Monday, October 1, 2007

Overview of Hitting Percentage

For my next few postings, I would like to provide initial examinations of the major volleyball statistics, to try to get a feel for them. Let's start with hitting percentage (also called attack percentage), which can be computed for either individual players or teams.

For a player or a team, one totals the number of kills (i.e., successfully putting the ball away on an attempted attack), then subtracts the number of hitting errors (e.g., attack attempts hit out of bounds or into the net, or that get blocked back into the hitter's face for an opponent's point). The remaining number is then divided by total attack attempts. These terms are defined rigorously on this document from the American Volleyball Coaches Association.

Imagine the following different hypothetical performances. One player, whom we might call "Dana Devastator" has the ball set up for her 10 times and successfully puts it away all 10 times. That would be a 1.000 performance ([10-0]/10). Another player, "Patty Powerless," might be set up for 7 attempts, but only once get a successful kill, her other 6 spikes being fielded by the other team. That would yield a percentage of .143 ([1-0]/7). Then there's "Erin Erratic," who twice scores a kill on her 8 attempts, but also blasts the ball out of bounds 4 times. Because this player has done more harm than good, her hitting percentage enters negative territory, namely -.250 ([2-4]/8).

The hitting percentage formulation, which has been around as long as I can remember, is something I like. The ultimate goal of a team is to win games and matches, which requires getting points for one's own team and denying points to the opponent. Hitting percentage essentially weighs a player or team's balance between kills, which by definition result in points, and hitting errors, which lose you points. Poor efficiency, in terms of hitting a lot of balls that can be played by the opponent, serves to dilute a player or team's percentage.

Viewed from this perspective, it is not surprising that there is tremendous overlap between the nation's "best" NCAA Division I women's teams (as per the September 24 CSTV/AVCA Poll) and the top teams in hitting percentage (as of September 23). As I'll discuss in future postings, other NCAA statistics do not dovetail so well with the poll rankings.

Shown below for the top 10 poll-ranked teams are (left to right) their poll ranking, hitting percentage, and hitting percentage rank:

Nebraska____ 1 __ .338 __ 3

Stanford____ 2 __ .316 __ 4

Penn St.____ 3 __ .347 __ 1

USC_________ 4 __ .287 __ 12

UCLA________ 5 __ .255 __ 37

Florida_____ 6 __ .292 __ 10

Texas_______ 7 __ .298 __ 7

Washington__ 8 __ .341 __ 2

Wisconsin___ 9 __ .284 __ 13

California__ 10 _ .298 __ 6

As can be seen, 9 of the top 10 poll-ranked teams are in the top 13 of team hitting percentage. From the opposite perspective, 7 of the top 10 hitting-percentage teams are in the top 10 of the poll rankings.

There are some anomalies, though. UCLA, ranked as the nation's fifth-best team in the poll, is only 37th in hitting percentage. Texas A&M, on the other hand, ranks 9th in hitting percentage (.293), but is unranked in the poll (not only are the Aggies absent from the top 25, but they're not even among the additional 13 teams receiving some votes to be in the top 25).

9 comments:

Anonymous said...

this is very highly developed in europe. in fact there is yahoo group called "volleystats" that you would probably enjoy. It's leader is a guy named Leo Van Hal. I can put you in touch if you would like. Leo studies european leagues and international tournaments.

I sometimes struggle with the advanced (at least to me) math Leo uses in his stats. I hope that maybe you will be able to explain some of his stuff to me better than he can!

Anonymous said...

Hitting Percentage does tell a story...however, it is not a complete story!

One of the things we've done is graph our hitters hitting % versus the opponents raw pablo score....it helps to show (to the players) that they need to step up against the better competition, as well as give our setters an idea of who needs sets at critical times.....

Anonymous said...

One of the things we've done is graph our hitters hitting % versus the opponents raw pablo score

I think this is one important difference that you will run into as compared to baseball analysis. When doing analysis of MLB, differences in schedule strength are not very important. However, in NCAA volleyball, it is exceedingly important because there is huge variation (I suggest that is why A&M's hitting pct is so far out of line - quality of the competition).

BTW, speaking of such, it might make more sense to discuss results in light of Pablo rankings, as opposed to the AVCA.

Anonymous said...

Great site. I am a former Div I VB player and coach, and also a math major. Carl McGown of BYU has done extensive statistics on the game of volleyball similar to those of Moneyball. He and some other top volleyball coaches have a company called Gold Medal Squared that does coaching clinics about their statistics.

Anonymous said...

The comment about Carl McGowan highlights a big concern I would have about any attempts that fans might have at statistical analysis. Trying to evaluate volleyball based on the standard box score is kind of like trying to evaluate baseball based on the old time box scores that included only AB, H, R, RBI, and if you were lucky, HR. I'm guessing that one of the things McGowan is going to say in the workshop is that you need to track a lot more information than what is in the official stats. For example, start with a rotation analysis.

Even when data got better for baseball, there were still gaps for things like walks. Until Project Scoresheet came along, a lot of data was hard to come by.

Full PBPs will help when it comes to volleyball analysis, but they are not always available. And even if they are, they aren't perfect, although they do provide a lot more information than can be obtained just from the box score.

Anonymous said...

I wish that the output from some of the hand held programs was a bit more descriptive.....or easier to use.

I'm collecting all the data I want (points per rotation, our passing, first ball kills, etc), but in order to get it out of the program we use, I have to do a lot of excel conversion......

anybody have any ideas? (btw, I'm the Anonymous poster from above).

Do we have objective ratings of the various handheld software somewhere? (I'm using digital scout, have demoed vbace, what else is out there?)

Anonymous said...

Well articulated.
I would like to see an even greater refinement of the hitting percentage stat that encompasses all points scored (i.e., kills + solo blocks + block assists [times 1/2, of course] + and aces) minus all errors committed (i.e., kill errors + serving errors + blocking errors + and ball handling errors).
These statistics show actions that lead directly to a gain or loss of point. Then, divide this number by the number of games. I would refer to this statistic as "scoring efficiency."

My on-the-fly calculations indicate that the best player on most teams has a scoring efficiency per game of between 2.0 and 2.5. Outstanding players hit above 3.0 and there are a few that hit above 4.0 per game.

I prefer this statistic over hitting percentage because it shows the real impact a player has on points actually scored or lost. Good players do not give away hard-earned points in other areas. For example, a great hitter with many kills could give away points on serves or blocks. Some hitters are not allowed to serve by the coach (for various reasons), and this would not hurt or help a player's scoring efficiency. --JF

Unknown said...

Could I have Leo Van Hal’s contact information? I have a question about how hitting percentages are calculated that I hope he could help me with. It makes no mathematical sense to me why errors are subtracted from kills. They don’t really have that relationship to me. They are both subsets of the same whole but that does not mean that the errors took away from the total number of kills. It looks to me like the errors would be subtracted from the attempts before the kills are divided by the attempts to get the hitting percentage, not subtracted from the number of successful kills. I need someone to explain to me why it is done the way that it currently is done. Say someone has 225 attempts, successfullly has 65 kills, has 63 errors, and the zero attack number is 97. The percentages should be calculated as 65/225 giving .289 kill efficiency, 63/225 giving .28 error percentage, and zero attack 97/225 giving .431 zero attack percentage. If we want to account for the errors why wouldn’t it subtract from the total attempts instead of the kills before computation? 225-63=162. Then 65/162=.401 kill percentage, 97/162=.599 zero attack percentage? The errors are just xtra effort with no point for attacking team. I like just the total better. It seems a better way to calc these stats and I don’t understand what good it does to subtract errors from kills.

alan said...

Kills earn your team a point and hitting errors cost your team a point. Hence, K - E (if positive) is the number of points you're benefiting your team overall. If you get 8 kills, but make 3 hitting errors, you're earning 8 points for your team, but giving the opponents 3, for a net gain of 5. Of course, if K - E is negative, you're giving away more points to your opponent than earning for your own team. Hope this helps.

2023 NCAA Women's Preview

Sixth-four teams are alive at the moment, but it sure looks like Nebraska (28-1) and Wisconsin (26-3) will meet for a third time this season...