For Modelers — The Complete Creator Guide

A guide for the people building, publishing, and earning from models on Sharksnip.

If you're new to ML modeling, start with Your First Model in 10 Minutes. This guide is for once you're past that.

TL;DR for the degens-who-build

• You keep 50% cash of every sale. No tier ladder. No royalty chain on forks.
• $10 sub to your model → $5 to you. 100 subs at $10 = $500/mo, paid via Stripe Connect on the 1st.
• Track record is public. Brier + ROI + sample size on every listing. Faked backtests die in week 2.
• Sharp calls (Optimize Weights, Diagnose, Auto-tune) do real ML work in one click. God Mode = 50/mo with rollover to 100.
• Sell models, pipelines, datasets, ensembles, tutorials. Don't sell picks ("the Chiefs cover") or scraped sportsbook data.
• Forking is encouraged — visibility on the parent's profile and a public fork tree drive subscriptions back to you.

This is the kind of feature space you're modeling against. Real player-weeks, real PPR output, real sample sizes — directly readable from Tinker.

Why publish on Sharksnip

Sharksnip is built around the assumption that you, the modeler, are the most valuable asset on the platform. Top creators earn five to six figures annually selling monthly access to their models. The platform takes a cut — but a smaller cut than the alternatives.

Half of every dollar back, in cash, no tier ladder to climb. This is unusual in marketplaces — most platforms charge you more when you're starting out (smaller audience pull) and lower the rate when you're established. We took the opposite stance: a new creator with their first sale gets the same 50% as a creator with 10,000 monthly subscribers.

Earnings — flat 50/50

The split

• Creator: 50% of every transaction, paid in cash via Stripe Connect
• Sharksnip: 50% as platform fee
• That's it. No tiers. No grace periods. No credits. No royalty chain on forks.

What this means in practice

• Subscriber pays $10/mo for your model → you get $5/mo, Sharksnip gets $5/mo
• Subscriber buys a $5 Slate Pass for your model → you get $2.50, Sharksnip gets $2.50
• 100 subscribers at $10/mo = $500/mo to you, paid in cash on the 1st of each month
• 1,000 subscribers at $10/mo = $5,000/mo
• 100 weekly Slate Pass buyers at $5 = $250/wk to you = ~$1,000/mo

Cash payouts via Stripe Connect

• Method: Stripe Connect Express account (5-minute setup)
• Cycle: Monthly. Cycle ends last day of calendar month, payout processes within 7 days.
• Minimum: $50 USD. Below-minimum balances roll forward.
• Currency: USD by default. Other currencies supported per Stripe Connect availability.
• Tax forms: 1099-NEC issued for US creators earning $600+/year. Equivalents for non-US per local rules.

Why no tier ladder

Earlier versions of Sharksnip had a Beginner / Established / Signature ladder. We removed it because:

1. Simplicity beat sophistication. Creators in user research consistently picked simpler over higher-EV. Flat 50% won by a wide margin against the old 80% (credits) → 50% (cash) → 70% (cash) ladder.
2. The ladder caused friction at the entry point. Beginner creators were paid in non-cash credits, which felt like "we owe you nothing real." That's a worse first impression than "you get $5 cash from your first sale."
3. Tier mechanics were ~30% of the original implementation plan and shipped almost no incremental revenue. Promotion logic, demotion logic, grace periods, criteria computation — all engineering work that didn't move the user-visible needle.
4. It made the public docs more complex than they needed to be. Anyone could explain "you keep half" in 5 seconds. Explaining "you start at 80% in credits, then promote to 50% cash, then maybe to 70% cash, with these criteria, with these grace periods…" was a wall of text that turned creators away.

We may revisit a formal tier system later (after first 100 paying creators). For now: simpler is better.

Featured Creator status (informal, editorial)

There's no automated tier ladder, but there is editorial recognition.

Featured Creator is a status awarded by the Sharksnip team based on:

• Consistent performance (positive ROI, good calibration)
• Quality of model documentation
• Community engagement (Discord, Snip Tank interview willingness)
• "Vibe" — does this person represent the platform well?

What Featured Creators get:

• Prominent placement in marketplace browse
• Featured spot in Shark Snips of the Week (rotating)
• "Featured" badge on profile
• 25 bonus Sharp calls when featured in Shark Snips
• First call on Snip Tank monthly interviews
• Direct relationship with the Sharksnip team

There's no formal application — we reach out. There's also no formal "demotion" — featured status rotates naturally as new creators rise. If a featured creator has a bad month, we don't strip the badge; we just don't re-feature them until they bounce back.

What you can sell

You set the price. Sharksnip suggests a range based on the category and recent platform-wide median, but you're the seller.

What you can NOT sell

🚫 Picks themselves. "I think the Chiefs will cover" is not a marketplace product. We are not a tipster service, and selling individual game picks runs into licensing requirements in multiple states.

🚫 Real-time data feeds scraped from sportsbooks. Use The Odds API or another licensed source for live data. We don't allow re-distribution of unlicensed scraped data.

🚫 NFL/team trademarks. Don't use league logos, team names commercially, or player likenesses in marketing copy or product UI.

🚫 "Win/loss guarantees." No guaranteed-winning systems, no money-back-if-it-misses. Past performance is not indicative of future results, and pretending otherwise is a regulatory and reputational risk to the whole platform.

🚫 Anything using insider/non-public information. Models trained on leaked NGS data, unpublished injury reports from sources, etc., are not allowed regardless of how you got the data.

If you're unsure whether something fits, email creators@sharksnip.com before publishing.

Forking — the discovery multiplier

Forking is a major mechanic on the platform. When someone clicks Fork on your model:

1. They get a starter that mirrors your architecture + feature pipeline (NOT your trained weights — your alpha is preserved)
2. They retrain on their own data, with their own modifications
3. They publish their version
4. You are credited as the parent on their fork's profile + appear in the public fork tree

No royalty chain

Earlier versions of Sharksnip had recursive royalties (parent earns 10% on child sales, 5% on grandchildren, etc.). We removed this. The reasons:

1. Tax accounting on multi-generation royalty chains is genuinely terrible.
2. Recursive royalties created a perverse incentive: top creators kept their best work private to avoid "leaking" architecture to forks.
3. The actual financial impact on the parent (10% of $X) was small enough that the discovery upside (visibility from being forked) outweighed it for most cases.

What you DO get from being forked

• Visibility on the fork's profile
• Inclusion in the public fork tree (browseable by users looking for "ancestors of this hot new model")
• Discovery flywheel: a forker's audience sees the parent and often subscribes to it as well
• Signal of quality (frequently-forked models become "starter" models, which tend to attract continued subscriptions)

If your fork-eligible flag is OFF, no one can fork you. Default is ON. We recommend leaving it ON unless you have a specific reason — the discovery upside is real.

Performance verification

The y=x line is the dream. The cloud around it is reality. Buyers see this on every listing.

We don't take your word for your model's performance. Every published model has a public track record:

• Live predictions — every game your model is run on (during inference) is logged with the prediction and the eventual outcome
• Brier score — how well-calibrated your probabilities are
• ROI — implied wagering returns assuming flat-stake betting
• Sample size — how many predictions are in the track record
• Consensus contribution — your model's weighted impact on Shark Snips Consensus

These show on your model's listing page. Faked backtests don't survive contact with live data; calibration metrics expose them within weeks.

This is a feature, not a tax: it's the strongest possible marketing for a good model, and the strongest possible warning against a bad one.

Privacy — what's required for monetization

To list a model on the marketplace, you must opt in to:

• Public listing (model name, description, your username, performance metrics visible)
• Inclusion in Sharksnip Consensus (your model's votes contribute to weighted aggregate)
• Live performance tracking (every inference logged with outcomes)

You can NOT keep a published model's picks private. If you want to keep your edge fully private, don't publish — train models for your own personal betting and never list them. Your free Sandbox tier gives you all the Tinker tools you need to do this; you don't need a paid subscription to build private models.

You can choose:

• Whether your username appears on Consensus contributions (or stay anonymous)
• Whether your model can be forked (default ON; turning it off forfeits discovery upside)
• Whether your model is searchable vs only accessible by direct link

How buyers actually use your model

When someone subscribes to your model (or buys a Slate Pass for it), they're paying for an inference window. During that window, they can:

• Run your model against every game in the relevant slate, as many times as they want
• View predictions and confidence scores
• See feature attributions if you've published them
• Mix outputs with other models' outputs into ensemble views

The model itself stays on Sharksnip's servers. Buyers don't download the weights — they call an API endpoint that runs the inference. This protects you from piracy and protects the platform from re-distribution.

Sharp calls — your secret weapon as a creator

Sharp calls (Optimize Weights, Improve Calibration, Run Monte Carlo, etc.) are AI-powered button presses inside Tinker that do real ML work. As a creator, you'll likely use them constantly:

• Use Optimize Weights to do quick hyperparameter sweeps before publishing a new version
• Use Run Monte Carlo to stress-test a model before it goes live
• Use Improve Calibration to clean up Brier score before pushing to the marketplace
• Use Suggest Features when iterating on a struggling model
• Use Diagnose to figure out why a model that backtested well is underperforming live
• Use Auto-tune to do a clean retrain with a smarter starting point

Sharp call quotas:

• Free: 1 per week (Monday reset, no rollover) — try the killer feature on every model you train
• Slate Pass alone: 0 from Slate Pass itself — keeps whatever underlying tier quota you have
• Grinder ($10/mo): 5 per month, rolling forward up to 10 if unused
• God Mode ($30/mo): 50 per month, rolling forward up to 100 if unused — recommended for active creators
• Sharp call top-up: $1 per call on every tier — pay-as-you-go overflow, no subscription required

Top-up balance is separate from monthly quota and doesn't expire. Bonus Sharp calls (from Pack Breaker prizes or Featured Creator features) stack on top of all of the above.

If you're publishing models seriously, God Mode pays for itself in time saved and model quality improvement.

Creator dashboard

Your dashboard shows:

• Total earnings (cash, with month-over-month trends)
• Earnings by model — which of your listings is actually working
• Subscriber trends — new subscribers, churn, total active subs per model
• Slate Pass purchases — one-shot buyers (often a leading indicator of subscribers next month)
• Fork tree — who forked your models, how their forks are performing
• Performance vs Consensus — how your model compares to the platform aggregate
• Snip mentions — when your model has been featured in Shark Snips content
• Stripe Connect status — payout setup, next payout date, lifetime cash earnings

Marketing your models

Sharksnip drives traffic to your models, but you can amplify it:

Inside the platform

• Your shark profile — short bio, links, model gallery
• Discord — there's an active #showcase channel for new releases
• Snip Tank application — apply to be featured for monthly interviews

Outside the platform

• Twitter/X — share your model's track record (auto-generated images available)
• YouTube — record yourself walking through the model's logic; we'll cross-promote good content
• Reddit r/sportsbook + r/algotrading — high-signal audiences

The single highest-leverage move is consistent live performance. A model that publicly hits over a 4-week NFL window will sell itself.

Best practices

1. Start by forking, not from scratch. It's faster and you start with a working baseline.
2. Document the "why" of features. Buyers pay more for models with documented reasoning, even if the underlying performance is similar.
3. Keep one publishable model per major sport you cover. Multi-sport coverage outperforms NFL-only because of seasonal rev smoothing.
4. Backtest aggressively before publishing. Your live track record starts the day you publish. A poor first month is hard to recover from.
5. Update models seasonally — feature drift and rule changes happen. Static models decay.
6. Engage in Discord. The most successful creators are visible. Buyers buy from creators they trust.
7. Don't oversell. Honest "this is a 53% spread model with calibration score X" outperforms breathless "GUARANTEED 80% PICKS" every time, because buyers see track records publicly.
8. Use your Sharp call quota. A creator who clicks Optimize Weights once a month publishes better models than one who never does.

What happens when you screw up

You're going to publish a model that performs badly. Everyone does. Here's what happens:

• Your model's live track record will reflect it (negative ROI, poor Brier score)
• Buyers will see it on the listing and either pass or buy with eyes open
• You can unpublish at any time (existing subscribers retain access through their billing period; new subs stop)
• You can republish a revised version (new model, new track record)
• You don't lose Featured status from one bad week (if you had it); you do drift out of the rotation if performance stays poor

The platform is forgiving of failures and learning. It's harsh on misrepresentation. Cherry-picking, faked backtests, or stat fudging will get you removed and banned permanently.

Tax and payout details

For US-based creators:

• 1099-NEC issued for any creator earning $600+/year in cash from the platform (handled by Stripe automatically)
• Payouts go through Stripe Connect (you set up Express or Standard account)
• We collect required tax info (W-9) at first payout setup
• Sharksnip is responsible for collecting and remitting sales tax where applicable; you're responsible for income tax on your earnings

For non-US creators:

• We support Stripe Connect in 40+ countries
• Tax info varies by country; you're responsible for your local obligations
• We can issue local equivalents (W-8BEN for non-US individuals)

Questions?

• Creator support: creators@sharksnip.com
• Discord #creator-help channel
• Snip Tank submission: creators@sharksnip.com with subject "Snip Tank application"

Welcome to the marketplace. Happy modeling.