Team Profile: Balanced
For the past several months, I’ve been fleshing out the analytics framework I call the Triangle. If you need to get caught up, here’s the 4 main articles that outline the concept of the Triangle, as well as the 3 points of the Triangle.
From this framework, I also build out several Team Profiles. These can be thought of as diagnostic tools. Tell me my weak points, so I can work on them. They are also meant to be profiles of the different ways that teams can be successful. Tell me my strengths, so I can highlight them.
Above all, the point of these tools are to improve your play on the court. Just running the numbers isn’t enough. How is that going to change how you’re going to train? How will it change the strategies you teach your players? Etc
The penultimate post in the series was earlier this month:
And finally, today, we get to the end of the road
Review: What Is A Team Profile?
Using The Triangle to create a Team Profile means to understand which of the factors are relatively strong or weak for that team. If you think about a team that is perfectly average in all three aspects, the triangle would be even on all sides. Equilateral, if you will. But if one aspect is much stronger than the other two, you can imagine that point would move away from the other two, skewing the triangle in that direction. Likewise, if one aspect is much weaker than the other two, you can imagine that point moving toward the other two, skewing the triangle in a different way.
Ultimately, a Team Profile is a visualization that helps coaches connect their team’s strengths and weaknesses to what needs to be done in training.
What Do You Mean By Balanced Profile?
Using the visualization of a triangle, the equilateral triangle, even all sides, is the balanced profile. No aspect of the triangle (Terminal Serving, First Ball, Transition) is significantly stronger or weaker than the other two.
I define a strength as an aspect that is at least a half standard-deviation above the other two aspects. For example, a team that’s a bit above-average in First Ball has a First Ball strength if they are below-average in Terminal Serving and Transition. I define a weakness as an aspect that is at least a half standard-deviation below the other two aspects. For example, a team that’s a bit below-average in First Ball has a First Ball weakness if they are above-average in Terminal Serving and Transition.
I define a Balanced Profile as a team with all three aspects being within a half standard-deviation of the other two aspects. An important note is that this is relative to the overall strength of the team. We’ve seen this before. Nebraska and Pitt had a Transition “weakness” because they were so strong in the other two areas.
How Common Are Teams With A Balanced Profile?
Of the 63 teams in this database1, 20 had a Balanced profile. As
This makes Balanced the most common profile in Power 5 Women’s NCAA volleyball. The last column there is what I call “Balance Index” which basically shows how balanced they were.2 Congratulations Texas A&M, you were the most balanced team in the sample this year!
How Successful Were Teams With A Balanced Profile?
I included (conference) winning % in the above graph, so you can see that for yourself. And indeed, as you might expect with a fairly large sample of teams, you run the gamut from a 1-17 UVA team to an 18-0 Louisville team.3 We see this with most of the profiles and a reminder that this exercise is not necessarily indicating, “which profile is ideal?” but “what do successful teams look like when assembled this way?” Nonetheless, let’s look at a couple more ways of assessing the success of this profile.
A second way of looking at it is to correlate Balance Index with Win %. The correlation between Balance Index and Win % was -0.14, which means that, technically, the less balanced you were, the less you won. Or, the more balanced you were, the more you won. BUT… a 0.14 magnitude of correlation is pretty low. I wouldn’t read much into it.
A third way is to look at tournament success this year. Of the 18 profiles in the Sweet 164, 5 of them5 were a Balanced profile. Since there’s 7 profiles, that’s more than what you expect. Maybe there’s something there! On the other hand, Balanced was also the most common profile. Another way to say it was, “given that you had a Balanced profile in the Power 5 this year, you had a 1-in-4 chance of going to the Sweet 16.” Considering there’s a 63 volleyball teams in this sample, you have a 1-in-4 chance of going to the Sweet 16 by simply being in a Power 5 volleyball team, thus indicating that a Power 5 profile doesn’t seem to convey any particular advantage to tournament success. Whomp whomp.
So What Are The Takeaways?
Again, the continued lesson from this exercise seems to be that there is not one specific profile of success in women’s NCAA volleyball. All 7 profiles had teams that were successful and unsuccessful. All the profiles were represented in the Sweet 166 and, if you factor the offense/defense splits, all Final 4 teams had a different profile.
And this is basic economics tells us anyway, right? If most teams are trying to build one particular type of team, certain players become undervalued, teams build recruiting classes around them and have success. Coaches wanted 6-rotation players. Then some coaches have success putting big arms on the pin and subbing them out in the backrow. Then coaches want outsides who can hit out of the backrow so now they need 6-rotation players again. And around and around in an evolutionary cycle.
I think one of the fundamental decisions you make as a coach is where you lie on this continuum of “Recruit Athletes To My System” vs “Build My System Around My Athletes.” I’m not sure I know any coaches who are 100% dogmatic on either pole, although some are for sure closer to one end of the other. The takeaways from this article series are going to be a little different depending on where you fall on that continuum.
If you are closer to the Recruit Athletes To My System end, then you should be pretty familiar with what successful teams look like in that profile. If you’re going to win or lose by your First Ball Offense, you should be pretty familiar with the standards you need to hit in those categories.
If you are closer to the Build My System Around My Athletes, you probably need to have a broader knowledge of the different profiles. Something like a Midseason Review is probably valuable as well, because your teams might have different profiles from year-to-year. So understanding what shape your team is taking on and what the most successful teams in that profile look like is important.
There’s a bit of the Should Get, Could Get flavor in this sort of thinking:
If you’re a First Ball team, and you lose the first set because you lost the Transition battle, your adjust might look different than if you pride yourself as a Transition team. If you’re a First Ball team, the in-match adjustment might be, “how do we assert ourselves more in First Ball, to compensate for some of the points we’re losing in Transition?” If you’re a Transition team, and you lose the first set by being behind in Transition, you’re probably specifically making adjustments in Transition, because you can’t win if you get beat in your strength.
Next week will be Beach Week as I’ll be down in Gulf Shores for NCAA Beach Nationals. After that, I’ll adjust the focus of the analytics lens one level beyond the broad profiles of the Triangle framework into some of the offensive and defensive specifics. How do you diagnose offensive strengths vs defensive strengths? Within those strengths and weaknesses, we’ll look at a concept called Key Factors and see the sub-elements that compose your offense and defense. Stay tuned!
Drawing here from Big 10, Big 12, Pac 12, ACC, and SEC. I’m also using some VM numbers to pull these a little faster than running separate .dvw analyses for every team. This is going to be slightly less-accurate than the more detailed numbers I provided in my NCAA tournament analysis, but it turns dozens of hours of research into just hours. I’m okay with that trade-off right now.
Measured by comparing the z-scores of the three aspects.
Also, is it me, or has the ACC consistently produced some of the most interesting profile examples in this series? I love it.
An explainer because that’s a little confusing. First of all, BYU wasn’t in this sample because I only pulled from Power 5. (Sorry WCC!) But 3 teams (Nebraska, Georgia Tech, and Pitt) had “double-profiles.”
UCLA, Baylor, Illinois, Ohio State, Louisville.
Except Transition Strength, but I think that’s a small-sample quirk.
How do you calculate Balance Index starting from the z-scores of the 3 aspects?