Sports Models-as-a-Service

Built for pro league
front offices.
Now available for
college athletics.

The same intelligence infrastructure behind NFL, NBA, and MLB front offices — purpose-built for your athletic department, your sports, and the decisions your staff actually makes.

Football MaaS model topology field map

From the team behind intelligence systems at

Three sports. One platform.

Purpose-built model fleets for the three revenue sports that drive your department — each trained on professional-grade data, each ready to deploy for your program.

FootballMaaS — Green Bay 2026 roster plan

Football

FootballMaaS

20 ML models covering pre-snap prediction, coverage geometry, causal defender value, and cap-aware roster construction — built on NFL tracking data.

Try the live demo →
BaseballMaaS — Jacob Misiorowski player detail

Baseball

BaseballMaaS

18 ML models covering pitch intelligence, fatigue tracking, arsenal analysis, and game strategy — trained on a decade of professional pitch data.

Try the live demo →
BasketballMaaS screenshot

Basketball

BasketballMaaS

22 ML models covering player evaluation, load management, injury risk, game strategy, and roster optimization — deployed inside an NBA front office.

Live in NBA · Demo at NACDA Booth 443

The decisions that
cost real money.

Every model in the platform is built around decisions your staff actually faces — not hypothetical analytics use cases.

Sunday night · Transfer portal opens

Is this kid worth the NIL commitment?

Transfer value, injury history, roster fit, and NIL market rate synthesized into a single brief — framed for the person making the call. Not a spreadsheet to scroll through. An answer with evidence behind it.

Athletic Director · Head Coach · NIL Director

Tuesday morning · Budget meeting

Which programs justify their investment?

Recruiting ROI, competitive performance, athlete outcomes, and operational cost models running together. When the numbers tell a different story than the politics, you see it before the meeting — not during.

Athletic Director · CFO · Senior Associate AD

Thursday · 6am before practice

Should she practice full contact today?

Workload ratio, sleep data, injury risk model, and training volume need to talk to each other before the whistle. The platform surfaces a cross-model recommendation before you make the call.

Head Athletic Trainer · Head Coach · Sports Scientist

Signing day · Three recruits, one scholarship

Which one moves the needle?

Projection models, positional need analysis, roster balance, and developmental trajectory scored together. When the model disagrees with the scouting consensus, it tells you why.

Head Coach · Recruiting Coordinator · Director of Scouting

How it works.

Not a tool you buy off a shelf. A custom intelligence stack built around your program, your data, and the decisions your staff makes every day.

1

We listen first.

A structured discovery process with your coaches, trainers, and administrators. We map the decisions that matter, the data you already have, and the gaps that cost you. No assumptions. No demos until we understand your program.

2

We build your models.

A custom fleet of machine learning models shaped around your sport, your data, and your staff. Trained on your information. Calibrated to your decision-making process. Every model traces back to a real conversation with your people.

3

Your stack grows.

The platform gets smarter the longer it runs. User behavior shapes personalization. New questions surface new model opportunities. When frontier technology improves, your entire stack inherits the upgrade. You own the intelligence.

Start the conversation.

No pitch deck. No demo until we understand your program. Tell us what you're working with and we'll tell you what's possible.