Pac12 Pass Rating and W/L Sets

B1G Pass Rating in W/L sets   Figured I would build a similar chart for the Pac12 from 2016. It includes all conference matches, not just the big ones. As with the Big 10 numbers, there are certainly some teams where pass rating doesn't necessarily differentiate won/lost sets. By including all sets however, this may... Continue Reading →

Big Ten Pass Rating in W/L sets

I'm not a huge fan of using pass ratings - I don't believe they accurately value different reception qualities. That being said, every single person ever uses pass ratings, so I decided to dive into it a little. In the above chart, pass ratings are valued on a 3 point scale (R# 3, + 2.5,... Continue Reading →

Receive Eff in Big Ten

Similar idea - just messing around with the ggjoy package in R. What you see above is the receive efficiency (basically passer ratings valued by Big Ten standards for FBSO eff). I filtered out a bunch of names that failed to consistently post high values - as well as those sets in which the passer... Continue Reading →

Point Scoring% in the Big Ten

Not a sexy topic, but I just figured out how to do these 'joy division' charts in R so I'm kinda pumped to share. What you see is a histogram of each team's point scoring % in every individual set they played (only against the teams you see listed, so Purdue v. OSU but not... Continue Reading →

Heatmap Intro

*the net is at the top. the endline is closest to this text In the land of cones and zones...and subzones, it's easy to forget that these are merely representations of locations on the court. Equipped with that logic - and sparked by our friends at VolleyMetrics - I converted the zones to xy coordinates.... Continue Reading →

Top Passers in the Big Ten

Here's the same type of viz I made earlier for servers. Just because I was curious who the best passers were, relative to the league average for FBSO value provided by each reception quality. What you may immediately notice is that Nebraska has 3 of the top 4 passers in Albrecht, JWO, and Rolfzen. So... Continue Reading →

Top Servers in the Big Ten

Coming back from the SSAC in Boston this past week, I've been putting more thought in player evaluation against the market they're situated in. Much like how baseball uses WAR (wins above┬áreplacement) to compare players' values against that of an average MLB player. That stat has of course evolved over the years with different measurements... Continue Reading →

Pac 12 – FBSO & Service Error

Welcome to the Pac 12. So here's the same FBSO vs. SE% graphic I built for the Big Ten. Looks pretty similar, with a loose, positive correlation between the two metrics. If you don't remember from the original post, these are the individual match performances of each team - meaning that UCLA in the bottom... Continue Reading →

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