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 [...]

Efficiency Change Refresher

So here's the concept: we want to evaluate each touch by the difference between expectations and results. Input Contact: this serves as the expectation - given the situation you've been dealt, how well do we expect you to do? Output Contact: this serves as the result - looking at both terminal & non-terminal results Serving, [...]

Create & Terminate

*blue is won matches, orange is lost matches - matchid is chronolnogical from start (1) to end of season (39)* So the other evening, I was starting to draw up my first practice of the 2019-2020 season for the Bay 16-1s. It's a team that has great potential, some fantastic athletes, good height, and just [...]

Harker – Serve/Rec/Atk Efficiency

Because I'm on a roll with the R Shiny web app stuff, I figured I'd make another. This one allows you to look at how each player is trending throughout the season in their serve, receive, or attacking stats. Harker - Serve/Rec/Atk Efficiency!! For serving, we look at the outcome of the serve (different reception [...]

Harker – Attacking Effect Size

So. Made my first Shiny web app using R and feeling pretty good right now. It's not sexy by any means - and really only displays 4 different plots that are pre-made, but it's still super cool compared to the absolutely nothing I had built before this. You can check it out by clicking here: Harker [...]