Penn State Women Complete Undefeated Season with Title-Match Sweep of Stanford

As virtually all college-volleyball fans would know by now, Penn State has successfully defended its NCAA women's title and gone undefeated (38-0) in the process, sweeping Stanford in three games in the final. The scores were 25-20, 26-24, and 25-23. Here are a few brief observations on the match...

Penn State outhit Stanford in Games 1 (.257-.167) and 3 (.196-.109). The Cardinal outhit the Nittany Lions in Game 2, .159-.102. As I showed in analyses of the earlier rounds, a team will usually win the game when it outhits its opponent by this much. In this instance, though, it didn't turn out that way for Stanford.

On the ESPN2 telecast of the final, color commentator Karch Kiraly added a statistical flavor to the proceedings, with his periodic evaluations of the teams' serve-receipt/passing effectiveness on a 0-3 scale.

Happy holidays to everyone! VolleyMetrics will be back in the new year to focus on men's college volleyball.

Pre-Match Analysis of Penn State-Stanford Women's Final

With tonight's NCAA championship match between Penn State and Stanford just hours away, I wanted to provide some pregame statistical analysis. In the aftermath of Penn State's dramatic semifinal victory over Nebraska, one of the most frequent observations among discussants at the VolleyTalk site was how the Nittany Lions appeared to stray from attacking the middle against the Cornhuskers. In order to break things down scientifically, I created the following graph based on Penn State's NCAA tournament matches thus far this season.


Indeed, it appears that the Nittany Lions' three middle-hitters (Christa Harmotto, Blair Brown, and Arielle Wilson) have been getting a declining proportion of the team's hitting attempts in recent matches.

Meanwhile, outside-hitter Nicole Fawcett has, to an increasing extent, been getting the "lion's share" of the hit attempts. Penn State's other main outside-hitter, Megan Hodge, has consistently been getting between 25-35% of the team's hitting attempts in the tournament, thus the degree to which she was set against the Cornhuskers was well within normal range.

From Stanford's perspective, one of the main ways in which the Cardinal has succeeded this season is by limiting opponents' offensive prowess. When that fails, however, Stanford seems to be able to lift its own offense to a higher level. This game article from Stanford's semifinal victory over Texas notes that, "The Longhorns were the first team all year to hit above .300 against the Cardinal..."

In fact, even with the Longhorns hitting .438 and .381, respectively, in Games 4 and 5, the Cardinal was able to prevail in both games by hitting an astronomical .439 and .500 (box score). As discussed in the article, it was Stanford's "Big Three" doing the damage:

It took all that Stanford's three All-American hitters could muster, but in the end Alix Klineman, Cynthia Barboza and Foluke Akinradewo played one of the best matches of their careers. Klineman paced the team with 20 kills, while Akinradewo slammed 17 on .452 hitting and provided six critical blocks. It was Barboza, however, who stole the show in the improbable comeback, recording 15 of her 19 kills in the final three sets.

In conclusion, Stanford appears to have two options: slowing down Penn State's offensive attack or, failing that, prevailing in a slugfest. Neither seems too likely to me.

Measuring Serving Effectiveness: The Length of Average Serving Stint (LASS)

For the last few weeks, I've been trying to think of new ways to measure serving effectiveness. Box scores and statistical summaries typically report only service aces and errors (example). My concerns are that aces occur infrequently (limiting their statistical usefulness), and that focusing on aces does not take into account how even serves that are picked up by the receiving team can still be advantageous to the serving team (e.g., by preventing the receiving team from setting up its top available hitting threat).

Alternatively, one can obtain detailed statistics by observing and classifying the receiving outcomes of serves into micro-level categories, such as whether a serve disrupted the receiving team's ability to "mak[e] the first tempo attack," as reported in this article. If a team has the staffpower resources to record such statistics, that's great, but not everyone can.

What I've been conceiving of, therefore, is some sort of "middle ground" statistic -- something easily derivable from online play-by-play sheets (as can be accessed, for example, via this NCAA interactive bracket by clicking on particular games), but that goes beyond just service aces and errors. What I've come up with is the Length of Average Serving Stint or LASS.

The longer a serving stint, the more points the serving team is racking up. If a stint lasts for one serve, the serving team has not received a point (i.e., the other team has sided-out). If a serving stint lasts two serves, the serving team has garnered one point. If a stint lasts three serves, the serving team has accumulated two points, etc. Thus, longer serving stints appear to capture -- indirectly, at least -- effective serving.

Before anyone starts sending me e-mails of complaint, I am aware that the identity of a server is systematically connected to (or "confounded" with) the serving team's front-court line-up, due to the rotation. Thus, if Player A tends to have long serving stints, some (or even most) of the credit might be due to the team's having Players B, C, and D in the front court, rather than Player A's vicious serving. I never claimed that my new statistic was perfect!

Also, I suspect that many coaches already chart their teams' success at winnning points and siding-out, by rotation, which is very similar to my scheme. The difference would just be a matter of focus, as I'm interested in who is serving.

What the LASS does have going for it, however, is relative ease of compilation. One can simply look at a play-by-play sheet and see how many plays in a row somebody served. A sample chart of LASS statistics is shown below, for the University of Texas in its recent NCAA Elite Eight match-up against Iowa St. Shown in each box is the length of a given serving stint; going down the first column shows you each player's first stint (in the order they served), the second column shows each player's second stint, etc. You can click on these graphics to enlarge them.


I've gone ahead and calculated LASS statistics for all regular players from the Final Four teams that will be playing Thursday night, based on each team's two games in last weekend's regionals.


If one were going to adopt the LASS, it would be best to use a much larger database than just two matches; my initial calculations were purely for illustrative purposes.

I'm interested in what readers think are the pros and cons of the LASS. I invite you to use the Comments section to provide feedback. Now enjoy the Final Four!

Looking Back on Opening Weekend (First Two Rounds) of 2008 NCAA Women's Tourney

I've put together a bunch of statistics on last weekend's opening two rounds of play in the NCAA Division I women's volleyball tournament. Forty-eight matches were played (32 in the first round and 16 in the second), comprising roughly three-fourths of the tournament's total matches (63 are played, in all).

In these 48 matches, 179 total games (sets) were played. The type of result (i.e., sweeps, four- and five-game matches) broke down as follows:

3-0: 24
3-1: 13
3-2: 11

The closeness of many matches is illustrated by looking more closely at the five-game tilts. Five were decided by the minimum two points, another three were decided by the score of 15-12, and only three were decided by 5 or more points.

Regular readers of this site know that I consider hitting percentage to be a very important statistic. For each of the 179 individual games played over the first weekend, I examined each team's hitting percentage in relation to who won the game. In only 19 games (11%) did the lower-hitting team win the game.

The following chart shows the relationship between the margin by which the higher hitting team in a game outhit the lower hitting team (horizontal axis) and the probability of the higher hitting team winning the game (vertical axis).


Starting at the left, when a team outhit its opponent by a very small amount (.001-.049), it had about a 62% chance of winning the game (16/26, which is not significantly above a 50/50 chance probability). If a team outhit its opponent by a somewhat larger margin (.050-.099), it had a 78% chance of winning the game (25/32, which is significantly beyond chance).

The remaining bars in the graph tell us that, if one team's hitting percentage in a game is greater than its opponent's by .100 or more, the higher-hitting team was virtually certain to win the game. In fact, from this point onward, there were only two cases (out of 121 possible) where a team outhit its opponent and lost.

One of these instances occurred in Game 1 of the Illinois-Cincinnati match in the second round. Cincinnati recorded the better hitting percentage (.294 vs. .189, a difference of .105), but Illinois prevailed 26-24.

An even more extreme anomaly occurred in Game 3 of the second-round match between Florida and Colorado State. The Gators were victorious, 25-23, despite being outhit by the substantial margin of .226 (UF .107, CSU .333). For this one, I had to see what happened, so I consulted the online play-by-play sheet. The apparent reason why the Rams lost this game despite a hefty hitting advantage is that they made EIGHT service errors.

I also looked at some miscellaneous hitting statistics. Two teams stood out as super-consistent in particular matches, their game-to-game hitting percentages staying within a band of .100 percentage points throughout five games.

In a first-round win over San Francisco, Duke recorded the following hitting percentages in the five games: .255, .243, .243, .182, and .273 (box score).

Also in the opening round, Purdue hit for the following percentages in defeating Louisville: .333, .290, .333, .321, and .294 (box score).

I hope these statistics will give you something to think about as you await the next round, beginning Friday.

Kansas State at Texas Tech Regular-Season Finale

As we await the start of the women's NCAA tournament, I thought I'd share some photos from last Saturday night's match featuring Kansas State at Texas Tech (you can click on the collage to enlarge it).


It was Senior Night for three Red Raider players, Michelle Flores, Brandi Hood, and Amanda Sbragia. Sadly for the seniors (and the broader Texas Tech volleyball community), the team lost to Kansas State to finish 0-20 in Big 12 play this season; going back to last season, Tech has lost 39 straight conference matches. Not surprisingly, Saturday night's match was the last for Coach Nancy Todd, ending her six-year stint with the Raiders.

Shown on top are some shots I took during the warm-ups (I wouldn't want to risk distracting the players with flash photography during actual game action). In the lower right-hand corner, your trusty analyst is shown, serving the ball during a contest between Games 2 and 3 that was open to all members of the audience. A dozen or so pizza boxes are placed on the court on the other side of the net, and anyone whose serve lands on a box wins a pizza or other prize. I didn't hit a pizza box, but I'm proud to say my serve landed in-bounds!

The season isn't over for Kansas State, however, as the Wildcats will be participating in the NCAA tourney.

Correlation Between Seed Number and Making the NCAA Women's Sweet Sixteen

The brackets have been announced for this year's women's NCAA Division I championships. A couple of matches will be played Thursday, but most of the action in the 64-team field gets underway Friday. At each of this weekend's sites, the second round will be played the night after the first-round matches. Tonight, and during the next three weeks, VolleyMetrics will be exploring various statistical aspects of the NCAA's "December Madness."

Tonight, let's start with something very basic, namely the record of No. 1-through-No. 16-seeded teams over the past five tournaments (2003-2007) in making the Sweet Sixteen. That is, of course, the immediate goal of all teams playing this weekend. Unlike the NCAA basketball brackets in which all 64 teams are seeded (i.e., each of the four regions has its teams seeded 1-16), the women's volleyball bracket only seeds 16 teams (explicitly) total.

Thus, for example, among the 16 teams vying to make the four-team regional to be hosted by Penn State, one can see teams labeled with the No. 1, 8, 9, and 16 seeds nationally, and the remaining 12 teams have no seed number by their names. Each of the other three regions also has four seeded teams. The NCAA committee may well, of course, have ranked all 64 teams so that the No. 1 seed gets easier early-round opposition than does, say, the No. 16 seed, but such rankings are not shown explicitly in the brackets released publicly.

At this point, it should be mentioned that all of the 16 explicitly seeded teams are expected to make the "Sweet Sixteen" (i.e., the four four-team regionals). But do things actually work out that way? As stated above, I have examined the past five years' tournaments to look at whether highly seeded teams have a better track record of making the Sweet Sixteen (regionals) than do lower seeds, among the 16 seeded teams. To increase the sample sizes and thus reduce chance fluctuation, I have grouped together the No. 1-through-4 seeds, 5-8 seeds, 9-12 seeds, and 13-16 seeds. Here are the results...

Teams seeded No. 1-4 are a perfect 20-of-20 in making the Sweet Sixteen during the past five years.

Teams seeded 5-8 have had a little bit of turbulence, successfully making the Sweet Sixteen 17-of-20 times (85%). Two of the exceptions occurred a year ago, with No. 6 Washington losing in the second round (round of 32) to BYU, and No. 7 Wisconsin losing in the same round to Iowa St. In 2005, it was No. 5 Stanford losing in the second round to Santa Clara.

Likewise, teams seeded 9-12 have had a 17-of-20 success rate. Last year's wacky brackets also saw the premature exits of No. 9 Kansas St. (to Oregon in the second round) and No. 11 Hawaii (to Middle Tennessee in the second round). The third upset involved No. 12 USC losing to Pepperdine in 2005, again in the second round.

Finally, as might be expected, teams seeded 13-16 have the lowest success rate of making the regionals, 14-of-20 (70%). I won't bother to list all six of the upset losers.

Interestingly, only one year of the last five, 2003, has seen all 16 national seeds move on to the Sweet Sixteen. In 2006, 15 of the 16 did. It thus seems likely that at least one of this year's 16 national seeds will be gone by this weekend. Whether things will be as wild as last year, when six of the 16 seeds failed to make it to regionals, remains to be seen.