Bringing The Triangle To The Beach
This week is Beach Week at Smarter Volley. I dedicate the first 3 weeks of each month to indoor volleyball and the 4th to beach. If you’re not interested in anything related to beach volleyball, check back in next week.
I’m a big fan of John Mayer. The dreamy eyes. The guitar skills. What’s not to love?
John Mayer the beach player and coach is pretty cool too. Actually, he’s even better than that. You think the guy who sang, “Your Body Is A Wonderland,” could be AVP Defensive Player of the Year? Come on now. And after a great playing career, John’s become a great coach as well. I had the chance to work with him a little as a player, and when he retired to coach full-time as the head coach at LMU, he asked me to bring some of the Moneyball approach to NCAA Beach Volleyball.
How could I say no?
Beach Vs Indoor
To say that beach volleyball was less advanced statistically than indoor volleyball in 2015 (when I started working with pro beach players) is an understatement. When Hugh McCutcheon brought Jamie Morrison on staff from 2005-2008 with the USA Men, almost nobody in the US used DataVolley. Even at the start of the London quad, Jamie was one of the few people doing advanced statistics in volleyball. (Let’s face it, half of the NCAA is still using a version of his match summary sheet.) When I started working with Jamie in 2012, DataVolley was starting to get popular.
I think my contribution was less innovation and more just taking what was being done in the other (read: big money) sports and find ways to translate that into volleyball. And I made some heatmaps that people seemed to like.
The thing is, once people saw the value of analytics in indoor volleyball, the adoption curve went way up, because it was relatively easy to deploy the resources. Indoor volleyball is played… indoors, in an arena, and often the same one that basketball plays in. (Or perhaps, the arena that basketball thinks they are too good to play in anymore) It was easy to set up cameras, get somebody to plug a laptop into the wall and start typing away. When you were done with that, you just strolled down the hallway into the office, uploaded the video, synched your code (let’s face it, this took a while for some of us at the beginning…) and you could start manipulating the data.
Beach offered a whole other set of challenges. First of all, beaches are sandy. Computers don’t like sand. There aren’t bleachers and power outlets. Stats programs were designed for indoor and not beach. And there’s way less money in beach volleyball. That was especially true at the beginning. When beach players are fundraising to try to afford to play to the next AVP event, they aren’t fired up to shell out $1000 for a DV license.
Where To Start
Because of all these factors, when I first started working with John at LMU, the tasks were both simple and incredibly challenging. The most basic knowledge for NCAA-level beach volleyball analytics just wasn’t there. What should sideout % be? How often do good teams at this level miss serves? Does it even matter if they miss serves or not?
From an analytical perspective, these questions are easy to solve. But the logistics were tricky. NCAA beach volleyball is played with 5 pairs from each school playing against each other. Usually all 5 pairs aren’t playing at once, but multiple pairs are. So you need multiple cameras to be turned on, to stay upright for the full match, to be turned off, and their memory cards put into a computer. This ends up being quite a challenge. Most indoor coaches would be surprised at how much NCAA beach volleyball has no existing recording. It’s like trying to watch NBA games from the ‘60s.
Despite that, in my first couple years at LMU, I was able to start gathering data. To this day, I process most of it by hand. (I’m working on some solutions to that) But slowly I started to put a database together and start getting some baselines for success. Basically, I started trying to create the Triangle framework on the beach.
Using The Triangle
The good thing is that this Triangle framework translates well to the beach. In fact, in some ways, I think it translates even better. One of the good thing about beach volleyball is that, “Team,” statistics are so useful. In indoor volleyball, a, “team,” can have a bad serving day while half of the team had a good serving day. On the beach, if, “we,” struggled on defense, that means that, “I” probably contributed directly to that.
(There are of course, some exceptions to this. It’s not uncommon that one player is a strong server and teams struggle to sideout off her serve, while her sideout is low herself, while the other partner is a strong sideout player but a weak server and thus allows a high sideout off her serve.)
In terms of splitting the game up into the three categories:
1. Terminal Serves
2. First Ball
3. Transition
This analysis is very useful on the beach. With only two players serving, and those same two players handling all the serves, the analysis of Terminal Serving is clear. The intermediate and high-level beach game, even more than the indoor game, revolves around First Ball play. And Transition involves both players working together to solve that puzzle.
Translating To Practice
Something that I love about coaching beach volleyball is that it translates very well to constraints-based games. Mayer is one of the best I’ve seen at creating game situations that teach concepts to his players. On Friday, I’m going to post the link to an online coaching workshop we did together on this topic. My role as a consultant with the program has been to analyze each match and provide reports on the strength and weaknesses of each team. The Triangle is the base of that analysis. John then takes that and works with the players to create game structures designed to improve those areas of the game for those players.
Now of course, most of you reading this don’t have a statistical consultant to provide match reports. You might be able to get some statistics on your beach players, but you might not even be able to get that. But even if you can’t do that, you can use the framework qualitatively as a thinking device. Just spend a minute thinking about the pair that you are coaching.
Do they seem to get more aces and/or miss fewer serves than their opponents? Then they are probably positive in Terminal Serves.
Do they seem to kill the ball more often in First Ball and/or stop their opponents more often? At the very least, do they, “Make Them Play,” more often? Then they might be positive in First Ball.
Do they seem to thrive in Transition? Do they get a lot of digs? Are they good at turning those digs into swings and kills? Do they make fewer earns in Transition? Then they might be positive in that area.
Once you have an idea of strengths and weaknesses, you can create practice to highlight them. The simplest way is just by number of reps. If a team needs work on Terminal Serving, how many Terminal Serves occurred at practice? How can you increase that number? How many balls are killed or stopped in First Ball? How can you increase or decrease that number? Same for Trans.
I’ll have some ideas in this blog. Keep reading. Even better, subscribe so you can read all of it.