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Advanced metrics and data-gathering devices are able to measure previously unmeasurable basketball quantities from a team's best-performing lineups to the distance a player travels during his time on the court. While many of these systems are still in their earliest stages, we learn new things about the sport every day, even if that progress only extends to asking better questions or understanding the limits of said technology. These things are moving fast, but they have clearly proven their value in a general sense.
Yet several traits remain unmeasurable for the vast majority of basketball evidence. Team chemistry, for instance, is typically thought to be the product of some ineffable process, or maybe just a natural outcome of a group of core players understanding each other's strengths and weaknesses and taking their jobs seriously. In theory, such things cannot be quantified.
In an era of statistical revolution, however, a few researchers are trying to do just that. Jordan White of Hardwood Paroxysm recently spoke with Daniel McCaffrey, the co-founder of SyncStrength, a firm that optimizes athlete training, health, and performance. Here's a sample of their conversation:
With mobile biosensors becoming more ubiquitous, it became possible for us to use biofeedback as a way to measure the impact we were having on teams. This also enabled us to explore the potential of using biological markers of performance and human behavior to measure things that have never been measured before, such as team chemistry. [...]
For years, “immeasurable” traits such as chemistry, heart, hustle and so on have been perceived as just that: unquantifiable. Are you finally able to measure those traits, or do you think there are things we can’t measure?
I think we’re on the right path. These are difficult and complicated subjects that we’re tackling, but we believe over time that our team will get there. Our analytics are built to make sense of this complexity by providing for the inclusion of different modalities of data. By modalities I mean biometric data such as heart rate, sport specific data such as yards, shots or corner kicks and interpersonal dynamics data such as team chemistry. Combining these modalities helps us begin to see a 360-degree view of health and performance and begin to measure what was once immeasurable.
How could a team implement your measurements? You can tell a player to stop shooting from a certain distance, or that he’s better driving left than right, but you can’t tell two players to start liking each other, right?
True. But imagine at the beginning of every season, in addition to game plans, practice plans and health plans organizations had team chemistry plans and strategies. A plan that focuses and concentrates on enhancing team chemistry through building specific team chemistry related skills: communication, emotion regulation, stress regulation, energy management, and mental toughness to name a few examples. All of these skills can be improved upon and help teammates better understand one another and how they perform together.
In addition, by implementing our measurements teams will be able to manage lineups, formations and substitutions ensuring that the team on the field or court has the optimal level of synergy at the right moments in a game or practice. [...]
The two sports you used in the study at Sloan were basketball and soccer. Were the instances of synchrony similar for each sport, or did you find that teams “came together” at different times?
This is unanswered at the moment. We’re trying to definitively answer questions like this by looking at the data more closely.
I encourage reading the entire (relatively short) interview, because McCaffrey comes across as someone who understands that his company's efforts haven't yet led to many conclusions. He's honest about the limiting factors, of which he not surprisingly focuses on teams' and athletes' unwillingness to open up their operations to SyncStrength. While many of the recurring words in his explanations sound like the products of vague and unscientific business management seminars, the approach seems like a classic example of the scientific method. They're testing hypotheses and examining their data as closely as possible.
That's not to say their working theories are perfect. (Although we're obviously working with an incomplete explanation here.) McCaffrey's ideas of teams employing chemistry plans seems like potential overreach, if only because certain things tend to get less fun when they become official activities. The greater idea here is that, even if chemistry is a real thing with tangible benefits, identifying it is very different from creating it. It would appear that creating the optimal chemistry-building scenario is a separate discussion from figuring out if chemistry exists in the first place.
But SyncStrength is doing valuable work, no matter if they change the face of team construction or not. In interrogating a commonly held belief and remaining self-aware of the limits and barriers to knowledge, these researchers are exploring the limits of analytics in an intellectually responsible way. It's possible they'll fail in spectacular fashion, but startlingly ambitious projects often court that level of risk.
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