Throws Program Rankings – Post 2021 Indoors

Here is a full ranking list of all collegiate throws programs after the 2021 indoor season, including all divisions (NCAA DI, DII, DIII, NAIA, and NJCAA). This ranking is based on the methodology first used by “The Throwers Page” and was used to generate rankings through the 2018 season. You should be able to scroll through the list as well as sort and filter the various columns.

This is based on the same methodology that was used by “The Throwers Page” and is explained in full here: http://throwerspage.125mb.com/stats/rankmethod.php

I followed the same methodology. First, each performance in each event is scored, and then those scores are summed together to get a total for each school. The performances are scored by using a logistic function 100/(1+EXP((m–x)/c)) where:

m – the mean of the top 10 and the top 1000 collegiate performances in that event

c – 1/5 of the difference between the average of the top 10 and the top 1000 performances in that event

x – the mark, in meters

Here are the values used for m and c for each of the events in the indoor 2021 season:

Here are the point distributions for each of the events. The Y-axis represents points, and the X-axis represents the performance in meters:

Because these current distribution curves provide many points for performances in the mid-range, the original parameters used by The Thrower’s Page rewards programs that have good depth. I constructed an alternative ranking based on the same formula, but using slightly different parameters, specifically I changed m to be the mean of the top 10 and the top 100 collegiate performances in that event, and I changed c to be 1/5 of the difference between the average of the top 10 and the top 100 performances in that event. The following are the rankings that what I would call the “National Level” rankings that reward top-end performances more than depth:

And here are the values used for m and c for the “National Level” ranking:

As well as the point distributions for each event. You can see that the distributions are skewed much more to the right, and reward the top performances much more than mid-level performances.