Analysis of Last Night's Thrilling Penn State-Texas NCAA Women's Final

Last night's NCAA women's championship match between Penn State and Texas was truly, pardon the cliche, one for the ages. There was the historical aspect -- the Nittany Lions winning their 102nd straight match and third straight national title. There was the aspect of the teams' senior leaders trying to will their respective squads to victory -- the Longhorns' Destinee Hooker dominant for most of the match, with the Penn State pair of outside hitter Megan Hodge and setter Alisha Glass getting by with a little help from their friends. And there was the comeback aspect -- Penn State having trailed two games to none -- and the fact of how closely the teams ultimately were matched. There were 10 tie scores in the decisive fifth game, which was won by the Nittany Lions 15-13.

Here at VolleyMetrics, however, our job is statistical analysis. The role of statistics in the sport arguably reached a new milestone during last night's telecast when Penn State coach Russ Rose, in a brief interview heading to the locker room for the "halftime" break between Games 2 and 3, noted the following (as I transcribed from ESPN360.com's archived video of the match):

"...five of [Hooker's] 15 or 16 kills were on tips to the right front on [Penn State's] Blair [Brown]... [Hooker] hits the ball so high, you've got to make some better adjustments."

As we'll explore through the numbers, the one decisive factor for the Nittany Lions can perhaps be distilled to one word: balance. Simply put, Penn State seemed to have a lot more options in the long run than did Texas. Before we begin the major statistical analyses, I must express great thanks to the NCAA for providing a "deluxe" 11-page box score, which provides not only overall match statistics, but also statistics and play-by-play sheets for each game (set). The graphics I've created (shown below) would have been a lot more difficult to produce without the elaborate box score.

In our first graph, we see that Hooker clearly got the best of Hodge in individual hitting statistics.


For readers relatively new to volleyball who aren't familiar with the formula for hitting percentage, ESPN was kind enough to provide an example of a calculation, midway through the match.


Longhorn coach Jerritt Elliott had an interesting, possibly surprising, observation after the match, as reported in the Daily Texan (second linked article above):

“I thought we set [Hooker] a little bit too much,” Elliott said. “We kind of got out of our rhythm a little bit. But for us to win, Destinee has to have a big game. She’s carried us. She performed at a very high level.”

Readers may find it useful to ponder Elliott's statement in light of the following graph.


Yes, Hooker was set a lot, but no more (as a proportion of the respective teams' hit attempts) than was Hodge. With Hooker hitting markedly better than her teammates -- the opposite of what happened with Hodge and Penn State -- it seems hard to fault Longhorn setter Ashley Engle (or Elliott, if he was calling the plays) for calling Hooker's number so often.

The excellent hitting of Hodge's supporting cast manifested itself at the most important time. In Game 5, three Penn State players -- Arielle Wilson, Blair Brown, and Darcy Dorton -- combined for 7 kills (with no errors) on 10 attempts, for an overall .700 hitting percentage.

In my previous posting (below), I speculated that blocking would be important, and boy was I wrong! As shown in the next graph, in Games 2 and 3, the losing team outblocked the winning team. Perhaps at a larger level, however, one could argue that Texas's relative parity with Penn State in blocking -- the Longhorns had only two fewer total team blocks than than the Nittany Lions, 12 to 14 -- helped keep the Burnt Orange so competitive.

Hodge and Hooker Key to Upcoming Penn State-Texas NCAA Women's Final

Saturday night's NCAA Division I women's championship match between Penn State and Texas will pit a couple of star outside hitters against each other. For the Nittany Lions, it's Megan Hodge (shown on top in the following sequences), whereas for the Longhorns, it's Destinee Hooker (who has also won multiple NCAA high-jump titles in track and field). I made these screen captures from ESPN360.com's archived videos of Thursday's two semifinal matches (I added yellow outlines to highlight the ball and Hooker's burnt orange sleeve).



Being able to assess the physical parameters of a spike attempt -- how high above and far behind the net it was struck, at what downward angle, and at what speed -- might be the way of the future for volleyball analysts, much like Pitch f/x, which already exists in Major League Baseball. I am not aware of anything similar coming up in the near term for volleyball, so the above photo sequences will have to serve merely as an inspiration of what might become available in the future.

In terms of more conventional volleyball statistics, one that jumped out at me was Hawai'i's total of ZERO team blocks vs. Penn State Thursday night, compared to the Nittany Lions' 15. In the other semifinal, Texas outblocked Minnesota 5-2. (Only when the defense directly earns a point such as by stuffing the ball back onto the hitting team's floor is a block officially credited; see scorekeeping procedures.)

According to official NCAA statistics (through December 13) on blocks per game (or set), Penn State ranked second in the nation at 3.23, Texas was fifth at 3.03, and Hawai'i was way down at 40th with 2.46. If these statistics are any indication, Texas should be more competitive with Penn State than was Hawai'i.

Word Clouds of NCAA Women's Final Four Teams

I thought it would be interesting and fun to analyze the NCAA women's Final Four (beginning Thursday night) via "word clouds." Actually, I stole the idea from someone who used word clouds in connection with the Major League Baseball playoffs a couple of months ago. Anyway, with word clouds, the user can simply copy and paste blocks of text (in my case, game articles from the NCAA tournament) into a field at the website Wordle.net and have it generate "clouds," such as those shown below, that depict the most frequently occurring words in the text.

With Penn State, for example, I went to the school's athletic website and got the four articles reporting the Nittany Lions' wins in each round leading up to the Final Four. I then copied and pasted all four articles, stacked one on top of the other, into the text field at Wordle. I also did the same for Texas, Hawai'i, and Minnesota. You can click on the graphics below to enlarge them (you'll almost certainly need to, in order to see the smallest words).

You'll see for each team the names of its most prominent players standing out in the largest type, such as Megan Hodge, Alisha Glass, and Arielle Wilson for Penn State; Destinee Hooker and Juliann Faucette for Texas; Kanani Danielson, Stephanie Ferrell, and Aneli Cubi-Otineru for Hawai'i; and Lauren Gibbemeyer, Tabitha Love, and Taylor Carico for Minnesota.

Also showing up readily in the clouds are various volleyball terms. The terms "kill" and "kills" (i.e., "put away" spikes that the defense can neither block nor dig) feature prominently in each team's display, but they really seem to stand out (to my eyes, at least) for Hawai'i and Penn State. According to official NCAA statistics, the national rankings of the four teams in kills per game (or set) are Penn State (5), Hawai'i (11), Texas (13), and Minnesota (33). Coincidence? Maybe, maybe not. If you think there are any valuable insights to be gleaned from these clouds, let us know via the Comments feature!

Statistically Minded Penn State Coach Russ Rose Featured in New York Times

Yesterday's New York Times had an article on Penn State women's volleyball coach Russ Rose and his longtime fascination with volleyball statistics. His team currently would have to be considered the nation's most dominant college program in any sport -- with 98 straight matches won and in pursuit of a third straight NCAA national title. The following stretch of paragraphs in the article describes Rose's background in statistics and how he augments the traditional statistics reported by the NCAA:

Rose thought he would be a gym teacher, maybe a basketball coach. But at George Williams College, he began playing volleyball under Jim Coleman, a former Olympic team coach and a future volleyball Hall of Famer. Coleman is credited with creating the modern volleyball statistics system, among other innovations.

Rose then spent two years at Nebraska, where his master’s thesis examined the skills most associated with winning. (“Passing predicts the level of play,” Rose said of his conclusion. “Hitting and blocking are most correlated with winning.”)

Official statistics have always bothered him. Most sports tally what the player did, not what he or she failed to do. He sees that as only half the equation. What about the rebound the basketball player should have had? Or the ground ball the shortstop did not reach? Or the dig that the volleyball player blew?

“On that sheet,” Rose said, pointing to a match’s official N.C.A.A score sheet, “if you don’t hit the ball, you don’t get a statistic. On mine, you do. You didn’t hit the ball.”

Most of his scribbles in the notebook reflect missed opportunities, what his players call “error control.” Rose grades each play, too, on a scale — not just whether the serve was in, for example, but how good the serve was.

The degree to which Rose's use of statistics in his coaching plays a causal role in the team's success is probably unknowable. I suspect, though, that when everything else is equal (which it usually is not) between Penn State and its opponent in terms of talent, experience, and so forth, Rose's stat-based strategizing may help the Nittany Lions get a few extra points here and there.

How Conferences Have Fared So Far in the 2009 NCAA Women's Tourney

Thanks to a pair of upsets -- Colorado State over Washington, and Baylor over UCLA -- the Pac 10 was left with only two teams among the Sweet 16 (Stanford and Cal). On the other hand, the Big 12, with five remaining teams, and the Big 10, with four, aquitted themselves well.

These results made me curious as to how Big 10, Big 12, and Pac 10 had done against each other during the regular season. The following chart (which you can click on to enlarge) shows the answers.


Big 10 and Big 12 teams met on 10 occasions, far more than teams from either of these conferences took on Pac 10 opponents. In clashes between the Big 10 and Big 12, the Big 10 won seven times. Arguably, the two most impressive of such wins were Michigan over Nebraska, and Minnesota over Iowa State. In fairness, these match-ups were not necessarily balanced in terms of competitiveness, as a large chunk of the Big 12's losses were by two of its weaker teams, Kansas State and Texas Tech.

Looking at the bracket, the Big 12 is assured of at least one Final Four team, with the Omaha region consisting entirely of teams from the conference (Iowa State, Nebraska, Texas A&M, and Texas). The fifth Big 12 team, Baylor, is in the same region with Penn State, so is extremely unlikely to make the Final Four.

Two-time defending NCAA champion Penn State is one Big 10 team that's a prohibitive favorite to make the Final Four. Illinois and Michigan comprise half the Stanford regional, but the host Cardinal and Hawai'i will be tough opposition. Minnesota, playing its regional at home, would arguably be favored to join the Final Four.

Correlation Between NCAA Women's Teams' Hitting Percentages and Tourney Seeding

As longtime readers of this blog know, I have focused extensively on hitting percentage as a kind of "all-in-one" marker of a team's productivity. Points are what win games and matches, and hitting percentages include a lot of information about points gained (through kills) and lost (through hitting errors), as well as spike attempts that merely keep the ball in play and thus reflect missed opportunities to score points.

If one looks at the seedings of the upcoming NCAA Division I women's tournament and the final regular-season statistics on team hitting percentage, one sees quite a bit of correspondence.

Penn State is the top national seed and led the nation in hitting percentage. Texas is seeded second and finished second nationally in hitting percentage. Florida State is seeded third (a surprise to many, perhaps because the Seminoles did not play many matches against "power-conference" opponents) and was fourth in hitting percentage.

For the 16 nationally seeded teams, I've plotted the relation between seed and hitting percentage, below. (Note that there are also some teams that finished in the top 16 nationally in hitting percentage, but either got into the NCAA field as a non-seed, such as St. Mary's (Cal.), which ranked eighth in hitting percentage, or missed the field entirely, such as Maryland-Eastern Shore, which was sixth).


For readers with some statistical training, the correlation is negative, meaning that smaller seed numbers (where 1 is best) go together with higher hitting percentages. The trend is not quite statistically significant, but with the small sample size of 16, that's not surprising.

I have highlighted two teams -- Washington and Hawai'i -- in underline and italics, as they had hitting percentages above what their seedings would seem to suggest. If the Huskies and Rainbow Wahine do better than what their respective seedings would project, that will further support the importance of hitting percentage (it should be noted, however, that Hawai'i is ranked No. 3 in the nation in a couple of "traditional" coaches' and media polls).