Another pretty good result this week: \(36/52 = 69.2%\). Accuracy by spread is at right.

A quick note on accuracy as an evaluation metric: We actually predict significant fluctuations in performance of our model from week to week. If we estimate our prediction accuracy at 70%, then for a week with \(n\approx 50\) games we expect a distribution of accuracies from week to week with standard deviation given by the binomial distribution: \(\sigma = \sqrt{n p (1-p)}/n \approx 6.5%\). This is a rather broad distribution - we might expect results ranging from \(60%\) to \(80%\) to be quite common from week to week. For \(n \approx 15\) games (as in each row of our tables comparing by point spread), the standard deviation increases by a factor of \(\approx 2\).

We have a functioning visualization tool for our NBA content, but are still working on loading it up to our server. Expect that, and a post about our difficulties, to show up soon. Our week 6 predictions are now up.