To fill the void left by the NBA and NFL in the summer, I’ve decided to create a WNBA model to tide me over until the fall. I used the same framework as the NBA model, which finished the regular season +13.51u on a 53.9% win rate. I will start with one criterion games must meet to post a pick for:
- Games with a model/spread difference not within one standard deviation of the average difference (using NBA model average until I get a big enough sample size): The model cannot factor injuries into its calculations, so games that involve notable injuries often have predicted outcomes much different than the spread. Instead of trying to figure out how to incorporate injuries or which teams have significant injuries, we will just avoid any game in which the model’s outcome is more than one standard deviation different than the spread.
It will be interesting to see how this model performs. Using the same framework as the NBA model could be a mistake as the nature of the two leagues are completely different, but I believe it will transfer over decently well. I don’t believe I’ve watched a minute of WNBA basketball in my entire life, so I am by no means a trustworthy source. I just thought it would be interesting to take a stab at it during the summertime sports drought.