Behind the Laptop Week 14+1
The season may be over, but the season's work is not
Friday 12/6
While my afternoon schedule has changed because we are no longer practicing every day, there’s been plenty of work to keep me busy this week. My head coach has been conducting end-of-season player meetings this week so he asked me to prepare stats for him to use in those meetings. While he only asked for returning player stats relative to the conference, I took advantage of the opportunity to do a bunch of work that otherwise would have been done in July. Let’s take a quick look at what I’m doing to create player and team rankings.
Throughout the course of the season, I spend time each week downloading the Volley Metrics scout files from all the matches involving Big 12 conference teams, including my own team’s matches. I ended up downloading over 300 scout files and importing them into Data Volley for use in opponent scouting but I also processed those same files for use in Tableau. While the primary use of that data, even in Tableau, is for opponent scouting, I also use it to look at team, position, and individual stats over time. It’s that secondary use of the data that I’m describing here.
The stats I look at are not special, but they do reflect, to some extent, what our program values and what we think it takes to win. There are lots of other metrics we could use, but the ones we use are insightful and easily digestible. The first step for me is to rank the teams/positions/players in our conference according to the different metrics our coaches are most interested in. (Really, the first step is wrangling all the data so I can calculate the ranks and the averages for each third, but that work is not-at-all sexy or interesting, just necessary.) Those rankings look like this.
This table answers the question, “how efficient was each team in Big 12 play this season?” All the other tables I use are some version of this. Some focus on how different positions performed, but still on the level of the team. What I mean by that is the table would show the attack efficiency for all the middles combined for each team. Such a table answers the question, “how efficient were each team’s middles this season?” I also have tables with each player in the conference, sorted by position. Those tables allow analysis on the individual level and answer questions like, “who were the most efficient middles in Big 12 conference play this season?”
Once I’ve digested all the data, I’ll present it in tables and indicate where our team/positions/players fell within the list. You’ll notice that there are no “standards” per se, no benchmarks that we feel we have to hit in order to be successful. The standard, in some sense, is the opponent. You don’t have to be better than a bunch of numbers, you need to be better than a bunch of teams.
If you’re consistently in the top third of the statistics, you’re likely winning enough to be in the top third of the conference, which is usually good enough to earn a seed in the NCAA tournament. If you’re consistently in the middle third, at best, you’re a tournament bubble team. That’s a scary place to be if your ambitions are to make the tournament. If you’re consistently in the bottom third, you’re sitting in your office today compiling this data instead of scouting tournament opponents.
If you go back to the first table, you’ll see how well my evaluation of the different thirds held up. The top five teams all advanced to the second round of the NCAA tournament. The sixth place team lost in the first round, the seventh place team is a top NIVC seed, and everyone else is sitting at home. Of all the metrics I’m reporting, attack efficiency is the most tightly correlated to winning so you should expect the evaluations to be pretty good for that metric. My evaluations hold true in P4 conferences, conferences in which many teams receive at-large bids to the NCAA tournament. In conferences that receive fewer bids, even being in the top third might not be enough.
In closing, I’ll remind you that the analyses I’m using are strictly descriptive, they only tell you what Big 12 teams did against each other this season. These analyses are not normative, they do not tell you what you should do with the information. The course of action for our team will be determined by the coaches and players in the coming days and months. All I’ve done is give them an accurate description of where we’re starting from.
I’ll be presenting at the AVCA convention next month and I hope you can attend both the convention as a whole and my sessions in particular. I now have two sessions! The first is called “Music and Magic: Ideas for Coaching, Planning, Managing, and Creating” and is scheduled for Saturday, 12/21 at 9:00am. The second session, scheduled for Saturday, 12/21 at 11:30am, is called “Risk _____ to Win _____: Identifying and Managing Competitive Opportunities”.
