Quote:
Originally Posted by austin101123
> You're going to have to explain why it would be important to give everyone the same ratings when you're trying to test this. The whole point of linear regression is to extract the importance of each variable within the model.
> Yes, there are some events and ratings that are not linear
If the distribution of batting ratings isn't the same for LHBs and RHBs (and I don't see any reason to assume they have the same distribution), then you need to consider nonlinearity as well as interaction terms to say if LHB or RHB is actually overperforming or not.
|
Again, individual events like walk rate, home run rate and strikeout rate are non-linear. However, for those events it's just better to create a low and high model based on whether the player in question has a low/high rating in whatever tool mainly governs that event. I am not attempting to predict any of those. Simple linear regression is more than adequate for what I am attempting to do.
Also, if 22 is working as intended, why is 21 showing the exact opposite results?