step 4 – passer ratings

So. Where do we start? We know that passing is important, but does it predict the future? Man...I hope so. That would save me some steps. 0.5 Just for reference, I've created a passer rating in the data that's built as follows: Top to bottom: perfect, pretty good, medium, poor, no attack/overpass, error 1. Let's [...]

step 3: attack efficiency

The short answer is, no, attack efficiency doesn't help us predict the future either. (However, it does help explain the past). Let's follow the same steps we used for PS% and see why. 1. Find the attack efficiency average for each team 2. Grab all the different sets that were played + the two teams [...]

step 2: point score %

Unfortunately, just knowing the average point score % for two opponents doesn't really predict who will win the set. I honestly thought it would...or that it would fair better than it did. Here's what I did: 1. Find the point score % average for every team in the dataset 2. Set up all the matchups [...]

step 1: what’s the point?

Predicting the future is difficult. People get the future wrong all the time. Coaches miss on recruits, GMs miss on draft picks, and bettors lose money. So are they just horrible at prediction? or is prediction really difficult? You'd think with the resources of big franchises, clubs, etc - coupled with the embarrassing ramifications of [...]