Serve-Receipt Success in Different Rotations

Yesterday was the home opener at my university, Texas Tech, as the Red Raiders hosted Texas A&M in Big 12 play. It was also the home debut for new Tech coach Trish Knight, who faces an enormous rebuilding job. Prior to Knight's arrival, Tech had lost 39 straight conference matches. After yesterday's 25-15, 25-11, 25-17 shellacking by the Aggies, the streak is now at 41 (the Raiders lost a Big 12 road match before returning home to play Texas A&M).

With pencil, paper, and camera in hand, I decided to focus my statistical analysis yesterday on the serve-receipt success of Texas Tech's six rotations. I took the following picture (which you can click on to enlarge) during Game 3. We see that for the Red Raiders (near court), No. 11 (Amanda Dowdy) is front left, No. 4 (setter Caroline Witte) is front center, No. 13 (Barbara Conceicao) is front right, No. 1 (Hayley Ball) is back right, No. 10 (Aleah Hayes) is back center (her number doesn't show in the picture, but I got it from my notes), and No. 9 (libero Jenn [Harrell] Goehry) is back left. Once the ball is served, players can shift laterally; as shown in the photo, the setter Witte (No.4) is getting ready to move to the right, to leave Conceicao (No. 13) in her natural position of middle-blocker.


Shown next is a chart of Tech's six rotations in Games 1 and 3 (the rotation with the court depicted in yellow is the one in the photograph). In a few cases, I was unsure about a uniform number and/or positioning, but I've re-created the rotations to be as logically coherent as possible (e.g., if a given player were in the front left position in one rotation, she should be in the front center position in the next rotation). Between the libero role and just ordinary substitution, charting a team's rotations was not nearly as easy as I thought it might be.


As it turns out, you don't really need advanced statistical methods to see which rotations did better or worse on serve-receipt in Game 1 (I did not keep statistics when Tech served, but by locating server names in the play-by-play sheet and consulting the Red Raider roster, the success of the different rotations on serve should be able to be determined).

The ideal for a serve-receipt opportunity, would of course be to have a successful First-Ball Attack (FBA). In other words, the served ball would be dug, set, and spiked for an immediate kill. Texas Tech's starting rotation (the top-most in the left-hand column) achieved this ideal both times it had the chance. Starting setter Karlyn Meyers (No. 3) was in the back row, meaning that she had three front-row attackers at her disposal.

The Raiders' weakest rotation was clearly the third one down (one of three rotations in which the setter is in the front row, thus leaving only two eligible front-row attackers). In this rotation, Tech exhibited just about every problem in the book. Mostly, the Red Raiders mounted an FBA where the hit was Not Put Away (NPA), leading to a rally that the Aggies eventually won. Tech also failed to get its FBA onto the Aggie side of the court inbounds (twice), sent over a free ball, and made an overpass.

I assume that all teams keep their own statistics of this type. Further, there appear to be computer software packages available to assist with such data-collection efforts (just do a Google search with keywords such as: computer software volleyball rotation).