Athletes often train without clear, objective feedback. Coaching can become overly dependent on personal interpretation. Teams routinely invest in prospects whose measurable tools don't consistently translate to game performance. Today, there is still no universal way to quantify true athletic capacity.
The Problem
- No unified metric for total athletic signal
- Existing tools are fragmented (motion capture, ball-flight data, stat lines, subjective evaluation)
- Development pathways can be inconsistent and influenced by subjective factors
- Non-traditional movers are routinely undervalued despite measurable upside
The Gap
- No standardized score that compares athletes across positions, sports, or eras
- No way to separate pure capacity (signal) from environmental factors (field)
- No clear mapping from mechanics → output ceiling, injury risk, or developmental upside
UBKT is the first attempt to formalize the physics of athletic signal into a single score.
Quantifying the Signal
UBKT measures rotational movement through five fundamental biomechanical metrics.
SEI
Sequencing Efficiency Index
"How efficiently does energy transfer through your kinetic chain?"
Measures how efficiently the body's kinetic chain transfers energy over time. Captures both the order of segment firing (proximal → distal) and the tempo at which they fire. A clean sequence executed too slowly scores lower than one fired at optimal speed.
ASC
Axis Stability Correcting Coefficient
"How stable is your posture under rotation?"
Tracks deviation of spine angle and head position throughout delivery. Higher scores indicate better command potential and reduced injury risk.
RDR
Rotational Distribution Ratio
"Is your power rotational or linear?"
Computes the ratio of rotational power to linear momentum. Identifies mechanical style and predicts spin generation capability. Used as a diagnostic metric and for style profiling, not in the base BSS score.
PA
Perceptual Advantage
"How difficult are you to read?"
Measures how much your movement timing disrupts an opponent's ability to anticipate. In pitching, this includes release point visibility and timing cues. PA amplifies your engine — it doesn't replace it. An athlete with high PA performs above what their physical metrics alone would predict.
CONS
Consistency Index
"How repeatable are your mechanics?"
Measures how repeatable your mechanics are across sessions. Requires multiple data sessions to calculate. This metric helps identify whether performance variance is due to inconsistent execution or external factors.
BSS & SSQ
The five metrics combine into two headline scores: a universal mechanical rating and a sport-specific performance score.
Base Signal Score
BSS (0-100)Universal, cross-sport rating of core mechanical quality. Represents the pure quality of the movement engine, independent of sport context.
BSS = (SEI^0.5 × ASC^0.5) × 100Sport Signal Score
SSQ (0-100)Sport-specific performance score. Contextualizes BSS by incorporating Perceptual Advantage—for pitching, this is POW.
SSQ = BSS × (1 + k × PA), where k = 0.25Velocity Models (As Related to Pitching)
While V1.3 focuses on the Signal, the long-term vision includes quantifying the Field—team context, opposition, and situational pressure.
Performance ≈ SSQ × FSQWhy Baseball as the Initial Testbed
Rotational & Measurable
Pitching isolates rotation in a controlled, repeatable motion — ideal for testing whether these metrics actually work.
Existing Data
Velocity, spin, command — the outputs already exist. UBKT asks whether we can trace them back to a unified input.
No Unified Framework
Lots of data streams exist. None of them talk to each other. UBKT is an attempt to connect them.
Real Stakes
Velocity, health, and development matter to athletes and teams. If UBKT works, it's useful. If not, we learn why.
Pitching is the testbed. If the framework holds here, it might generalize. That's the experiment.
How UBKT Differs
UBKT doesn't replace existing tools—it synthesizes their outputs into a single, interpretable framework.
| Parity | Traditional Coaching Focus on Technique and Output | Modern Data Labs Sports Tech | UBKT Signal & Field Mechanics |
|---|---|---|---|
| Approach | Primarily subjective evaluation | 40+ individual metrics | 4 core metrics → 1 unified score |
| Interpretation | Depends heavily on coach experience | Requires expert analysis | Designed to be interpretable by any athlete, coach, or scout |
| Consistency | Varies across evaluators | Highly accurate but often overwhelming | Standardized across athletes and contexts |
| Scalability | Limited by personnel and time | Data often siloed across systems | Built to integrate with existing tools and expand over time |
| Bias | Personality & logistics | Technology-based blind spots | Physics-based, neutral on physical traits |
Traditional
Primarily subjective, varies across evaluators, limited by personnel and time
Modern Labs
Highly accurate but often overwhelming, data siloed across systems
UBKT
Unified score, interpretable by anyone, neutral on physical traits
Current Status
UBKT V1.3 is a working hypothesis. Here's where it stands.
Framework
The mathematical model is defined. Four metrics, two scores, geometric weighting. V1.3 is complete and documented.
Authenticate
Currently testing against real movement data to evaluate whether the model correlates with known performance outcomes.
Iteration
Refining based on what the data shows. The framework will evolve as empirical testing and accurate data reveals what works and what needs adjustment.
This is an open research project. The goal is to test whether these principles hold up against real data.
The SFM Taxonomy
SFM operates on three levels: the mechanics of movement, the analysis layer, and the speculative frontier.
Primary Field
Measurable Results & Kinetic Proof
- Biokinetics & force transfer
- Rotation sequencing
- SEI, ASC, RDR, POW metrics
Secondary Field
Forensic & Computational
- Diagnostic analysis
- Computational models
- Pattern recognition
Tertiary Field
Speculative & Theoretical
- Early-stage hypotheses
- Narrative models
- Field-effect theories
This taxonomy organizes the broader Signal & Field landscape behind UBKT. V1.3 focuses on the Primary Field—measurable biomechanics and kinetic outputs.
Frequently Asked Questions
If You're Interested in Movement Measurement
This is an open project. If the framework interests you, feedback is welcome.
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Have a question about the framework, the math, or how this might apply to your situation? Happy to discuss.
UBKT is a solo research project exploring whether athletic capacity can be measured through a unified framework. The work is ongoing.
Questions and feedback are welcome.