MUMustard Financial Model
AI/ML Startup Financials (Free Excel Download)
AI-powered sports coaching app using computer vision and mental performance training to make elite coaching accessible to youth and amateur athletes.
professionals from Deloitte
Used by professionals from
About this model
Mustard is a sports-coaching platform that uses smartphone computer vision and mental-performance training to bring elite coaching to youth and amateur athletes. Its sensorless app analyses motion against a biomechanics database built from 40 years of Tom House's work, then supplies report cards and drills.
The product has a freemium consumer app, a paid premium layer for coaching and mental-training content, and team licenses for professional, NCAA, high-school, and club organisations. It also identifies future data licensing and a potential FocusBand hardware partnership, without disclosing pricing.
The model follows downloads, activation, free-to-paid conversion, subscription churn, and content usage, then adds organisation contracts and renewals. It tests consumer acquisition cost, software gross margin, data-licensing timing, engineering and marketing investment, operating burn, and runway under adoption scenarios.
A turnkey financial model
Live formulas, no hardcoded values
Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.
All assumptions in one tab
Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.
Statements always balancing
For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.
Distinct schedules for clarity
Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.
No hidden macros or external links
There are no unexplained external workbook links or macros to undermine auditability or portability.
Changes flow through the model
Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.
About Mustard
getmustard.com
How to build a detailed financial model for Mustard
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Mustard model - distilled from its pitch deck and publicly available information.
Product & value proposition
Three-part suite:
- B2C Freemium App - smartphone camera captures motion; proprietary AI engine (built on 40 years of Tom House biomechanics data) delivers report cards and prescriptive drills. Sensorless, computer-vision-based.
- Mental Performance Training - in-app protocols curated by Jason Goldsmith and hall-of-fame advisors; optional integration with FocusBand EEG headband for real-time neurofeedback.
- B2B2C Coaching Organizations - motion analysis dashboards for pro, NCAA, high school, and club teams; data licensing to orgs (Hawk-Eye data integration mentioned).
Value prop: democratize elite coaching currently costing families ~$6,000/year and available only to the privileged few.
Market
All figures from slide 8 image, confirmed visually:
- $77.6B - Youth Sports Market Size by 2026 (broadest TAM)
- $14.7B - Spent annually on mobile app subscriptions for sports & fitness instruction by 2026 (app-layer SAM proxy)
- $4B - Spent in sports analytics, scouting, and team performance analysis by 2022 (B2B segment)
- No SOM or market-share estimate provided. No CAGR stated.
Sources cited in deck: Youth Sports Market Shares, Strategies and Forecasts Worldwide 2019–2026; Sports Analytics Market Growth, Marketwatch; Global Wellness Summit, Pew Research.
Revenue model
Deck describes business model structure but gives no pricing figures:
- B2C Freemium - free tier (motion capture + basic report cards) with implied paid subscription for premium coaching content, drills, and mental training programs. No price point disclosed.
- B2B2C / Team licenses - selling Mustard platform access to coaching organizations at pro, NCAA, and youth levels. No per-seat or per-org price disclosed.
- Data licensing - future revenue stream; licensing aggregated biomechanics data to third parties (e.g., Hawk-Eye). Not operational at time of deck.
- Hardware partnership implied (FocusBand) - revenue share or referral likely, not stated.
Competition / moat
Not explicitly named. Moat articulated through:
- Proprietary IP: 40-year biomechanics database assembled by Tom House - described as "most extensive in the world."
- Founder credibility: Tom House personally coached Brady, Brees, Nolan Ryan, Randy Johnson, etc.; Jason Goldsmith coached Justin Rose (2016 Olympic Gold), NBA/NFL/MLB/Olympic teams.
- Tech pedigree: CTO Kevin Prince was VP at MLB; Carlos Dietrich built Statcast; Kielan Prince was PM at Hawk-Eye.
- Sensorless approach (phone camera only) - implicit competitive advantage over hardware-dependent systems.
- No direct competitors named.
Team & funding ask / use of funds
Team:
- Tom House - Founder; 40+ years MLB/NFL, PhD, personal coach to Brady/Brees/Ryan et al.
- Jason Goldsmith - Founder & President; high-performance mental coach; Air Force veteran; coached 6 Major champions.
- Rocky Collis - Co-Founder & CEO; co-founder of re-inc. (VC-backed); former Boies Schiller attorney; Cornell / Georgetown Law.
- Luke Collis - Co-Founder, Launch COO, Head of Product; former pro QB (AFL, 4 championships); field organizer for Stacey Abrams.
- Kevin Prince - CTO / System Architect; former VP of MLB Emerging Technologies; built Statcast infrastructure.
- Carlos Dietrich - Founding Engineer; built Statcast player tracking for MLBAM; PhD, NYU Tandon.
- Jordan Kutzer - Head Product Designer; first employee at Strivr (VR training, $150M+ valuation); Stanford grad.
- Marilou McFarlane - CMO/CRO; former President STATSports NA; former CEO Edufii/Coach Now (acquired).
- Kielan Prince - Head of Product Management; former PM at Hawk-Eye Innovations (MLB teams).
- Steve Nelson - Founding Advisor; co-founder Carbon3D ($2.4B valuation); co-founder re-inc.; former VC.
Advisors: Mia Hamm, Drew Brees, Cam Cameron, Mike Candrea, Kevin Kirk, Tom Penn, Reid Ryan, Fred Whitfield, Anson Dorrance, Meghan Klingenberg, Adam Dedeaux.
Recommended financial model
- Archetype + why: Freemium Consumer App (B2C SaaS) with B2B2C revenue layer. Primary revenue engine is subscription (monthly/annual) unlocked from a free-to-download app; secondary engine is recurring org/team licenses. This mirrors Peloton, Strava, or Hudl model - freemium drives top-of-funnel, paid tier monetizes engaged users. A full 3-statement model is warranted once the company has unit economics, but at this pre-revenue stage a driver-based revenue buildout + P&L is the right starting point.
- Forecast horizon & granularity: 5 years (2021–2025), monthly for Year 1, quarterly for Years 2–3, annual for Years 4–5.
- Key drivers & assumptions:
- App downloads / installs per month
- Free-to-paid conversion rate
- Monthly subscription price (B2C)
- Annual subscription discount
- Monthly churn rate (B2C)
- B2B2C org accounts (teams/leagues)
- B2B2C ACV (Annual Contract Value per org)
- Gross margin (software)
- CAC (B2C paid)
- R&D / engineering headcount
- Data licensing revenue
- Youth sports TAM = $77.6B by 2026; mobile sports app SAM = $14.7B by 2026; sports analytics segment = $4B by 2022 - used as market ceiling checks, not direct drivers.
- Scenarios (Base / Bull / Bear - which variables flex):
- Bear: Slow consumer adoption (conversion 3%, churn 6%), B2B2C pipeline takes 18 months to close, no data licensing in horizon.
- Base: Moderate conversion (5%), churn 4%, B2B2C 8 orgs by end of Year 1 scaling to 50+ by Year 3.
- Bull: Strong viral growth via Drew Brees/Mia Hamm social reach (downloads 2–3x base), conversion 8%, enterprise deals close early.
- Required sheets / outputs:
- Assumptions & Drivers (all inputs in one place)
- User Funnel (downloads → free users → paid subscribers → churn waterfall)
- B2B2C Pipeline (org count × ACV × renewal rate)
- Revenue Build (B2C subscription + B2B2C licenses + data licensing)
- P&L (Revenue, COGS, Gross Profit, OpEx by function: R&D, S&M, G&A, EBITDA)
- Headcount Plan
- Cash & Runway (burn rate vs. raise; critical given no funding ask in deck)
- Scenario toggle (Bear / Base / Bull)
- Dashboard / Summary (KPIs: MRR, subscriber count, org count, gross margin, runway)
Frequently asked
Is the Mustard financial model free?+
Yes. The Mustard model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.
What's included in the model?+
A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.
How was this model built?+
It was built from Mustard's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.
Can I change the assumptions?+
Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.
Have more financial modelling questions? Contact us
Created by ex-finance professionals
Hey, I’m Alex and I created Finamodel.
Over my years in the finance industry I kept building the same models over and over again. Same structure, same assumptions, different logo. So I started building frameworks to turn them into clean, reusable templates.
Every model here is one I’d actually use for a client, and I personally vet each one before it goes up.
I’m not an expert in every industry, but I’ve built enough models to know what belongs in one. And when something is completely foreign to me, I reach out to my network for experts to work on our models with us.
Having a template library on hand cuts a first build from hours to minutes.
Need help finding your model? You’ll find me in the Finamodel app!
Other AI/ML Startup Financial Models
Browse another startup in the same category.
AI Rudder
AI Rudder provides multi-lingual conversational AI for B2C customer engagement - automating outbound and inbound voice/chat interactions at scale.
Aisera
AI Service Experience platform that automates IT, HR, and customer service workflows via conversational AI and automation.
Amberscript
AI + human hybrid transcription and subtitling platform targeting B2B customers in Europe
Apheris
Privacy-preserving federated ML platform enabling enterprises to train AI on distributed data without sharing raw data.
Arcane
AI copilot for marketing teams that automates data analysis, reporting, and repeatable tasks via a chat interface and scheduled workflows.
Artisan
AI-powered "digital workers" (branded Artisans) that autonomously perform role-specific tasks - starting with outbound sales - and are delivered as SaaS subscriptions.
Artisan Series A
AI-native B2B SaaS platform consolidating the enterprise software stack with human-like "Artisan" AI employees that automate role-specific workflows
Bigblue
Tech-enabled e-commerce fulfillment platform for European D2C brands - "Amazon-standard" delivery without Amazon.
