About KarmaEdge.AI
Models, markets, and saying nothing when we have nothing
What we do
KarmaEdge.AI builds sports models and publishes what they produce, alongside the market prices those models are competing with. The aim is narrow and specific: show a projection, show what the market says, and show enough context that you can judge the difference yourself.
We cover NFL and college football game models and player prop research today.
How we make money
Subscriptions. That is the whole model. We take no sportsbook affiliate revenue, we are paid nothing when you place a bet, and we do not sell customer data.
It matters because it decides what the product optimises for. A business paid per referred bet has a reason to publish more picks. A business paid by subscription has a reason to be right, and to say nothing when it has nothing worth saying.
Where the data comes from
Schedules, rosters and results come from public sports datasets. Market prices, betting splits and model inputs come from licensed commercial providers, whose agreements permit us to display the information but not to redistribute it or name them, which is why you will see the data and not their brands.
What we withhold, and why
The system checks its own evidence before publishing. If the data behind a game is missing, stale, internally inconsistent or cannot be tied to a verified fixture, the output is withheld and the page says so.
That is why you will sometimes see “unavailable” where you expected a number. We would rather show you a gap than a confident figure we cannot support. A product that always has an answer is not being careful.
What we will not claim
No guaranteed wins, no invented track record, no testimonials we did not receive. Models are wrong often; published results describe the past and predict nothing. If we ever state a performance figure, it comes from graded records we kept before the outcome was known.
Talk to us
Questions, problems, or something on the site that looks wrong: support@karmaedge.ai. If you think a number is incorrect, tell us — we would rather hear it from you than not at all.