I am hoping that I can ask this question the correct way. I have access to play-by-play data, so it's more of an issue with best approach and constructing the data properly.

What I am looking to do is to calculate the probability of winning an NHL game given the score and time remaining in regulation. I figure I could use a logistic regression, but I am not sure what the dataset should look like. Would I have multiple observations per game and for every slice of time I am interested in? Would I have one observation per game and fit seperate models per slice of time? Is logisitic regression even the right way to go?

Any help you can provide will be very much appreciated!

Best regards.