Texas Tech professor Alan Reifman uses statistics and graphic arts to illuminate developments in U.S. collegiate and Olympic volleyball. [For archives of this blog and extensive links to other volleyball sites, please click the three-line icon in upper-right corner.]
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
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
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'
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 o
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
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 n