Although the traditional box scores might be lacking, using more advanced statistical programs like DataVolley or Volleymetrics can give us more insight into what happened on the blocking end.

Quite a few individuals see their blocking statistics change. For Texas, Butler was credited with 4.5 blocks (9 BAs, each worth 0.5 blocks) by the NCAA but 7 by Volleymetrics. On the flip side, Johnson dropped from 3.5 (7 BAs) to 3 and Gabriel and Eggleston dropped from 2 BAs each to 0. BYU also sees some similar changes based on who actually made the block on each play.

Where it really gets interesting is when blocking errors are factored in.

At first glance, one of the stories of this match was the blocking advantage Texas had. They outblocked BYU 15 to 8! (NCAA box score actually had Texas with 16 blocks, but it’s likely they counted a ball BYU attacked into the net as a block- that happens sometimes.)

However, look at the blocking error column. This includes the blocker being in the net, as well as the hitter tooling the block. Texas had 16 and BYU had 9. Now things don’t look so lopsided. In terms of a raw +/-, both teams gave up 1 more point via blocking error than they scored via stuff block.

We could also measure this in a ratio or efficiency rating, by dividing stuffs by tools. In this case, Texas was 15/16 = 0.94 and BYU was 8/9 = 0.89. I call this ratio blocking efficiency, stuff-to-tool ratio, or just, “Stuff to Tool.” This is a stat that few people use that automatically upgrades your understanding of blocking effectiveness, both on the individual and team level.

It’s reasonable to assume that stuff blocking correlates well with blocking efficiency, just as kill % correlates well with hitting efficiency. But just as some hitters are high kill and high error, some blockers are both high stuff and high tool. This statistic also helps us coach. Teach players that their number-one job as a blocker is to stuff the ball. But the next most important thing is to not give up an easy point by getting tooled! Understanding both sides of this equation makes blockers better.

This brings us back to another reason NOT to use block solos and block assists. Using the NCAA logic for assigning block assists to any blocker involved in the block, whether they touched the ball or not, we’d have to assign block errors to any block involved in the block, whether they touched the ball or not. This strikes most people as absurd, so why are we assigning block assists to both players when only one made the block?

To summarize:

Block assists are almost meaningless. The FIVB method of assigning the block only to the player who blocked the ball gives more accurate information. Both NCAA and FIVB statistics neglect at least half the story by only listing stuffs and not blocking errors. Blocking efficiency (stuff-to-tool ratio) gives us a much clearer picture of a team or individual’s blocking effectiveness than just stuff blocks.

In Part 2, we’ll look at how the GMS Stats App analyzes blocking, why it’s different than Volleymetrics, and what to do about all those pesky non-terminal block touches!