NBC Olympics Website for Volleyball Stats

The NBC Olympics website is now providing extensive (indoor) volleyball statistics -- hitting, blocking, serving, digging, setting, and receiving. Further, hitting percentage is now being calculated correctly (subtracting errors from successful kills, before dividing by attempts). Clicking here leads you to men's statistics at the team level, but from that page you can click on a heading to get to women's statistics, as well as varying whether you get team or individual statistics. Pool play ends this weekend for both men and women; upon conclusion of this stage of the competition, I'll present some analyses of how the pool winners did in the various statistical categories.

Statistics are available in a similar format for men's and women's beach volleyball, but there seem to be a lot of holes in the numerical information provided. There's already been a lot of excitement for the U.S. teams in the sand, as the legendary women's duo of Misty May-Treanor and Kerri Walsh had a first-game scare on Thursday against a Belgian team, whereas the men's pair of Phil Dalhausser and Todd Rogers eked out a three-game victory over a Swiss combo last night (U.S. time).

NBC Olympic Announcers Sunderland and Barnett Informative on Strategy and Stats

NBC's late-night Tuesday/early-morning Wednesday Olympic coverage featured a women's (indoor) volleyball match between the U.S. and Venezuela, ultimately won 3-1 by the Americans. Thus far, I've found announcers Paul Sunderland (a member of the 1984 U.S. men's gold-medal team) and Kevin Barnett (an Olympian of more recent vintage) to be informative on strategy and statistics.

As Game 4 got underway, Barnett (I believe, rather than Sunderland) asserted that U.S. blocking (7 in Game 3 alone) and Venezuela's poor serving (1 ace compared to 12 errors, through three games) were the "dictating statistics of this match." According to the final box score, the Americans indeed outperformed the Venezuelans in blocking, 16 to 6. Jen Joines, who entered the match in a substitute role for the U.S., was singled out for accolades by the announcers.

The announcers also stressed the importance of playing "in system." By this, they mean consisent, quality passing to the setter, so that she can have the maximum possible options in deciding which hitter to set. U.S. passing difficulties, both on serve reception and on free balls, were described as the "single greatest thing that's going to hold this team back in this tournament," again according (as best I could tell) to Barnett.

Following Statistical Aspects of the 2008 Summer Olympic (Indoor) Volleyball Competitions

With the Summer Olympics underway in Beijing, I would like to welcome everyone to VolleyMetrics, where I'll be presenting statistical analyses of several of the volleyball matches and taking comments from interested viewers. Before starting, I would like to offer condolences to the Bachman and McCutcheon families for the tragic attack that took place earlier.

First, for results and boxscores of (indoor) volleyball, you can go to the following link (I may add in some postings on beach volleyball, I'm not sure):

http://www.nbcolympics.com/volleyball/resultsandschedules/

As some of you may have seen this morning on television in the U.S., the American women opened up with a 3-1 victory over Japan. The boxscore for this match is available here.

Two of the major topics I have emphasized on this blog are hitting percentage and defending against opponents' hitting via blocking and digging.

If you look at the boxscores provided through the NBC Olympics website, you'll see that hitting percentage, as traditionally defined by volleyball statisticians, is not provided. The raw ingredients to calculate it, however, do appear to be present.

In the U.S.-Japan boxscore, just on top of the individual-player statistics, you'll see that for the aggregate team statistics, only the countries' successful spikes ("S") or "kills," and attempts ("A") are shown, and then the ratio of the two. That, of course, leaves out hitting errors, which count negatively against a player or team in the usual hitting percentage statistics.

Once you scroll down to the individual-player statistics, however, you'll see that in addition to successes (SUCC) and attempts (ATT), you get "FLTS" (which I interpret as faults or errors) and "CONT" (which I interpret as playing continuing, without the spike attempt immediately helping or hurting the attacking team). Note that for each player, SUCC + FLTS + CONT always adds up to ATT. From this part of the boxscore, therefore, we can add up all the players' FLTS numbers and get a team error total, which can be used along with the team success and attempt numbers higher up in the boxscore.

The U.S. thus had 64 successful kills, 17 faults (errors), and 145 attempts. Hitting percentage thus equals 47 (from 64 - 17) divided by 145, which yields .324.

Japan had 49 successful kills, 21 faults (errors), and 136 attempts. We then take 49 - 21, which equals 28, then divide by 136, yielding .206.

More later...

2008 Olympic Qualifying Tournaments

I recently visited the NBC Olympics website to learn about developments in the volleyball competitions taking place later this summer. While there, I found this article (accompanied by extensive statistics) on the final women's Olympic qualifying tournament, which concluded recently.

Among the statistics listed in the final tournament standings, were each team's points scored and allowed, and games (or sets) won and allowed (the first reference to "Points" in the chart appears to refer to points in the standings, 2 for a win and 1 for a loss; points won and loss in the rally scoring are separate).

Volleyball, like tennis and perhaps other sports, uses an aggregative or hierarchical scoring system. First, a team wins points. Upon winning 25 points in a game (15 in a Game 5), with at least a two-point margin, a team would then win a game (also known as a set). Winning three games would then give a team the match.

Certainly there would be a positive correlation among the winning of points, games, and matches. Teams that win more points should win more games, and those that win more games should win more matches. Focusing on the relationship between points and games (because these would have the largest numbers of observations), I wasn't sure that it would necessarily be perfectly linear, however.

Perhaps the plot of the two variables would be S-shaped. As a theoretical example, Team A might average 8 points per game (roughly a ratio of .33 if the opponent consistently scored 25 points per game), whereas Team B might average 12 points per game (roughly a ratio of .50). Team B would have a higher points ratio relative to the opposition, but both teams would have an equal (equally tiny) ratio of games won to games lost. Higher up the ability scale, where teams had moderately good point ratios, there could be a positive linear relation between point ratio and game ratio. Lastly, at the highest ability level, there could be slight variation among teams in their point ratios, but all could have uniformly high game ratios.

For what it's worth, given the small sample size of only eight teams, the obtained correlation between point ratio and game ratio was a near-perfect r = .989. The relation is shown below (you can click on the image to enlarge it).


Several findings are worth noting:

1. The range of ratios was much smaller for points (between .848 and 1.16) than for games (.25 to 2.857).

2. No teams were located particularly near the 1.00 neutral point for either ratio. To do so, a team would have had to play virtually all close matches, winning and losing equally often and by equal margins.

3. Although the overall distribution exhibited a virtually perfect linear pattern, there appeared to be greater flatness in the plot among the least successful teams, than among the other squads.

Preview of Penn State-Pepperdine NCAA Men's Final

In anticipation of tonigh't NCAA men's volleyball final between No. 1 Penn State and upstart Pepperdine (which only made the field via a late surge through the Mountain Pacific Sports Federation tournament), user "nomas" on the VolleyTalk discussion board offers this analysis of the match-up.

One of the salient issues is that Penn State has not played that tough of a schedule during the season, thus likely inflating the Nittany Lions' statistical prowess. As seen on Penn State's schedule, the Lions have played only a few matches against traditionally strong teams from the Pacific (Hawaii, UCLA, and Long Beach State), and two of those three matches were back in early January.

Preview of Men's NCAA Final Four

This coming Thursday and Saturday, the men's volleyball version of the NCAA Final Four will take place in Irvine, California (tournament website). The semi-finals will match Penn State against Ohio State, and Pepperdine against Long Beach State.

Men's collegiate VB is much more of a low-key affair than women's, with fewer schools fielding teams, less media coverage, etc. Accordingly, I have not posted nearly as much on the men's season as I had done for women's play last fall.

The Final Four is actually all there is of the men's "tournament." Three teams earn automatic berths via conference tournaments of the Mountain Pacific Sports Federation, Midwest Intercollegeiate Volleyball Association, and Eastern Intercollegeiate Volleyball Association. The field is rounded out by one at-large team, inevitably from the MPSF. The at-large choice is often controversial, and this year's was no exception.

The two contenders were BYU and Long Beach State, the regular-season MPSF co-champions at 18-4. Each lost in the conference tournament to eventual champ Pepperdine (which tied for fourth in the regular-season conference race at 12-10), thus giving the automatic bid to the Waves.

This Salt Lake City Deseret News article attempts to break things down scientifically:

The NCAA manual gives some criteria for selection the fourth at-large team — which didn't help clear up matters.

One of the first matters is won-loss records. Both finished tied atop the MPSF regular-season standings with identical 18-4 league records. Long Beach won the rights to host the MPSF Tournament, to be the top seed and to have the quarterfinal bye because of beating BYU twice in the regular season.

However, BYU had a better overall record, finishing 25-5 to LBSU's 23-6 — that's two more wins and one fewer loss than the 49ers.

Also considered is the strength of schedule, head-to-head competition, results against common opponents and results against Final Four qualifiers and other teams under NCAA tournament consideration.

LBSU had faced the other three Final Four teams in regular-season play, winning twice at Ohio State, losing at home to Penn State and going 1-2 all year against Pepperdine. The 49ers were also 1-1 against Cal State Northridge, who finished a game behind BYU and LBSU in the final league standings and lost to the Cougars in the MPSF semis.

BYU's five '08 losses were to Stanford (at home), twice to Long Beach (on the road), to UCLA (on the road) and to Pepperdine in the MPSF finals.

Long Beach's six losses were twice to Pepperdine (a regular-season defeat in Malibu and the MPSF semifinal loss), at hoem to Northridge, Penn State and UCLA and on the road at UC Irvine.

To me, the issue comes down to this. With NCAA tournament bids extremely scarce, why does the MPSF choose to have a conference tournament at all? The result this year is a regular-season co-champion staying home, while a team that finished six games behind in the standings will be playing in the Final Four. Perhaps the NCAA requires these conference tournaments to be held. It doesn't in other sports, however, so it probably doesn't in men's volleyball.

Tradeoff of Serving Aggressively (or Cautiously): Service Errors vs. Aces

The other night, I caught a replay of UCLA hosting USC in men's volleyball, on Fox College Sports. It was the second match of the season between the Bruins and Trojans. In the first match, as the TV announcers pointed out, the teams had combined for 51 service errors, so it was suggested they would be toning down their aggressive service in the rematch. Indeed, UCLA and USC cut their combined service errors in half, to 25, in the second match.

That got me to thinking about coaches' decision-making strategies involved in choosing whether to have their teams serve aggressively or cautiously. The most aggressive type of delivery would seem to be the jump serve, as illustrated in these brief video clips I found on the web (here and here).

Such a serve has the potential to generate an ace or, if not that, a ball that the receiving team struggles to retrieve and thus takes the team out of its offense. Trying to pulverize the ball on the serve also, however, creates the potential for a missed serve, either into the net or out-of-bounds long. Jump-serving truly seems to be a high-risk/high-yield proposition (see here for a general discussion of risk/return tradeoffs, from the perspective of investing).

Additional web-searching turned up a 2000 American Volleyball Coaches Association (AVCA) newsletter article on serving, written by Melissa Stokes, who this past fall completed her 12th year as women's coach at Missouri State (formerly known as Southwest Missouri State).

The article by Stokes covers serving strategies and practice drills, with a healthy supply of statistics thrown in (probably from 1999). Using stats from the Missouri Valley Conference (in which her team plays), Stokes reveals that though her team was not among the league leaders in aces per game, it kepts its service error rate very low, resulting in virtually a 1-to-1 ratio of aces and errors. In contrast, there were a few MVC teams whose error-to-ace ratios were roughly 2-to-1. Stokes commented that:

Every team will have a different serving philosophy. This chart shows you that these statistics support our serving philosophy. We may not have posted as many aces, but committing fewer errors allowed our players the opportunity to score points at the net or by playing defense.

My curiosity sufficiently piqued, I then went and found the boxscores for the two UCLA-USC men's matches (both of which, incidentally, were won by the Trojans).

UCLA at USC (January 23, 2008, 5 games)
UCLA: 11 aces (2.2/game), 30 errors (6.0/game)
USC: 3 aces (0.6/game), 21 errors (4.2/game)

USC at UCLA (February 6, 2008, 3 games)
UCLA: 3 aces (1.0/game), 11 errors (3.7/game)
USC: 4 aces (1.3/game), 14 errors (4.7/game)

Speaking in approximate terms, UCLA's rates of aces and service errors each were cut in half from the first to the second match. This kind of proportionality is what I would have expected. USC doubled its rate of aces (albeit from a low baserate), but only experienced a slight proportional rise in errors.

These are just some limited examples, but I hope this posting can spur an expanded discussion of serving tradeoffs.