How come nobody talks about regression to the mean when a good shooter is in a slump? My favorite non-regression to the mean example is Neils Giffey. No way a career 34% shooter is going to shoot almost 50% the entire season. Yeah, he is. Including the title game.
In many games of skill plus a chance element, most people do not realize what an adequate sample size truly is for what they are looking at. It's nearly always larger than what they may think.
For example poker is a game of skill that also has a significant element of chance. Skilled players will be winners in the long term. Yet horrible players can win money for longer periods than what you might think,..and great players can & will lose money over ridiculous sample sizes due to variance/luck.
There are some really nice elegant examples you can find online that show that you literally need to play hundreds of thousands of hands of poker (some argue millions) to prove with high statistical rigor/confidence that you are a winning player.
You get dealt about 30 hands per hour in live poker. It can take literally years of playing for you to state with confidence you are a winning player.
For 3pt shooting, let's say someone shoots 37.5% over a season of 250 attempts. The range of "true" 3pt shooting ability for that player using a 95% confidence interval is between 33-43% for any given 250-shot sample size season.