According to AVCA guidelines, blocks "are awarded when a player blocks the ball to the opposition's court leading directly to a point without a successful dig." As elaborated in the guidelines, blocks are credited as solo or assist, according to certain criteria. Also, the hitter who is blocked in the manner described above receives an attack error.
A dig "is awarded when a defensive player keeps a bona fide attack in play with a pass."
The central inquiry motivating this blog, of course, is what can be learned through measurement and statistics that tells us about winning matches. Given the suggestion in an earlier posting that a team's hitting percentage seems to be a good marker for general success, it seems plausible that holding down opponents' hitting percentage might also be associated with winning.
Opponents' hitting percentage is not among the statistics displayed on the NCAA statistics page, but it is kept for four major women's volleyball conferences -- Big Ten, Big 12, Pac-10, and Southeastern Conference -- that I looked at recently (see links section on the right).
In looking at team-level defensive statistics, my interest was two-fold: first, what is the correlation (overlap) between teams' blocking and digging statistics and their opposition hitting percentages (OpHP); and second, how do these three variables relate to winning percentage?
I thus computed some correlation coefficients between the four variables, separately for each conference (the data were as of yesterday). To avoid discrepancies within a conference in schedule difficulty due to non-conference schedules, I used statistics only from within conference games. The sample size (number of teams) for each analysis is small, but the replication of results over the different conferences can be instructive.
A positive correlation simply means that both variables travel in the same direction -- as one goes up, so does the other. A negative correlation indicates an inverse or opposite relation -- as one variable goes up, the other goes down. One should not infer a "bad" connotation to the word "negative" in this context; positive and negative simply convey patterns of relationships. A positive correlation approaching its maximum of 1.00 and a negative correlation approaching its (absolute value) maximum of -1.00 each convey a powerful relationship.
The results are shown in the following table (which you can click to enlarge). I just cannot resist the graphical embellishments of PowerPoint!
An "official" block (as defined above) gives the opponent a hitting error; a block that does not immediately rocket to the floor for a defensive point, but is instead played by the original hitting team to prolong the rally also dilutes the opponent's hitting percentage by adding an attempt without a kill. I thus expected to see negative correlations between blocking and opponent hitting percentage (as one goes up, the other goes down). I didn't know how strong the relationship would be, however.
As shown in the above table, these correlations were quite strong, ranging from -.68 to -.87 in the four conferences (these were all statistically significant, even with the small sample sizes). Digs also detract from OpHP, but the correlations were only moderately negative, at best, and not statistically significant (i.e., not reliably different from zero).
How might digs and blocks be correlated? One might expect an inverse (negative) relation, as "airtight" blocking would preclude the need for digs. On the other hand, if a team has a high skill level in general, it should excel at both of these (and other) facets of the game, leading to positive correlations.
In fact, these correlations ranged from moderately negative to moderately positive, with none significant. The one negative correlation, for the Big 10, may well stem from the fact that Michigan (my graduate school alma mater) was leading the conference in digs, but was last in blocks.
Next, for the second part of our inquiry, which defensive element -- OpHP, blocks, or digs -- is most strongly associated with conference winning percentages? In each conference, opponent hitting percentage edged blocks in absolute strength, but both were potent. OpHP is negatively related to own winning percentage because the lower the hitting percentage to which Team A holds Team B, the more likely Team A is to win. Blocks are positively related to winning, as higher numbers of blocks are associated with better winning percentages.
In doing my research to prepare for this entry, I came across two additional sources:
One is a study comparing two blocking strategies: "commit" vs. "read and react." According to this FIVB document:
Teams usually opt for a 'read and react' block (whereby they try to react to the ball leaving the setter's hands) or for a 'commit' block (whereby they decide before the point whether to jump on the quick middle balls).
In their article, "Relationship between the use of commit-block and the numbers of blockers and block effectiveness," researchers J. Afonso, I. Mesquita, and J.M. Palao analyzed four men's national teams in 2001. Quoting from the abstract of their article in the International Journal of Performance Analysis in Sport:
The results show that the use of the commit block [makes?] difficult the formation of double and triple blocks in the wings and does not increase the block effectiveness or the opponent's error in spike.
(As can be seen, a word was omitted from the original version of the online abstract. Based on context clues, my guess is that the word is "makes," but I've added the question mark to denote the uncertainty.)
The other source is an article from Gold Medal Squared by Carl McGown, a highly successful men's coach, on liberos' passing vs. digging. Like my four-conference analysis, the statistical analyses in McGown's article also highlight the uncertain role of digs in winning and losing.
3 comments:
Instead of looking at the correlation with digs, perhaps it might be better to consider "dig percentage" - which would be digs/(attacks - oppBlocks).
There is a good question about opportunities here that should apply to not only digs, but to blocks as well. Are all opportunities equal?
There was a comment on volleytalk about the Hawaii/Nebraska match where it was pointed out that, while Hawaii had more digs, Nebraska had a significantly higher dig %. I think it's worth considering.
I am intrigued by the relationship between number of blocks and number of digs. Initially, intuition told me that the correlation should be negative, for the reason that you expressed: a team which gets more blocks has fewer opportunities to dig an attack. However, as you said, a good blocking team may be a team which is strong in all defensive aspects, so one can't rule out a positive relationship. I would like to build on this last thought. A team which gets a lot of blocks may also touch a lot of attacks and slow the ball down, thus making the attack easier to dig. Even though these touches aren't recorded in the "blocks" column, they do have an impact on the ability of the team to dig a ball.
Alan - I know this is old news, but it is relevant.
Our VT discussion got me looking into digs a little more and I made an interesting discovery about dig correlations. The strongest correlation I found for digs was with ... opponents digs! Correlations (r values) for the Big Ten, Big 12, and Pac Ten were in the range .65 - .75, and the overall correlation for all three conferences is something like 0.77!
Ruffda pointed out that the way to get lots of digs is to have long rallies, and that means that both teams get lots of digs. That means a team like Penn St, who doesn't get dug very often, doesn't get a lot of chances to get digs of their own. As a result, they are near the bottom of the NCAA in digs/game ("292 out of 325"). Then again, they are at the TOP of the NCAA in terms of getting dug, and by a good amount (the closest team I have found so far allows 1 more dig/game).
From top to bottom, there is a difference of about 10 digs/game among D1. However, the difference between a team and its opponents is typically less than 3 (the max I have found is 3.3, and most are much less). So Penn St is near the bottom in D1, but their opponents are even less (and probably would be the bottom if they were a separate team). Similarly, whereas Chatanooga lead the country in digs at 22.6/game, their opponents, where they a separate team, would be second in the country at 21.5 or so, behind only Chatanooga.
Interesingly (at least for me ;)) is that there is basically NO correlation between Dig % (digs/(opp attacks - opp errors). Unfortunately, this is only really applicable at the team level, and I don't think it translates well to individuals. Perhaps the way to do that is by a WinShares-like approach?
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