The ground doesn’t lie. The pitch or swing starts as force pushed into the dirt. Force goes into the ground which is redirected to the legs, hips, trunk, and eventually the hand/ball. Biomechanics without ground force data is incomplete. However, athletes shouldn’t have to treat it as a separate “force plate day.” KineBase predicts ground reaction forces on any mound, anywhere, on every throw you make.

KineBase Sports x @DeMarini Excited to get KineBase in the hands of the team at Demarini.

KineBase’s Ghost Mode lets you compare captures and data side by side, so you can actually see what changes when you introduce a new training tool, drill, cue, or even months of training. In this example, we compared the same hitter with the Slot Ball vs. without it. The bat tracer shows a noticeably more direct path to the ball with the Slot Ball, while the data gives us another piece of the story: connection. Right Elbow Angle at contact: Slot Ball: 120.4° No Slot Ball: 140.1° That’s nearly a 20° difference, with the Slot Ball producing a much more connected position at contact. Instead of guessing whether a drill, cue, or training tool is creating the change you want, Ghost Mode lets you see it, measure it, and compare it. Train. Capture. Compare. Validate. DM “Assess” for more information on either assessments or getting your own KineBase system.

Tomorrow August 26 from 8:00 to 8:30 AM pacific, KineBase’s Jake Suddreth joins Jeremy Wolf on Open Athletes. They’ll talk all things baseball, how KineBase came to be, and how we see KineBase changing the future of player development by bringing high level biomechanics and performance data into the real training environment. @Jsudds44 🎙️ Tune in live at openathletes.org #KineBase #Baseball #PlayerDevelopment #SportsTech

Build a lab, without the lab. KineBase combines $35,000+ ground reaction force data, $100,000 kinematic data, and $10,000 launch monitor data into one portable system. Starting at $28,000 with early adopter rates available. Email jake@kinebase.ai for more information.

My question is how can we measure it on a force plate mound that is turf and guarantee it’s accurate compared to a real mound. @kinebase ‘s force prediction models are predicted, but through proprietary methods and have been validated to 98-99% as accurate as AMTI. I don’t believe the goal is “accurate measurement” as much as it is accuracy in terms of what data translates to the game environment.

Is “accurate” data actually the goal? We don’t believe that just because a product’s ability to measure is 100% accurate that it represents true data. If the environment is not the same as the environment a player would be in during a game, output and data for both kinematics and ground reaction forces will never perfectly display what it would in a game. KineBase’s predicted ground reaction forces are roughly 98% accurate to an industry leading force plate mound for frontal, lateral, and vertical forces (lead and trail foot)… the only difference is we can do it on a clay mound.

Last day in house at @PDPAthletics yesterday for New Mexico State LHP @BradynBarnes5 who had a sick summer capped off by an electric Live-AB session. Bradyn topped out at 91.4 during his first pen of the summer. We spent the first few weeks working on how he moved based on his @kinebase motion capture and putting him in a position to allow the back hip to internally rotate. This helped improve his direction allowing him to produce more force behind the baseball. With this, the fastball shape started to improve and create more IVB on average. Once Bradyn had a more consistent FB profile, he added a one-seam sinker to utilize seam shifted break and create more arm side run. He also improved the slider velo getting it up as high as 90mph. Down the stretch once he was moving more efficiently, he started letting it rip. He averaged over 92mph and was up to 95.5mph multiple times in his last pen and live. Bradyn put in some incredible work this summer and looks set up to be dominant this next season.

Set up a demo for your organization: ro.am/KineBase

You don’t need an 8+ camera biomechanics lab and a force-plate mound that costs $100,000+. But you don’t have to settle for iPhone-quality motion capture either. @KineBase gives you portable, lab-quality biomechanics with predicted force data at less than 1/3 the cost of traditional lab-grade systems. 3D kinematics. Predicted GRF. Joint loading. Muscle segment activation. Force vectors. Lab-quality data without the lab costs. Don’t settle for less. Set up a call for more info: ro.am/KineBase

Force plate mounds aren’t as accurate as they want you to believe. While the data is accurate, the situation isn’t. A pitcher can’t reliably move at their maximum speed and force output throwing on a surface that shifts under the load. This is why @kinebase predicted model will actually be a more realistic representation of ground reaction forces because you can throw on a real mound. Real data in a real environment.

Preston Abel gained 3mph this summer, and all 3mph came in one bullpen with one cue. Leave the back foot attached to the rubber. It helped him shorten his stride length and avoid his back leg collapsing on his front. @kinebase gives data in real time to make corrections in real time. Dm INFO to set up an in-person assessment or a live demo for your organization.

No force plates. No EMG. No additional sensors. KineBase turns movement into actionable data visualizing segment activation as a real-time heat map, joint contact loads, and force vectors directly on the athlete’s avatar. DM to set up a demo for your team.

One man R&D team for @kinebase Impact locations within .6 inches on average. Exit velocity/launch angle/direction within 1mph/1° of both a stalker radar gun and TrackMan. Kinematic data on par with markered systems. Still offering early adopter pricing.

While generally this may be true, @kinebase will actually track it to provide personalized data for every swing. Kinematics, bat path, how the hands control the bat, how well the hitter steers the barrel, and every other aspect of the bat/ball/body.

The baseball injury epidemic isn’t caused by one problem, so it won’t be solved with one metric or workload model. For years, baseball has tried to manage injury risk by building workload models on incomplete data. Pitch counts, velocity, innings, elbow torque workload sensors, and isolated biomechanical metrics all provide pieces of the puzzle, but none tell the full story. At @kinebase , we’re taking a different approach. By combining estimated joint stress, predicted muscle segment activation, markerless kinematics, predicted ground reaction forces, and performance outputs into a single system, we can evaluate how an athlete moves, what loads they’re experiencing, and whether mechanical changes are actually sustainable. The goal isn’t to eliminate risk, baseball will always carry risk. The goal is to make better-informed decisions based on a more complete picture of the athlete. Because the future of injury prevention won’t come from collecting more disconnected data. It will come from understanding how all of the data works together.

Motion capture data delivered 24 hours later doesn’t help athletes make changes in real time. Why wait a day for results to process when you can see data in seconds and provide results to your athletes in between pitches? DM for more info.

Hitting development has long been overshadowed by pitching development from a technology perspective. Not with KineBase. We have added precise impact location on the bat to accurately assess bat to ball skills. It’s not just bat speed, it’s how accurate the bat is to the ball.