Here’s just a quick snapshot of Eff Change taken from a late September match between UCLA and USC this season.
I’ve explained the idea behind Eff Change in a couple posts but figured I’d throw it out in a Pac 12 post for fun. The idea plays off the FBSO and Service Error concept that different teams have different strengths/weaknesses. I don’t know enough about the Pac 12 to generalize, but let’s say USC is a stellar offensive team, but they struggle to dig balls. With that idea in mind, getting a stuff block against USC – or perhaps serving them out of their in-system offense might be incredibly valuable, given their offensive strength. But on the flip side, if USC is a team lacking great ball control defenders, then maybe failing to rack up kills against them is pretty bad, seeing how USC already has a lower defensive baseline in this example.
You should go read the original post about Eff Change if you haven’t since it explains in more detail how all of this is calculated…but the idea is that you account for the two teams that are playing – as well as the specific context within the rally (good block touch, perfect dig, poor reception, etc). So you look at both in the input and output contacts. For an attacker, you look at the pass or dig that precedes the attack as the input – and the output is the block touch, kill, error, or dig quality that follows the attack. You then subtract the efficiency of the output from the initial efficiency of the input to create Eff Change. So if you have an input of a poor reception (maybe that input eff is 0.100 since it’s tough to score with that pass quality) but you take that and tool the block for a kill (a kill has an output eff of 1.00 because that team always wins the rally). So you started at 0.100 and ended with 1.00; so that 1-0.1 for an Eff Change of .900. This is a big deal since you started with a weak position and improved the outcome drastically. That’s the gist of Eff Change.
For some of the touches in that above UCLA/USC match, you’ll notice that Eff Change is actually above 1 and below -1 for some touches. So for Frager’s ace, UCLA is actually expected to lose with that input contact more often than not. So UCLA starts with an Input Eff of -0.247 (not surprising as the receiving team is almost always favored) but because she serves an ace (Output Eff of 1.00) her net Eff Change is actually over 1.
Anyway, just some stuff to think about for those who haven’t cruised through all the posts. Let me know what you think / if you have questions. I can talk about this stuff all day.