What is the best measurement when it comes to athletic talent and potential? On-field sport performance is one important variable we can measure, and the results witnessed are, in fact, a true measurement of performance for that particular game. So whether you just had a great game — or bad game — both experiences provide insight to athletic potential, and even suggest a range of what one might reasonably fall within on any given day. So, in essence, you really are as good as that great game yesterday, and you are also as average (or below average) on your toughest day. Yes, both measurements are true measurements, and both can be used in very unique ways in order to experience future success.
How good are you?
So, was that last great game a true reflection of your talent, or are you more similar to your toughest days? One way to understand human performance is to learn about how we, over time, play to our average. Put another way, regression to the mean is the phenomenon that occurs when data is extreme compared to an average benchmark previously observed, and the subsequent expectation is that future data collected will “regress,” or return to the previous mean (or average). Below are a few examples of regression to the mean:
- If your average score in math is around an 80%, and you then score a 55% on an exam, we can reasonably expect that your future math scores will regress back toward your average score. In other words, it is statistically more likely you will score near an 80 on future exams than you will a 55% or lower.
- If you are an established baseball player who hits at a .300 average but are in the middle of hitting below .100 over the last week, we would reasonably expect that in the next couple weeks your average will naturally climb closer to .300. Interestingly, this phenomena also works the other way — if you are a .300 hitter that is hitting over .500 for the last week, odds are you will soon be hitting below .500 and closer to your benchmark average of around .300
Regression toward the mean is not an exact science, but what we have learned is that over time human performances tend to cluster around average scores unique to the individual. Practically speaking, this means you shouldn’t sulk too much on those really bad days — but you might also want to place those super-great performances in proper perspective, too.
Probably the best takeaway from learning about the regression toward the mean is that athletes should not get too high on their best days, nor too low on their worst days. The danger in getting caught up in atypical performances is twofold; by using a great performance as an assumption of a normal performance the result can be over-confidence, while believing you really are the talent of your worst performance the risk is experiencing more unnecessary stress, and possibly quitting the sport prematurely. Enjoy the great days, but take them more as an anomaly, and quickly let go of the bad days rather than using them as evidence that you just aren’t very good.
Statistics can sometimes feel overwhelming, but applying the regression toward the mean is a relatively simple way to understand your average ability doing a specific task. Keep track of objective measurements of your performance, and over time you will see averages emerge that are important to use as a base score when dealing with unusually high or low performances. By keeping things in check, focus, motivation, confidence, and resiliency improve, all leading to playing your best.