So I got a message a couple months ago and 100% failed to respond, so I’m trying to do it some justice now. The question is about FBSO Efficiency, Passer Ratings, and Winning.
*Because the question was in reference to passing, I eliminated missed serves from the analysis.
So here are the 2017 numbers for the Big10 and Pac12 (only looking at matches in which both teams were from one of those two conferences). They’re sorted by their opponents’ average passer rating. So you’ll notice Maryland, Northwestern, and Indiana all get their opponents in a little trouble, but because these teams struggle to capitalize on these advantageous situations, their opponents still FBSO at a pretty high efficiency, dropping them deep into the red on the right side chart.
UCLA is on the other side of the coin – they don’t serve particularly tough, but their block/defense prowess holds opponents to a pretty decent 0.136 FBSO Eff. Nebraska and Stanford both serve tough, but also slow opponents with large blocks and scrappy defense, allowing them to rise into the top 2 of both statistics.
I would partially disagree with our VT friend that there is bias in evaluation of passer ratings. Typically yes, if you were to compare between multiple coaches who are charting the same 20 passers, you’d like end up with some different numbers – but because I’m using the VolleyMetrics codes for all these matches, we can assume a decent level of consistency.
The inherent reason to dislike passer rating is because as previously stated in many many posts here, the change in how likely your team is to win the point as you move from a 3 pass to a 2 pass to a 1 pass is not equidistance. Let’s just take FBSO. You might kill the ball at a 50% rate off a 3 pass, but only 38% on a 2 pass, and only a 10% chance on a 1 pass. If we assume the 3 to 2 to 1 relationship is linear, we reward sporadic passers who may average a 2.0, but with passes of 3, 1, 3, 1, 3, 1, 3, 1. We’d much prefer a passer who always just passes a dead 2. Never 3s. Never 1s. Because once you look at the value of each pass in terms of winning the point, the equation becomes much more clear.
Just a quick rundown on VolleyMetrics: R# is a perfect pass, R+ is very good, within 10 foot line, R! is a 2 pass, R- is a 1 pass, R/ means you didn’t get a swing (either you freeballed it or may have overpassed it), R= means you got aced.
Here’s the equivalent chart for the 2018 men (using only matches when two teams in this chart played each other).
Very similar to UCLA on the women’s side, Long Beach isn’t even the toughest serving team in terms of getting opposing passers in trouble, yet they easily limit opponents to the lowest FBSO Efficiency out of the Top 10 teams – likely due to their block & defense.
If you were to run correlations on a per set and per match basis, you’d see strikingly similar results for both the 2017 women and 2018 men. The correlation between FBSO Eff in your team’s serve receive and your team’s likelihood of winning the set is 0.49. The rises to 0.59 when you look at the likelihood of winning the match.
While you may think the goal numbers are inherently different between the genders, for women, the top 5 teams in terms of FBSO Eff were Nebraska (0.274), Stanford (0.266), Penn State (0.265), Minnesota (0.255), and Wisconsin (0.238) – and on the men’s side it was Long Beach (0.278), Ohio State (0.257), UCLA (0.248), BYU (0.242), and Loyola (0.238). Pretty consistent between the two.