Our Mission

Every day, millions of dollars flow through New York’s scratch-off lottery — and most players pick tickets based on gut feeling, cover art, or whatever’s at eye level behind the counter.

We believe players deserve better. ScratchOffsNY analyzes every active game, every retailer, and every prize claim to surface the games that give you the best mathematical shot. We don’t sell tickets. We don’t take a cut. We just show you the data.

What We Track

How Our Rankings Work

Smart Score — Our proprietary ranking system that evaluates every scratch-off game on multiple dimensions. It goes far beyond simple payout rate to consider factors like where a game is in its lifecycle, how the odds have shifted since launch, and overall risk-reward balance. The result is a single 0–100 score that tells you which games are worth your money right now.

Payout Rate — The percentage of ticket revenue returned to players as prizes. An 85% payout means you lose about 15 cents per dollar on average. Higher is better, but payout rate alone doesn’t tell the full story — that’s why Smart Score exists.

Overall Odds — The lottery’s published chance of winning any prize on a single ticket. Sounds good on paper, but most “wins” are break-even or less. We focus on odds of winning more than you paid.

% Remaining — How much of the total prize pool is still unclaimed. A game with 40% of prizes remaining but only 30% of tickets unsold is mathematically better than one with 60% remaining and 70% unsold.

Key Insight — Data shows that game selection can improve your expected return by 30–47% compared to picking at random. Choosing the right store adds another edge on top of that.

Analysis Tools

Monte Carlo Simulations — We run 10,000 randomized trials per game to show what you’ll actually experience buying 10 tickets, not just the theoretical average. This reveals variance — the real-world difference between a game that pays back steadily and one that’s all-or-nothing.

Live Odds Tracking — As tickets sell and prizes get claimed, the true odds shift. We track these changes daily and show you whether each prize tier is getting easier or harder to hit compared to the original game launch.

Store Intelligence — Not all retailers are equal. We analyze sales volume, activation patterns, and delivery schedules for every licensed retailer in New York to help you find stores with optimal inventory turnover.

Historical Trends — Track how any game’s value has changed over time. See whether your favorite game is improving or declining, and make buying decisions based on trajectory, not just a snapshot.

Our Data Sources

Everything on ScratchOffsNY is built on official, publicly available data:

• NY Lottery — Live game data, prize structures, and remaining prizes via nylottery.ny.gov
• NY Open Data — Retailer locations, weekly sales data, and prize claim records via data.ny.gov
• US Census Bureau — Demographic and income data for geographic analysis
• Player Community — Verified win/loss reports submitted by real players on our platform

Responsible Play

Let’s be clear: the house always wins in the long run. Even the highest-scoring games on our platform have a negative expected return. No strategy eliminates the house edge — but playing smart means losing less and enjoying more.

We encourage setting a budget and treating scratch-offs as entertainment, not investment. If you spend $20/week on the best-ranked game instead of a random one, data shows your expected loss drops from about $6–$7 down to $3–$4. That’s real savings over a year.

If you or someone you know needs help with problem gambling, call 1-877-8-HOPENY or text HOPENY (467369).

Data Sources & Methodology

ScratchOffsNY is built entirely on official public data. We don’t scrape, guess, or crowdsource our numbers.

Contact

Questions, feedback, or partnership inquiries? Reach us at win@scratchoffsny.com

Data Sources & Methodology

ScratchOffsNY is built entirely on official public data. We don’t scrape, guess, or crowdsource our numbers.

Game Data: Prize structures, remaining prizes, and payout rates come directly from nylottery.ny.gov and are refreshed daily via automated pipeline.

Store Data: Retailer sales, payouts, and delivery patterns come from NY Open Data (Socrata API) — the same dataset the state publishes for transparency. Updated weekly.

Smart Score Algorithm: A weighted 0–100 composite of eight factors: Value (payout rate + EV shift), Edge (risk-adjusted returns via Sharpe ratio and Kelly criterion), Density (prize density and scarcity), Playability (how long your bankroll lasts), Momentum (7-day trend direction), Confidence (data reliability based on lifecycle stage), Upside (big prize accessibility), and Heat (sales velocity). Factor weights are continuously optimized via autoresearch — automated experiments that test thousands of weight combinations against historical outcomes.

Store Smart Score: Ranks retailers on nine factors: payout rate, volume, consistency, momentum, freshness, inventory breadth, statistical significance, win streak, and draw index. Weights are optimized by a separate autoresearch pipeline trained on 7,000+ stores.

Prediction Engine: A self-improving gradient-boosted tree model trained on walk-forward historical snapshots. Uses 14+ features including Smart Score, payout trend slopes, momentum signals, and lifecycle stage. The model validates itself daily against actual outcomes and auto-adjusts blend weights (Smart Score vs. Booster vs. Momentum) based on pairwise ranking accuracy. Separate from Smart Score rankings — they never cross-contaminate.

Autoresearch System: Three automated optimizers run continuously: (1) Game weight optimizer tests factor weight combinations to maximize rank correlation with future outcomes. (2) Store weight optimizer does the same for retailer rankings. (3) Prediction hyperparameter optimizer tunes the ML model’s trees, learning rate, train window, and blend weights. All results are logged and applied automatically.

Monte Carlo Simulator: We run 10,000 random trials per game to model realistic outcomes for different play budgets. Prize extinction estimates use statistical modeling based on claim velocity and remaining prize counts.

Live Autoresearch Stats

What kind of tips are useful?

Rare Finds — Spotted an ended game still on the rack? Tell us the store and game number.

Store Intel — Know a store that gets fresh inventory often, or one with dusty old tickets?

Strategies — Found a pattern or approach that works? Share it with the community.

Or just email us directly: win@scratchoffsny.com