AGINT is a structured intelligence graph for NFL prediction modeling: thirteen seasons of game data, line movements, injury context, weather, and settlements, processed through a seven-agent architecture that answers the questions models actually need answered. Audit your edge against it. Train on it. Feed your live pipeline from it. Or query the intelligence directly. Most engagements start with a calibration audit.
Everything AGINT offers sits on the same foundation: a graph that does not just store NFL data, it interprets it. Collection is organized around Priority Intelligence Requirements (PIRs), the specific questions a model needs answered. Each agent writes a direct answer to its PIR, timestamped to the moment it was known and scored for confidence. What comes out is not raw rows but resolved intelligence.
The graph captures game data, line movements, injury context, weather, and bet settlements across thirteen seasons, then layers agent outputs on top: direct answers to questions like starter-availability confidence or whether a line move broke from consensus.
That is the difference between a dataset and an intelligence graph. You are not buying rows to clean. You are buying answers your model can consume, with no look-ahead leakage and a confidence weight on every call.
These are not four separate products competing for your attention. They are rungs. Most relationships start with an audit and climb as the graph proves its value inside your operation.
An independent, statistically rigorous calibration audit of your NFL model. Fifteen analyses that find where your edge concentrates, whether your CLV is real, whether your sample can support it, and whether it has quietly decayed, every finding labeled by the confidence it earns. The wedge: prove the graph's value before you build on it.
Train your model on thirteen seasons of structured intelligence plus PIR outputs from every agent, instead of spending a year assembling and cleaning that pipeline yourself. Backtest against resolved answers, not raw data you have to interpret first.
During the live NFL season the graph feeds your production pipeline two ways: pull the data your model needs on your own schedule, or receive push notifications the moment something matters: line movements, injury updates, and timing signals.
A direct interface to the intelligence itself. Dig into specific questions, starter confidence, line behavior, situational history, through a GUI powered by the same AGINT intelligence that drives every other rung. Currently being scoped.
The hardest part of an NFL model is rarely the model. It is the pipeline underneath: collecting, structuring, and reconciling years of game data, line movements, injuries, weather, and settlements into something you can train on. Build hands you that foundation.
You train and backtest against thirteen seasons of structured intelligence, with the agent layer included, so your features can lean on resolved answers rather than raw signals you have to derive:
Scope and terms depend on what you are training. Start a conversation and we will size it.
A foundation you trained on is only half the value. Deploy keeps the graph feeding your model during the live season, as new data flows in, so production runs on the same intelligence your backtest did.
Two modes, used together or separately:
The result is a production pipeline that does not go stale between your batch jobs and does not miss the move while you are not looking. Seasonal engagement, scoped to your access pattern.
For most operators that is a calibration audit: a low-commitment way to see what the graph can tell you about your own model before you build anything on it. One conversation, no deck.
mj@fanvatic.comAGINT offers customer-funded intelligence and diagnostic services (Analyze, Build, Deploy, and Explore) built on a foundation of publicly sourced NFL data. These services are separate from AGINT Capital fund operations and do not provide picks, wagering selections, or investment advice. AGINT does not disclose its fund's models, signals, or performance through these services. Not financial advice.