The major known ranking systems -- the AVCA Coaches' Poll, RPI, Pablo Rankings, and Rich Kern Rankings -- all appear to take teams' win/loss records and strength of schedule into account. As anyone who has read my blog over the past five years knows, my focus has always been on hitting percentage. I think it's a great singular statistic for incorporating many aspects of the game.
If you hit well (not just keep the ball in play, but get kills), your (individual or team) hitting percentage goes up. An attack kept in play by the other team hurts, as does a hitting error (spiking the ball out of bounds or getting stuff-blocked for an opponent's point). In order to hit well, a team must pass and set well. If you block or dig your opponent's spike attempts, that drives down the opponent's hitting percentage.
What I've done, therefore, is create a national ranking metric based heavily on each team's ratio of its own overall season hitting percentage (offense) divided by the overall hitting percentage it has allowed the opposition (defense). A ratio is maximized when a large numerator is divided by a small denominator. For example, hitting .300 for the season and allowing one's opponents (in the aggregate) to hit .100 yields a ratio of 3. Hitting .250 and allowing one's opponents to hit .200 yields a ratio of 1.25.
But that's not all. Teams play in differentially tough conferences, so I wanted to adjust for that. I came up with a very simple adjustment system out of thin air. We'll see how well my rankings predict this year's tournament matches and I can modify my conference adjustments as needed. Here's my current adjustment system:
- If a team plays in the Big 10, Big 12, or Pac 12, I multiplied its hitting percentage-to-opponent hitting percentage ratio by 1.25. This way, teams that faced what I (and others) consider the top opposition are rewarded for doing so.
- Teams from the ACC, SEC, Big East, Atlantic 10, Mid America, Missouri Valley, West Coast, Big West, Mountain West, Western Athletic (WAC), or Conference USA had their ratios multiplied by 1.00 (i.e., leaving their ratios alone).
- Teams from all remaining conferences, whose schools tend to have relatively low athletic budgets and little or no track record of national success in women's volleyball, had their ratios multiplied by 0.75. Teams dominating these smaller conferences could hit really well and keep their opponents' hitting low, so to account for this, I adjusted their ratios downward.
Nebraska coming out top-ranked seems to give my system a little "face validity." Further, I have USC ranked higher than does the NCAA tournament committee! And if Dayton or Colorado State makes a big run in the tourney, you heard it here first. Like all other ranking systems, mine will stand or fall on how well it predicts tournament games. For any given match, we would predict the higher-ranked team to beat the lower-ranked one. We'll see how it works.
A note on sources: I obtained all teams' (offensive) hitting percentages from the NCAA statistics page (see link in right-hand column). To glean teams' opponent (defensive) hitting percentages, I looked at a variety of conference and team-specific pages. When looking at conference and team pages, I checked whether the listed offensive hitting percentages matched those on the NCAA site, to verify that the statistics were from the same time-frame. As it happened, a few tiny discrepancies appeared between the NCAA and conference/team pages regarding teams' offensive hitting percentages (e.g., the NCAA page said Yale had hit .253, whereas the Ivy League page said the figure was .254).
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