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.]
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FiveThirtyEight Tackles Women's College Volleyball
The website FiveThirtyEight, which offers quantitative analyses of politics*, sports, and culture, today turns its attention to women's college volleyball. The article is not as statistically laden as a lot of other FiveThirtyEight pieces, but has some numerical analysis. Mainly, the article looks at leading teams' returning talent, presenting the percentage of each team's total kills, assists, digs, blocks, and aces from last year that are accounted for by players returning this year. For example, of the 1,791 total kills Cardinal hitters recorded last year, 85.1% were collected by players returning this year.
*The website's name comes from the number of electoral votes in U.S. presidential elections.
Two years ago, I created a very simple prediction equation for the NCAA women's tournament. Each team gets its own value on the predictive measure. To calculate it, you take a team's overall hitting percentage at the end of the regular season and divide it by the hitting percentage the team allowed its opponents (in the aggregate). The result is then multiplied by an adjustment factor for conference strength, as shown here . For any match in the NCAA tourney, the team with the higher value on my measure would be expected to win. In both 2012 and 2011 , my formula did about as well as other, more complicated ranking formulas. I'm not going to do a full-scale analysis for this year's bracket , but I wanted to mention the formula and provide some sample calculations, in case anyone wanted to compute a score this week for his or her favorite team. The necessary information should be available from the volleyball page of a given school's athletics website. Here are 20
I was invited once again this year to vote for the Off the Block men's collegiate volleyball awards . The number of awards has increased and I've been very busy this semester, so I may not have time to conduct statistical analyses for all of the categories. However, I have conducted an analysis to determine my votes for National Server of the Year. The NCAA men's volleyball statistics site (see links column to the right) provides an aces-per-set statistic. Aces are only one part of judging serving ability, in my view. Someone might be able to amass a large ace total by attempting extremely hard jump serves at every opportunity, but such aggressive serving likely would also lead to a high rate of service errors. Another aspect to consider would be serves that, while not aces, still took the opposing team out of its offensive system. Only aces and service errors are listed in publicly available box scores, however. What I did, therefore, was find out the top 10 players in
With this year's NCAA women's Final Four getting underway Thursday night in Seattle, today's posting offers some statistical observations. The two semifinal match-ups feature defending champion Texas vs. upstart Wisconsin, and Penn State vs. hometown favorite Washington. Wisconsin, a one-time power that had missed the NCAA tourney from 2008 through 2012, is now back in an ascendant mode under new coach Kelly Sheffield. Seeded 12th nationally, the Badgers benefited in their part of the bracket from the fact that SEC teams Missouri (No. 4 seed) and Florida (No. 5 seed) were Paper Tigers and Gators, respectively. Having said that, Wisconsin may be the kind of team that can give Texas a tough match (like Michigan in last year's semifinal ). A year ago, I developed a statistic that attempts to measure teams' "grind-it-out" tendencies . To me a grind-it-out team is one that lacks spikers with pulverizing power, but digs opponents' attacks well and avoid