Top Servers in the Big Ten

servetop.jpg

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 replacement) to compare players’ values against that of an average MLB player. That stat has of course evolved over the years with different measurements for position players and pitchers, but the underlying principle has remained constant.

Looking at volleyball, there are 6 (7 if you count freeball passing) discrete skills so a single skill WAR metric makes a little less sense, but the general philosophy can be applied as a way to compare performance against league expectancies.

So in the above viz, I’ve used the league average PS Eff for each of the receive qualities. Which looks like this table below:

Screen Shot 2017-03-11 at 4.12.43 PM

Service Ace on the top, working down to service error at the bottom. And yes. Service ace should absolutely be at 1.0 and I’m not sure why it isn’t, but .998 and 1.0 are pretty darn close for our purposes at the moment.

Using these numbers, we then look at the frequencies a player served and got each of these specific outcomes. Multiply frequencies by efficiencies, add them up, and divide by the number of serve attempts and voilà!!

I’ve built this viz to again look at the relationship to service error percentage (while highlighting the top servers). You’ll notice there’s a slight negative relationship between effective serving and lower service error, but it’s not definite. Especially when looking at the servers who bring the most value, there’s certainly a range of error in that group – and almost a correlation of 0 if you draw a box between SSS, Davis, Swackenberg, and Kranda.

However in a general sense, you can assess the value each server brings to the table based on what her results are worth against the league average. In this case, Kranda comes out on top as giving you the best shot to point score.

Clever folks might be wondering what her breakdown looks like in terms of percentages of each outcome. So voilà again!

Book1

^ Here are the top 4 servers’ breakdown by each of the outcomes.

What you’ll notice is that they all have a unique footprint. Kranda makes her money by serving aces (around 14%) whereas SSS lives in the consistently good realm. SSS only misses 2% of her serves. That’s a huge deal. She keeps consistent pressure and even though her sum total of ok+good+perfect passes is higher than the others, she doesn’t give up free points, which results in her being the 3rd best server in the Big Ten in 2016.

I’m just starting to look at the data from a “what’s it worth relative to the league” type of standpoint, so I’ll likely have more posts like this soon. Previously, I’ve focused more on “what’s a player worth to her team” and specifically “what’s a player worth to her team, in this context, when playing opponent X.” I think the way I’ve approached this previously has merit, especially since we don’t have a marketplace for trading players like professional teams do – but you could easily evaluate All-Americans and other interesting things by comparing players to league data.

 

Advertisements