I bring this up time to time, but in the early 90s Bill James simulated thousands of baseball seasons for players. It was the first time anything like that had been done. Wade Boggs results were interesting.
A few thousand Wade Boggs hit as high as .400 but as low as .250 indicating that the real Wade Boggs 1992 could have been fluke.
Say you have a process that results in a 'positive' 3 times out of 10. Then you draw 500 of them. Then you do 10000 500 sample trials.
What is the highest and lowest number of positives you can expect to get? The variation is pretty high.
So the question is, in real baseball, a few hundred mlb players a year with significant playing time, many years, there will be natural variation producing outliers.
Are the number of outlier seasons, good and bad, more than expected by statistics considering aging curves?
Almost certainly yes. A lot of it probably caused injury.
If you could factor out the randomness and injury is there another level of unexpected variation caused by an unknown factor?
The unknown factor could be cheating (PEDs, sign stealing) or legal enhancement (legal nutrition/sleep hacks, good hitting tips, tells on pitchers) ?
It is these unknown factors, whether they exist and which teams and players are taking advantage of them that is the great mystery to us casual fans.