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I would say they are good at evaluating most teams, but this year’s Browns are actually a really unique outlier. They are the first team in NFL history for a lot of things, including the context around Freddie’s hire, Baker’s performance after Hue got fired, getting a receiver as talented as OBJ and pairing him with a young team, etc. Interestingly, I think last year’s Rams are a similar comparison, and the models also had them at 8-8 for comparable reasons.I know those weren't your analytics models, but my honest takeway from all this is that those models are hot garbage. Perhaps the reason for that is, as you say, that they're not good at accounting for context. But that just explains why they're hot garbage -- it doesn't actually make them better.
The thing is, ELO models generally are great at predicting the NFL season. Broadly speaking, historical teams like this year’s Browns - new coach, second year QB, below average offensive line, lots of roster overhaul, etc. - play below their expected points totals. Again, the problem is the Browns are a historically unique situation.
I was trying to do is explain why analytics models are projecting the Browns to go 8-8, and more importantly, why I think they are wrong. I think the models are projecting the Browns somewhere between 30-60 net points (or one to two wins) too low.