Thesis Proposal (set 8: prior pre-decision probability)

If this frame looks similar it's because we are again utilizing Bayes' rule, but this time it is with the posterior as the PRE-DECISION odds of team C winning the game given the game-state, which is shown on the left-hand side of the equation.

On the right-hand side we again have the prior and conditional likelihood (original and new information). The first term is literally the prior (pre-game) odds of team C winning the game while the second term is the odds of team C being in that game-state given that they ended up winning the game.

The next step is to calculate these two components. Down here you can see that to estimate the first component (the prior) we will be using a logistic regression to predict game outcomes from closing point spreads.

For the second component we will use a multinomial logistic regression to predict the probability of the team being in that situation given that they won the game. In this case X-Prime represents the group of variables that make up the game-state: the score margin, time remaining in the game, field position with respect to the offensive team, current down, yards to go to gain a new set of downs, and an indicator variable for possession with respect to the home team.

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