Sports Science Data Platform

Upward Performance & Physical Therapy integrates physical therapy and performance training as a single discipline, serving 346+ athletes in Grain Valley, Missouri. They had invested in VALD ForceDecks and other biomechanics platforms capturing detailed metrics — countermovement jump profiles, isometric strength tests, balance assessments — but each platform maintained its own data silo. There was no automated way to consolidate results into unified athlete profiles, no mechanism for cross-platform comparison, and no foundation for population-level analytics. Coaches and clinicians who wanted a holistic picture had to manually export, merge, and reconcile data — a process that was time-consuming, error-prone, and couldn't scale past 300 athletes.

Beginning with our Time & Energy Audit, we quantified the problem: staff were spending significant weekly hours on high-drain, low-value tasks like CSV exports, spreadsheet merging, cross-platform athlete lookups, and manual report assembly. We then designed and deployed a customized Sports Science Data Platform that automatically consolidates data from force plates, wearables, and other testing hardware into a single, unified athlete profile. Athletes across multiple systems are resolved to one identity, raw metrics are standardized regardless of source, and role-based dashboards deliver the right view to every stakeholder — coaches, clinicians, athletes, and administrators. The platform is HIPAA-compliant out of the box.

Manual data tasks flagged in the audit were eliminated entirely, redirecting staff time to athlete-facing work. Clinicians now access complete longitudinal performance data within a single profile for faster return-to-play decisions. Coaches generate detailed reports shareable with athletes, parents, and stakeholders. Group analytics and comparative dashboards allow athletes to benchmark against peers. For the first time, Upward can conduct statistical analysis across their full dataset — identifying trends, validating interventions, and making evidence-based programming decisions at scale — all while significantly reducing operational costs.