From Baseline to Game Day
How Hudy & Jui, the performance team for an NCAA Div 1 women’s basketball team, built a season-long movement intelligence system
Practitioner
Dr. Andrea Hudy & Jui Shah
Setting
NCAA Div. 1 Women's Basketball
Approach
Continuous, athlete-driven monitoring
Duration
Full competitive season
Dr. Andrea Hudy
Director of Performance
30+ years in NCAA Division I. Built programs where practice demands match the chaos of competition, not the control of a lab.
Jui Shah
Sports Performance Assistant
Background in coaching, strength training, and machine learning. Integrates data across platforms to surface patterns before they become problems.
The problem with a snapshot
Dr. Andrea Hudy has spent over three decades in NCAA Division I performance. She knows what a force plate test can tell you, and, more importantly, what it can't.
“Practice must match competition. The capacity we build has to handle the demands of the sport. Not the demands of a lab.”
That distinction - between controlled testing and chaotic, ecologically valid sport performance - is what drove Hudy and her assistant, Jui Shah, to look for something different. Jui, whose background is in coaching, strength training, and machine learning, had been integrating data across multiple platforms. They were after not just a better snapshot, but a continuous read on how each athlete actually moves, day after day, across an entire season.
That's where Plantiga came in.
The lab
A force plate test in a controlled environment
Precise, repeatable — but limited to a single moment. It can't capture how an athlete moves across a season, under fatigue, or in the chaos of competition.
The goal
A continuous read on how each athlete actually moves
Day after day, across an entire season. Not the demands of a lab — the demands of the sport.
Laying the foundation
The season began the way every good monitoring program should: with a baseline. Before the intensity of preseason camp, athletes were introduced to a daily protocol that would define how the team used data all year.
Each athlete ran their own standardized walk test and jump test, independently, before every session. No staff supervision required. The goal was a personal movement baseline for every player on the roster — one that would become the reference point against which all in-season fluctuations would be compared.
Arrive
Athlete picks up their Plantiga pods before the session
Walk test
Self-administered, standardised — no staff supervision needed
Jump test
Baseline jump data captured before every session
Train
Pods worn throughout practice and games
Review
Athlete docks pods and reviews results with Hudy and Jui
But Hudy didn't want testing to feel like testing. One of the persistent problems in applied sport science is the Hawthorne effect: athletes perform differently when they know they're being observed. The solution was to weave the protocol into the daily routine so thoroughly that it stopped being a "test" and simply became what you did when you arrived.
“Everyone has their own movement signature. Like music — everyone has different pitch, tone, and melody. Plantiga helps us find each athlete’s perfect pitch.”
By the time preseason camp was in full swing, the team had a growing, athlete-specific dataset that reflected real fluctuations — the kind driven not just by physical load, but by academic stress, travel, sleep, and emotional state. As Hudy puts it: "Fatigue can be an emotional response," so the walk test became, in effect, a daily mood ring with biomechanical precision.
The signal amid the noise
As the competitive season began, athletes wore Plantiga pods throughout practices and games. The data flowing back to Jui’s analysis pipeline included:
Impact & push-off asymmetry
Side-to-side load distribution across every session
Per sessionAthlete G-Load
Total mechanical load across training and competition
CumulativeAcceleration & deceleration profiles
Propulsion and absorption patterns as they actually occur on court
Real-worldTypical range flags
Individual asymmetry thresholds that trigger review when exceeded
Athlete-specificMovement signature
After 5 sessions, a typical range is established for each athlete across Plantiga's core metrics — a clear picture of how that individual moves
Set after 5 sessionsJui’s role was to quickly pull biomechanical responses from training, to the surface of that data. Her machine learning background meant she could integrate Plantiga's output with data from other tools in the team's arsenal, identifying athletes trending outside their personal norms before those trends became problematic. The daily review workflow was deliberately efficient: flag athletes outside their typical bands, contextualize with Hudy's daily conversations with each player, intervene where needed.
One of the more immediate applications was tracking the acute effects of manual therapy and activation sessions. Walk tests taken before and after interventions showed real-time changes in asymmetry — and, crucially, allowed the staff to track how long those effects held.
“The question we started asking was whether we were turning acute effects into chronic ones. Are we actually changing the pattern, or just temporarily correcting it?”
That question — acute vs. chronic adaptation — became one of the organizing principles of the team's in-season intervention logic.
The case that defined the season
No moment illustrated Plantiga's value more clearly than with one athlete returning from ACL reconstruction.
At approximately 10 months post-surgery, the athlete had cleared all standard return-to-sport criteria. Force plate testing looked good. Clinical assessments were passed. By conventional measures, the athlete was ready.
But their on-court data told a different story.
Plantiga revealed that they were loading their non-surgical leg 20% more than the surgical side during controlled on court sessions — a compensatory pattern that had gone undetected in controlled testing environments. The difference between the weight room and the court, between structured assessment and chaotic sport movement, was exactly where the deficit lived.
CLEARED (10 months post-op)
Standard return-to-sport criteria passed. Force plate: normal.
20% asymmetryON-COURT DATA REVEALS DEFICIT
Loading 20% more through non-surgical leg. Undetected in controlled testing.
Targeted interventionWEEKS OF REAL-TIME MONITORING
Activation, mobility, and strength adjusted. Progress tracked on court, session by session.
Asymmetry narrowingCOMPETITION SUSTAINABLE
Asymmetry down from 20% to under 4%. Cleared in the environment that matters.
<4% asymmetry“Cleared, competition ready, and competition sustainability are not all the same thing. Rehab starts in the weight room and the clinic. But it has to hold up on the court.”
With the asymmetry identified, the team had a precise, trackable target. Activation, mobility, and strength were adjusted. Progress was monitored in real time, in the actual sport environment. Over the following weeks, the impact asymmetry came down from 20% to under 4%.
“We wouldn’t have found it without the on-court data, and we wouldn’t have been able to show her the progress without it either.”
That last point mattered. The athlete could see their own trajectory — not as an abstract clinical metric, but as a number to watch move in the right direction as a direct response to their own effort and consistency.
Athlete-led, by design
Across the season, the single most important cultural outcome wasn't a specific data insight. It was the shift in how athletes related to their own data.
From day one, the protocol was athlete-driven. Players grabbed their own pods before sessions, ran their own tests, docked their pods afterward, and reviewed results with Hudy and Jui. That repeated exposure — daily, across an entire season — built something that performance staff rarely talk about explicitly: health literacy.
“The data is ultimately for the athlete. To understand who they are.”
Athletes started asking questions. What does my asymmetry mean? Why is my G-Load higher this week? What changed after my treatment session? Those questions signal genuine investment, and genuine investment changes behaviour. Athletes who understand their data make better decisions about recovery, sleep, and self-management.
For a generation of athletes navigating increasing financial stakes, academic pressure, travel fatigue, and the scrutiny that comes with elite competition, that ownership matters.
What a season of continuous data changed
The comparison between pre- and post-Plantiga practice isn't abstract. The table below captures the three concrete shifts that defined this season.
| Before | After | Value added |
|---|---|---|
| Day-to-day fluctuations driven by social, emotional, academic, and physiological stressors went undetected. | Daily shifts in typical movement patterns can be easily pinpointed and used to support interventions. | Context |
| Load measures were estimates or only considered centre of mass. | Side-to-side and step-by-step limb asymmetries allow immediate, individualised adjustments. | Precision |
| Data was available to athletes, but not all were invested in understanding it. | Athletes take charge of their own data collection and are invested in what it means. | Health literacy |
A continuum, not a destination
Hudy's framing of performance is worth sitting with:
“Everybody’s on a return to performance continuum. Whether an athlete is eight months post-ACL or fully healthy and preparing for a conference tournament, the question is always the same - are we having a positive impact on consistency and performance?”
A season of Plantiga data doesn't answer that question once. It keeps answering it, every day, in the environment that actually matters.
That's the shift. Not from bad data to good data. From a snapshot to a story — one that begins with a baseline, runs through every practice and game, and ends with athletes who know themselves better than they did before.
Data collection, analysis, and athlete monitoring conducted by Dr. Andrea Hudy and Jui Shah.
