed the less successful programs in this area.
What’s new:
With the extra data we can now confirm (not surprisingly) that the in addition to doing a better job recruiting freshmen, the stronger programs also do a better job recruiting sophomores.
Why does cross country become a numbers game with school size and recruitment rates outweighing the other factors? The answer is quite simple. Note from the graphs below that the four teams are identical, on average, with each having a mean of 21 minutes and a standard deviation of three minutes. Note that the 72 man team only needs to use runners that are sub-17:30 in their top seven. By contrast, the 36 man team needs to use runners up to 18:45, and the 18 man team may have a 20:00+ runner in their top seven. The nine man team will have 20:00+ runners in its top five. They will be trounced by the 72 man team even though both teams are the same “on average”.