Originally Posted by
suicidekings
The simple solution is that not every matchup of Team A @ Team B is equivalent. In a sport like the NHL, momentum means a lot, and there are numerous factors that are much harder to quantify accurately.
Team defensive breakdowns leading to excessive screened shots, elite scorers on hot streaks, teams experimenting by shuffling of offensive lines from game to game and therefore disrupting chemistry, nagging injuries of the starting goalie on a team with a weak backup, a couple of dirty goals early in the game throwing the team out of rhythm, specific matchup issues related to the teams' differences in size/speed, etc.
Depending on the data you're inputting, you probably are missing key information, even in the games where you don't notice the discrepancy in the model output. Maybe a 7-2 loss started off as a 4-0 deficit a few minutes into the game, but the gameplay over the remaining 50+ minutes was much closer than the final score indicates.
Does your model attempt to assess a team's current form (ie: last 5/10 games)? Or simply its overall rating at a given point?