[Cleveland Steam Whistle]

Question, is that 73% success rate the rate at which Corsi can predict the outcome of a game or season based on whatever feeds into it? I honestly don't know.

The reason I ask, is if that's the case, using Corsi success % or ratio's to figure out what's going to happen in the last 10 games is useless at this point. Because that same Corsi ratio would have suggested that the Flames would not be in the picture at this point. Meaning essentially, the Flames have overcome their Corsi over the course of 73 games, or said another way, Corsi has proven over the course of 73 games not to be a good predictor or outcome when it comes to the Flames, so there is no reason to believe that it would start to be applicable in the last 10.

Again, not sure I'm understanding the predictability ratio right, but that would be my thoughts.

I'm assuming the 73% is the confidence ratio at which Corsi can be deemed accurate or able to predict? If so, then that is the answer to this whole Corsi controversy crap. 73% is a fantastic directional predictor of outcome ratio. Meaning, if you were a gambling man, and wanted to predict the final standings of an NHL season at the start of said season, you'd likely get 73% of your prediction right. Can't really beat that predictability, in that regards.

But, from the perspective of statistical reliability, an essentially 30% error rate is terrible. It means that there are enough variants, issues or exceptions for the system that 30% of the time it doesn't apply. That's a huge number that simply can't be explained away as a "statistical anomaly". Which means, the Flames bad Corsi ratings aren't as likely to "catch up with them" as many would have you believe. Even a +/- 5% error margin wouldn't give you much hope other than to say that the Flames were defying odds this year with their record, and statistically it's bound to catch up with them eventually and they are going to pull a Colorado or Toronto. But a +/-30% error margin means something different. While it's still like the "best analysis tool" we have to try and predict with, it also means that there are enough fundamental flaws, or impactful details to outcome of games that the model doesn't capture that could be explaining the variance from the model. It doesn't have to just be a statistical anomaly that WILL even out over time, it could very realistically be that the team (in this case the Flames) are winning in ways that are sustainable but not captured by the model.

Anyway, Flames fans will obviously hope that the Flames success is due to them doing things not capture in the model (i.e. the 30% of error), while Flames detractors will hope the Flames actually should be falling into the 73%, but are part of a normal margin of error that that will eventually even out.

Wow, long ramble that I don't even know if I understand after reading it, but too much time spend now, I'm posting.