Father time is undefeated. In all athletic endeavors, as players age their skills diminish. This diminishment can be quantified in what’s called an aging curve (see figures below for examples and more details will be provided in the stats glossary).

I explored the aging of PDGA player ratings for the MPO division and found that it can best be explained when splitting players into three groups or types: stars, grinders, and also-rans. Predictions for the ratings of each player type can be found in the first plot below. Statistics for the three player type groups are given in the Player Type Statistics figure. 

The three player types  have a clear set of delineating statistical patterns. The “stars” are set apart in their throwing stats, while the “grinders” are pretty good at everything. The “also-rans” are decent putters but struggle getting to the green in regulation.

There are a few patterns in the aging curves to note. It is not so surprising that there is a gradient of peak rating expectations with the “stars” having the highest expected value. What is surprising is that there doesn’t seem to be a significant difference in ratings when the players are young. What really differentiates the groups is the rate at which their rating increases. The “stars” player type rating increases at a much higher rate than the other groups. The “stars” also seem to have the most significant regression in performance as they age.

You should also notice that there are a set of curves that control for survivor bias. These curves more accurately reflect the influence of aging on player rating, so I included them. However, they are less predictive.

See the glossary for more details.