Glen Sathers Cigar
Sather 4 Ever
Bolded is very true and most of the legitimate stat guys wholly understand this, even if they may weight their models a little heavier because of their own biases, they understand that there's context and subjectivity and stuff.The models themselves are also incredibly wrought with a subjective human opinion on how certain metrics should be weighted over others. And while I'd like to think those decisions when made initially were data-driven, they can still hold a ton of human error.
Long story short, if Patrick Kane garners a 3% WAR with us but is a PPG player on a Stanley Cup winning team, I'm not going to care one bit. Honestly, probably have the same reaction if he doesn't produce a single point. When push comes to shove, only one metric matters for a team - Stanley Cups.
I also say this as someone who had a stats emphasis in college and now works in Data Analytics, so this isn't an "old man yells at cloud" take. People simply overstate advanced analytics these days. They're way better than we used to have, but still nowhere close to what people think they are.
The problem is people who don't fully understand the models and what they're doing just taking their chart screenshots and being like blue good/red bad and that's that.
I saw someone on twitter posting a WAR chart and making a definitive statement about some player and someone responded with some context around the player and why charts like that aren't always entirely accurate for this player or whatever and the person who posted the chart was like "Um it's literally just factual data you can't argue against it!" Like the person doesn't even understand that what they're looking at is not raw data it's a model's interpretation of the data - a model can be using accurate data but be a flawed model, that's entirely possible.