About Sharksnip

The first sports betting analytics platform built around modelers — Tinker, Marketplace, and Shark Snips Consensus.

About Sharksnip

What we are

Sharksnip is the first sports betting analytics platform that lets you build, share, and earn from your own machine learning models — entirely in your browser.

Most sports betting tools give you their picks. Sharksnip gives you the tools to build your own — and a marketplace to monetize them if they work.

TL;DR for the degens

  • Build, backtest, share ML models in your browser. Free forever for the build side.
  • Marketplace = subscribe to a creator's model ($5–$25/mo) or grab a $5 Slate Pass for one slate.
  • Consensus = weighted aggregate of every opted-in model. The signal nobody else has.
  • Affiliate links + sub fees + 50% marketplace cut are how we eat. Not by selling your data or signals to sportsbooks.

NFL EPA + success atlas — pass/run efficiency, weekly drift, top team EPA per play

A real screenshot from the same data layer that powers Tinker, Picks, and Consensus. No stock images here.

Why we built it

Sports betting has a strange asymmetry. Sportsbooks employ teams of quants with proprietary data feeds, GPU clusters, and decades of pricing history. The retail bettor gets a phone app that highlights "popular bets" and a few news articles. The gap between these two worlds is where every dollar of negative expected value lives.

The handful of tools that genuinely tilt this balance — odds comparison, +EV finders, line tracking — cost $99 to $999 a month and assume you already know what to do with the data. The dream tools — build your own model, backtest it, see if your edge is real — basically don't exist for consumers. They live behind hedge fund walls.

We built Sharksnip because the underlying technology has changed. TensorFlow.js can train real models in a browser tab. Modern compute is cheap enough that "ML for sports" no longer requires a Wall Street salary. And LLMs are now good enough that an "Optimize Weights" button can do real ML work behind a single click. The only thing missing was a platform that lets people do it without becoming PhD quants.

The three products

Tinker — the build environment

Train your own machine learning models on real sports data, in your browser, with no setup. Pick features, choose architectures, run backtests, save what works. Everything runs client-side, so your data and your edge stay yours. Tinker is free forever — no paywall on building.

Marketplace — the creator economy

If your model is good, list it. Other users can subscribe to your model for live picks (you set the monthly price), or grab a one-shot Slate Pass for ~$5 to use it for a single weekend. You earn 50% of every transaction, paid in cash via Stripe Connect. No tier ladder, no royalty chain — just a clean half-and-half split.

Shark Snips Consensus — the wisdom of crowds

Every Monday, Sharksnip aggregates the picks from hundreds of opted-in marketplace models AND opted-in tournament submissions into a single "Consensus" view. Top creators get a 5x weight. Models with bad track records get downweighted or excluded. The result is a signal nobody else has — what a thousand independently-trained ML models think about Sunday's slate.

How we make money — and what we'll never do

We have three revenue streams:

  1. Subscriptions — $5 Slate Pass, $10/mo Grinder, $30/mo God Mode (annual save ~17%)
  2. Affiliate revenue — when users sign up for sportsbooks, DFS apps, or Kalshi through our links
  3. Marketplace fees — flat 50% of every creator transaction, no exceptions

Things we will never do:

  • Sell user data to anyone, ever
  • Sell Consensus signals to sportsbooks — our users are sharp bettors, and helping the books move lines against them would be a betrayal of the audience
  • Allow paid picks as a service category in the marketplace — we sell tools and models, not "lock of the day" content
  • Hide our methodology — our weighting, our calibration metrics, our affiliate disclosures are all public

Pricing in one paragraph

Free forever for building. Train all the models you want, backtest as much as you want, wire creator marketplace blocks into your private models and see the backtest performance. The only thing paywalled is live picks from your trained models (and from creator marketplace models). Pay $5 per Slate Pass for one model + one slate, $10/mo for Grinder (live picks from all your models + a few Sharp calls per month — Claude-powered ML helper buttons inside Tinker), or $30/mo for God Mode (everything plus 50 Sharp calls/mo, advanced Consensus features, and API access).

Who we're for

You're a... Sharksnip is...
Casual bettor The lowest-friction way to see what hundreds of ML models think about Sunday's games. $5 Slate Passes mean you can dip in for a single slate, no commitment.
Serious +EV bettor A research environment with backtesting, line shopping, and a Consensus signal that's not available anywhere else.
DFS player An optimizer + projections + ownership tool that ties into models you (or other creators) trained on real data.
Quant tinkerer A genuine playground — train models, fork others, sell what works, build a reputation. Sharp calls turn the LLM into a junior ML teammate.
Content creator A pipeline: get featured in Shark Snips of the Week, earn from your community, keep half of every dollar in cash.
A sportsbook or media outlet A B2B data partner — license aggregate signals or research datasets (we don't sell to operators on the books side).

What's coming

We're early. The platform is being built in public, fast.

  • Live now: Picks page, Tinker workshop, basic backtesting, blog
  • Building this quarter: Pricing page rewrite, Sharp call infrastructure, Marketplace MVP with flat 50/50, Consensus aggregation
  • Building this year: Shark Snips of the Week content engine, free Pack Breaker tournaments, full affiliate integration

If you want to be among the first creators on the marketplace — or just want to follow along — start at sharksnip.com and grab a free account.

The team

Sharksnip is currently a solo-founder build with the help of a community of early users, beta testers, and a deep stack of AI tooling. We're hiring (informally) — if you're a sports/quant nerd who wants to help shape the direction, hit us up via Discord.

Questions?

— Sharksnip