Product Decision Analyst: Evidence Review for Key Strategic Choices

This document evaluates Swing Catalyst's five most consequential product decisions through the lens of a senior data scientist at a product-first technology company. Where A/B test data is unavailable, we assess the quality of available evidence, estimate effect sizes, assign confidence levels, and recommend follow-up data collection. All numbers are from canonical-facts.yaml or the cited source documents.


Framework

For each decision, we score:


Decision 1: Hardware vs. Computer Vision

Question: Should Swing Catalyst invest in force plate hardware (kinetics) or shift to pure computer-vision-based analysis (kinematics)?

Evidence Review

Supporting force plates:

  1. Physics is non-negotiable. Cameras measure position (kinematics). Force plates measure force (kinetics). These are fundamentally different physical quantities. The best published multi-camera lab-grade markerless systems estimate ground reaction forces with 5–12% error on the easiest axis (vertical); medial-lateral GRF — the most important axis for rotational sports like golf and baseball — has the highest error rates. [source: hardware-vs-cv-thesis.md, 2026-03-20]
  1. ML estimation is parasitic on force plate data. OpenCap's LSTM-enhanced GRF estimation models require force plate training data. Camera-based GRF estimation cannot exist without force plates as the ground-truth reference. [source: hardware-vs-cv-thesis.md citing PMC, 2024]
  1. Industry adoption is accelerating. NBA: ~87% using VALD ForceDecks. EPL: 100% VALD. NCAA Power 5: 90%+. NFL Combine: Hawkin Dynamics is the official partner. [source: hardware-vs-cv-thesis.md, 2026-03-20]
  1. FTV Capital invested in VALD in September 2024 — a $6.2B growth equity firm put money into the world's largest force plate company while AI camera solutions existed. If cameras were about to displace force plates, this investment would not have happened. [source: market-landscape.md, competitive-landscape.md]
  1. SC's 23/30 MLB teams chose force plate hardware specifically because ball tracking (Rapsodo, TrackMan) and bat tracking (Blast Motion) exist but don't measure the ground forces that cause hitting mechanics. [source: canonical-facts.yaml, Tucker Nathans, 2026-03-20]

Supporting computer vision:

  1. SC is one of 4 competitors (out of 19 tracked) without AI features. 15 competitors have AI. [source: competitive-landscape.md, 2026-02-10]
  1. SC has zero mobile/range presence. Sportsbox AI (now backed by Bryson DeChambeau + Google Cloud/Gemini) bridges all four market quadrants. [source: competitive-landscape.md, 2026-04-07]
  1. The Tier 3 consumer segment ($136.5M TAM) is software-only — it requires mobile, not hardware. [source: bottom-up-tam-model.md, 2026-03-20]

Evidence Quality: Strong for hardware thesis; Strong for CV-as-complement (not substitute)

Effect Size:

Confidence Level: High. The physics is not ambiguous. This is not a close call.

Recommendation: Force plates AND computer vision, not one or the other. Force plates remain the irreplaceable core product. Computer vision (markerless MoCap) is the additive layer that opens new segments. SC's roadmap combining both (force plate kinetics + CV kinematics, synchronized) is the correct thesis. The Lane 1 mobile-first app (Q4 2026 beta) should be built on top of force plate data for studio sessions, with CV only (no force plates) for range/mobile sessions where force plates are impractical.

Follow-up Data Collection Needed:


Decision 2: Full Swing Bundling

Question: How aggressively should Swing Catalyst invest in the Full Swing Golf (FSG) bundling partnership?

Evidence Review

Key facts:

Revenue model (Base case at 50% adoption, $25/month OEM rate): [source: fullswing-bundling-model.md]

Year Incremental Revenue (HW + SW)
Year 1 $720,000
Year 2 $936,000 (cumulative ARR)
Year 3 $1,152,000 (cumulative ARR)

By Year 3, FSG bundling alone could represent ~645K of new ARR — pushing software mix from 26% toward 33–35% of total revenue [source: fullswing-bundling-model.md].

Risks:

Evidence Quality: Moderate. Revenue model is credible but hinges on two unconfirmed steps: (1) Carlsbad test success and (2) commercial agreement. Toronto data is one data point.

Effect Size: Base case $720K Year 1 incremental revenue is ~13% of current total revenue ($5.5M). [source: fullswing-bundling-model.md] This is meaningful but not transformational in Year 1. The 3-year cumulative effect (~$2.8M total HW + SW) is significant. [source: analyst estimate] Back Nine overlay (300 new locations × 6 bays × 50% adoption) adds an additional $270K ARR on top. [source: analyst estimate]

Confidence Level: Medium. The relationship is real and warm. The risk is execution — whether FSG's commercial team approves the bundle.

Recommendation: Pursue aggressively as a top-3 commercial priority. Specific actions:

  1. Close the SDK agreement before any bundling commitment (legal protection is non-negotiable)
  2. Offer FSG a zero-cost pilot batch (25 units) to generate internal proof of concept for their commercial team
  3. Leverage the Keith Bank / KB Partners overlap: use the FSG commercial partnership as a signal when pitching KB Partners for investment
  4. Set a decision checkpoint at Carlsbad test: if "yes," proceed to commercial terms; if "no," pause and understand the blocker

Follow-up Data Collection Needed:


Decision 3: MLB Expansion vs. Golf Doubling Down

Question: Should Swing Catalyst concentrate resources on expanding in professional baseball (MLB/MiLB) or defend/deepen in golf?

Evidence Review

Baseball data:

Baseball TAM vs. Golf TAM:

Segment TAM SC Current Rev Penetration
MLB/MiLB/College Baseball $8.2M ~$430K ~5% of full TAM
Golf Tier 1 $118.5M ~$3.5M+ ~85% of Tier 1
Golf Tier 2 $212.8M Declining ~40% (declining)

Critical insight: Baseball's TAM ($8.2M professional) is smaller than Golf Tier 1 alone ($118.5M). [source: bottom-up-tam-model.md] However, baseball has higher stickiness (23/30 MLB teams validate the product with the highest authority customers in the world) and lower competition risk in the short term. [source: canonical-facts.yaml, 2026-03-20]

Evidence Quality: Strong. Revenue and penetration data are confirmed. TAM model is well-sourced.

Effect Size:

Confidence Level: Medium. Baseball is the credibility anchor, not the revenue engine (yet).

Recommendation: Baseball is the proof point, not the primary growth engine. Continue deepening MLB relationships (Tucker Nathans focus), resolve Bertec conflict with written account protection agreement, and begin systematic MiLB outreach (standardized package, lower price point). Do NOT sacrifice Golf Tier 2 investment for baseball expansion — golf revenue is 89% of total. [source: financials.md] The right framing for investors: "We are the MLB standard. That credibility transfers to our golf business — a market 14x larger." [source: bottom-up-tam-model.md]

DATA GAP: SC does not have a published NPS or renewal rate specifically for baseball customers. Tracking MLB renewal rate and expansion revenue (upsells within existing MLB accounts) would strengthen the retention story.


Decision 4: Home Tier (Consumer Product Entry)

Question: Should Swing Catalyst invest in a consumer-facing product (Home tier, mobile app) before proving Tier 2 market fit?

Evidence Review

Supporting consumer entry:

Against premature consumer investment:

Evidence Quality: Moderate. Consumer TAM is real; SC's ability to capture it without a mobile app is speculative.

Effect Size: Software-only consumer tier at scale (2% penetration of 700K users = 14,000 users × $195/year) = $2.7M incremental ARR. [source: analyst estimate] That requires a working mobile product and 1-3 years of market development investment.

Confidence Level: Low for near-term consumer entry; High that this is the right long-term direction.

Recommendation: Do not divert resources from Tier 1/Tier 2 and the Lane 1 mobile product to a separate consumer push. Lane 1 is the consumer product — it serves both Tier 2 coaches and their students. Build it well, ship Q4 2026 beta as planned, and the consumer segment will follow naturally via coach-athlete network effects. Consumer-direct marketing is a 2027+ initiative. Keep the existing Home tier as-is; improve churn retention before expanding consumer acquisition.

Follow-up Data Collection Needed:


Decision 5: Geographic Expansion — APAC vs. Europe

Question: Should Swing Catalyst prioritize APAC growth (currently strong at 19%) or address European underperformance (7% despite 10M+ golfers)? [source: canonical-facts.yaml, 2026-03-20]

Evidence Review

APAC signal (19% revenue, strong growth indicators): [source: canonical-facts.yaml, 2026-03-20]

European underperformance (7% revenue, 10M+ golfers): [source: canonical-facts.yaml, 2026-03-20]

Revenue per golfer calculation:

Europe and APAC have roughly equal revenue-per-golfer ratios — both are at ~25% of the North American capture rate. Neither market is being effectively penetrated today. [source: analyst estimate]

Evidence Quality: Moderate. Revenue data confirmed; underlying drivers of APAC success vs. European weakness are not well-documented.

Effect Size:

Confidence Level: Medium. APAC has demonstrated organic traction; Europe requires active investment to compete against GASP.

Recommendation: APAC is the higher-ROI near-term geography because traction already exists — SC just needs to capture it. Prioritize localization (Japanese, Korean language UI, local pricing in KRW/JPY) and 1–2 regional resellers in Korea and Japan. European investment should focus on the UK first (English-language, PGA/WGAE connected, GASP's weakest flank) before continental Europe. Assign a specific European revenue target as a gate before committing a dedicated EU sales hire.

Follow-up Data Collection Needed:


Revenue Impact Summary

Decision Annual Revenue Impact (Base Case) Confidence
Hardware + CV combined roadmap Protects $3.5M+ existing Tier 1 + opens $136.5M consumer TAM (2027+) High
Full Swing bundling (Year 1) +$720K Medium
MLB expansion (MiLB + D1 base) +$500K over 2 years Medium
Lane 1 consumer product (2027) +$2.7M ARR at 2% penetration Low (depends on delivery)
APAC vs. Europe (APAC-first) +$1.4M incremental if rev/golfer reaches 50% of NA rate Medium

Critical Data Gaps Across All Decisions

  1. Free trial conversion rate — unmeasured. Without this, CAC models are incomplete. [source: business-kpis.md]
  2. Cohort retention curves by tier — not available. This prevents identifying which subscription vintage is churning fastest.
  3. CAC by segment — reported as aggregate $603.25 (2024). Cannot optimize acquisition spend without segment-level CAC. [source: business-kpis.md]
  4. Baseball renewal rate — not reported separately. The MLB story requires a verified retention number.
  5. APAC distributor revenue breakdown — 12 distributors are active but revenue attribution is not documented.