Each year, baseball players sink countless hours into perfecting their swing hoping to one day reach the next level and fulfill their potential — whether that next step is making the high school team, earning a Division I scholarship, or climbing their up the minor leagues to one day make Major League Baseball (MLB). But […]
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Each year, baseball players sink countless hours into perfecting their swing hoping to one day reach the next level and fulfill their potential — whether that next step is making the high school team, earning a Division I scholarship, or climbing their up the minor leagues to one day make Major League Baseball (MLB).
But with thousands of athletes sharing the same goal, it’s harder than ever to not only succeed, but to get discovered. That realization led Perfect Game, a nationally recognized leader in youth baseball and softball for its scouting service and more than 8,600 live events each year, to partner with K-Motion, the technology-driven company that offers end-to-end training solutions for athletes in golf and baseball via cloud-based products.
What followed was the creation of PG Tech, a joint venture between the two companies.
“Brad and I got together and said, ‘Let’s develop a way to take something done for the most elite players in the game and give access to a broader community,’” said Steve Diamond, CEO of K-Motion, speaking of Perfect Game CEO Brad Clement.
“I think what happened is we saw a need in amateur baseball to go to the next level in terms of data for baseball,” he added. “Originally, the statistics to look at were home runs and RBIs. Then people, like Perfect Game, started looking at external numbers like exit velocity of a ball or spin rate of a pitch. And then we both saw that those are artifacts, and if we could put those artifacts together with cause data from 3D motion capture and high-speed video, then we would be able to provide people with a full picture of cause and effect.”
This idea of cause and effect allows an athlete to understand what is happening and why it’s happening. In addition, the technology helps athletes review swing results online, helping them isolate and improve aspects of a swing.
Each PG profile page details the hitter’s signature kinematic peak speed sequencing pattern, referring to how a batter generates and transfers speed throughout the body.
Hitters have various swing types — for example, some reach peak speed with their pelvis first, then arm and torso, before finally the hands — but that isn’t true for all hitters, and there isn’t a one-size-fits-all correct answer for young athletes. So instead, the PG tech tries to aid a hitter in customizing a swing to fit the batter’s needs.
The profile will show the user the rotational velocity for each of the four body parts and from one segment to the next in the swing. It shows other information as well, like progression charts over time, slow-motion video and single-game stats.
When a hitter walks into a Perfect Game batting cage at a showcase, they’ll have high-speed cameras, a launch monitor and a radar unit at their disposal. Before they begin, biomechanic specialists will attach K-Motion 3D motion capture sensors to the hitter and hand a bat with a built-in Diamond Kinetics sensor. Once properly equipped, the batter will hit five balls off a tee before uploading data to the player’s profile.
More than 4,000 players sampled the technology at Perfect Game events during 2021, but players will use the technology full-time in 2022.
PG Tech incorporates technology from K-Motion (3D data), Edgertronics (high-speed video), Pocket Radar (ball data), Diamond Kinetics (bat data) and TrackMan (launch monitor data) in its equipment.
“There may be better technology next year or two years from now to supplant something that’s in there now, and we want to be best in class with all those elements,” said Mr. Clement. “That’s the only thing that can give us the best platform.”
With similar equipment already trusted by 25 MLB teams and the Baltimore Orioles choosing K-Motion as a player development partner, PG Tech is now the most streamlined, least fragmented option for amateur athletes on the market, said Mr. Clement.
The push toward utilizing data strategically in sports has only grown in recent years, notably after the hit movie “Moneyball” was released. In the film (based on actual events), Brad Pitt plays Billy Beane, a general manager for the Oakland A’s who challenged the status quo by overhauling how players are evaluated using data analysis. Although heavily criticized by his coaching staff, professional scouts and the media at the time, the change turned the perennial underdogs into MLB contenders.
Despite PG Tech’s heavy reliance on data, the aim is for it to be a complementary tool for the best coaches and scouts — not a burden that eliminates the need for good player evaluators.
So far, the technology has ringing endorsements from trusted names in baseball like Bill Bavasi, former general manager for the Anaheim Angels and Seattle Mariners; Jerry Ford, former collegiate coach and scout for the Minnesota Twins; and Bob Fontaine Jr., a former scouting director for the Angels and Mariners who signed superstars like Randy Johnson and Tony Gwynn. Mr. Ford and Mr. Bavasi work for Perfect Game in various capacities.
MLB all-star and World Series winner Luis Gonzalez also credits PG Tech for helping his son, a Perfect Game all-American in 2016, improve his game.
Today, batters receive crucial insights from the data collected, but the application of PG Tech is not limitless. Pitcher data is rarely collected, other than during limited times and confined to the highest level, said Mr. Diamond.
“We’re just not as far along in the process with pitching as we are hitting, but we know that will be valuable,” said Mr. Clement. But, he added, “We know the holy grail is taking steps forward to using it in games.”
Although PG Tech was used in live-action with major league coaches and scouts in a tech trial game, the implementation is not quite ready yet — although Mr. Diamond believes that day will come.
“We’ve got a lot of ideas about adding technologies to the datasets,” he said. “And one of the big challenges is representing the data in ways that are actionable to people. It’s going to be a process of iteration that will hopefully take some uncertainty out of player development.”
