Week 6

 

This week I worked on a model to apply to last season's playoffs in order to see how its predictions compared to the actual outcomes of the first round of playoff play. The model that I was assigned used different parameters to determine expected goals (xG) for teams depending on whether they were hosting the match or were the visiting team. For the 6 home teams in the first round of the playoffs, the model only considered goals scored while playing at home throughout the regular season for its xG calculations. For the 6 visiting teams, the model only considered the goals scored in away games that season to calculate xG. This model accurately predicted the result for four of the six matches in the first round of the playoffs. It should be interesting to see how the models from the rest of the group performed.

This week, Dr. Posta tasked me with an additional model that only takes the results of the last two games of the regular season for each of the 12 playoff teams in the first round. It seems like a very small sample size, but it should be interesting to see if only using the results of the last two games might best represent a team's current form heading into the playoffs. Particularly for teams that might have gotten off to a slow start but came into form late in the season. We’ll see how this model pans out.

Additionally, this upcoming week we are also going to be calculating both the binomial deviance and squared error for our predictions of the first round, in order to help us determine what the best model will be for us to use as we aim to predict this year's playoffs.

 

 


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