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GameRun Demo Toolkit

Pitcher Predictive Biomechanics

AI-powered mechanical analysis that projects performance, efficiency, and injury risk.


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GameRun Web Platform 

Our redesigned web platform offers a modern, high-performance experience with clarity, speed, and seamless navigation on any device.


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GameRun Mobile App

See how athletes upload videos, get instant performance breakdowns, and receive data-driven insights to improve faster and train smarter.


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Performance Analytics Reports

Access detailed reports with key metrics and actionable insights for every athlete.


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Performance Analytics Reports

Access detailed reports with key metrics and actionable insights for every athlete.


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See Baseball Analysis in Action

Watch GameRunIQ in action as it delivers real-time feedback on gameplay video and analyzes biomechanics.

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See Ice Hockey Analysis in Action

SWatch GameRunIQ in action as it delivers real-time feedback on gameplay video and analyzes biomechanics.

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AI-Powered Injury Prevention

Can AI predict injury? This video shows how biomechanics flagged injury risk before it appeared on MRI.

View Injury Breakdown


Predict Injuries with AI

See how AI biomechanics detects hidden injury risks before pain or MRI findings appear.

View Injury Breakdown


NTIS Form Submissions

NTIS Form submission data is stored in this sheet in a structured format, capturing all user inputs for easy tracking, analysis, and further processing.

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MLB Pitchers Injury Dashboard


Total pitchers analyzed
25
Anchor Point Analysis
High / very high risk
11
44% of roster
Primary flaw: soft lead leg
18
72% of pitchers
UCL / elbow stress flagged
21
84% of pitchers
Overview
Roster table
Flaw breakdown
Body map
Archetypes
Kinetic chain
Player cards
Injury risk distribution
Very high (2) High (9) Elevated (9) Moderate (4) Low-mod (1)
Primary mechanical flaws
Risk by experience level
Mechanical efficiency vs injury risk
Most at-risk pitchers
Mechanical efficiency leaders
Force profile breakdown
Pitcher Age Arm Exp Risk Primary flaw Efficiency Archetype UCL Fatigue risk
Flaw co-occurrence
Body weight vs avg injury risk
Corrective drill frequency across roster
Injury prediction - likely outcomes
Stress concentration - body map
Head Trunk T-spine Shoulder Shoulder Elbow UCL Elbow Wrist Hips Pelvis/Glute Lead Leg Knee/Block Ankle Foot plant Throwing arm Glove arm High stress 21 / 25
Stress zones - pitcher count
Deceleration quality
Archetype distribution
Fatigue risk across roster
Pitcher archetypes - Full roster
Kinetic chain breakdown - cascade frequency
Timing analysis - arm vs trunk sync
Monitoring recommendations - priority areas
Key metrics tracked across roster