Category Archives: Player Evaluation

Testing the Axe Bat’s claims

Collaboration with Jeff Long and Dan Kopitzke

To date Baden Sports, the parent company of Axe Bat, says it has backed up these claims through ergonomic and biomechanical research. The most extensive study on their product, completed by a team at UCLA, exemplifies much of their support for these claims. You can read the results of that study as it applies to the claims above on their website here, and you can also read more details from the full study here.

We wanted to take it a step further though, performing an independent study in a real world setting. Specifically, we wanted to look at whether the Axe Bat stood up to the performance claims that they make.

Read the rest on Baseball Prospectus (my first article there!)

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2016 college baseball season preview

Last year, I introduced my open-source college baseball database (which I’ve recently updated), and showed a few example applications. I looked at win probabilities, how the new flatter seams helped increase offense, the stolen base breakeven point, and the value of bunting (honest).

But this time, I want to use someone else’s data. Chris Long (now with the Detroit Tigers) has his own collection of useful college baseball tools on his GitHub. Let’s use them to generate a season preview.

Read the rest on Beyond the Box Score

GPS-based athlete tracking systems: A primer

But there’s another way for teams to use technology to gain an edge: by keeping their best players healthy and in those big games. This requires a separate system, especially on large squads like football teams where it would be impractical to collect and process the amount of optical data needed to capture everyone’s movements across all activities. As a result, systems based on global positioning system (GPS) technology are used in practices and rehab by a wide range of teams across all major sports.

Read the rest on TechGraphs

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Combining Technologies to Measure Swing Development

As hitters develop, their mechanics evolve over time into a swing that both shares many commonalities with other players and is unique to their own game. But tracking a player’s progress on that journey to a consistent swing has always been tricky. Scouting and video analysis can give players a sense of how repeatable their mechanics are, but these are expensive, time-consuming, and limited to players at the highest level, whom we would expect to already have the most consistent mechanics.

Enter technology. Technological developments, including inertial bat sensors and camera-based ball tracking systems, should make it possible to develop a quantitative measure of consistency readily available to a wider range of players, with a wider range of abilities. This will allow young hitters to better measure their progress while also giving scouts and coaches a tool to judge prospective players.

In this article, we look for a way to quantify that relationship between consistency and hitter quality. We measured over 1,500 individual swings from 25 hitters, ranging in age from Little Leaguers to NCAA Division 1 players. We also collected different kinds of swings from each hitter, having each player hit off a tee and a pitching machine, with the goal of hitting first for power and later for contact.

Read the rest in The Hardball Times Baseball Annual 2016

(Collaboration with Dan Kopitzke, K-Zone Academy, Apex, NC)

SmartKage helps scouts, teams evaluate players

“It’s analogous to a physical SAT,” Scannell says. “And if you take it multiple times, just like the SAT, we combine your best scores in each area. It’s not about consistency, it’s about capability.

Once the explanation is over, a few taps on a touch screen start the automated measurement process. The system has been designed to be completely automated. Aside from tapping “next” on the touch screen, no human intervention is required, though Scannell adds the occasional explanatory detail or words of encouragement.

Read the rest at TechGraphs