About me

One Person, Every Casino's Rules in One Place

I'm Valerii Zalivkin, and I built GambleGrade by myself. The clauses that cost players money are buried in the middle of terms nobody actually reads, so I collect each operator's rules, work through them clause by clause, quote the exact wording behind every flag, and publish the formula that turns it all into a single score. Both parts are transparent: the casino's own words, and the maths behind them.

Last updated:29 Oct 2026

Who Runs This

One developer · Everything else is automated

Valerii Zalivkin

Founder & Lead Developer

I built GambleGrade to put every online casino's rules in one place, across all 37 markets it covers. Casino terms are long, change without notice, and bury the costly clauses in the middle - so they get collected here, read clause by clause, quoted and dated, and you see them before the money rather than after.

60
Casinos reviewed
333
Bonuses analysed
37
Markets covered
Journey so far
  1. 2024Started buildingBegan work on GambleGrade with the mission of gathering all casino rules in one location and working through them clause by clause.
  2. 2024Formula publishedFinalized and released the six-pillar scoring formula in advance of computing the first score, ensuring the method was transparent from day one.
  3. 2025Pipelines builtDeveloped the scraping, terms analysis, scoring algorithms, and versioning infrastructure that operate the platform independently.
  4. 202637 markets liveWent live in August 2026 across all 37 markets concurrently, with each market's rules examined according to its own setting.
Tech & Tools
FastAPIPythonSQLAlchemyPydanticPostgreSQLRedisCeleryNext.js 15React 19Tailwind CSSMantineScrapingBeePlaywrightLighthouseNginxPM2
The Reasoning

The Rules First, The Ranking After

Most casino review sites are sales channels wearing a journalist costume.
Here it works the other way - one person, one automated pipeline, one formula that runs the same way every time. Every rating comes from a public model. Every source is named. No casino can pay to rank higher.
One developer. Every clause read. No paid placement, ever.
Typical review sites
  • Rankings driven by which operator pays the most
  • Scores backed by unnamed sources or unverifiable claims
  • One generic template repackaged for each region
  • Ratings shift when partnership money does
  • Affiliate deals buried deep in fine print
  • No methodology disclosed, no formula weights published
  • Outdated content recycled without re-checking facts
VS
GambleGrade
  • Scores calculated by a published formula anyone can verify
  • Every input is concrete and disclosed in full
  • 37 markets, each with its own regulatory and payment ruleset
  • Ratings recalculate when the underlying data shifts
  • Affiliate partnerships listed openly - they do not affect position
  • Six pillars of assessment, with documented weights
  • Terms-of-service pages re-analysed and all ratings re-scored monthly
€0 paid rankings - ever

Independence

Affiliate income covers hosting and the cost of running scrapers. The income has no access to the ranking code. A separation built into architecture, not just into promises.

Open methodology

Transparency

Methodology is public. Data sources are named. Formula weights are written down. A score does not go live unless I can walk backward through every step that produced it.

Formula decides

Data-First

I set the weights once. The scoring engine runs from there without me in the loop. No manual override exists. My opinion of a casino has zero influence on where it ranks.

10+
Ten years of casino terms collected, analysed, and stored
1
One person scoring every casino - automation handles scale across 37 markets
95
Data points per casino fed into the rating formula
60
Casinos scored by formula - rankings never change for payment or affiliation
333
Bonus terms flagged automatically for unfair clauses and traps
0
Player feedback analysed by sentiment and weighted into the score
How It Works

From Finding a Casino to Publishing Its Rating

I design and maintain the scoring formula. Automated systems handle the daily hunt for new operators, data collection, scoring calculations, and publication. Every month, the entire catalogue gets re-scored using fresh terms-of-service data.

01

Spotting New Casinos & Checking Their Licenses

Crawlers search for new operators across 37 markets every day. When a brand appears, I verify its license against the Gambling Regulatory Authority of Ireland and other official records, check the corporate setup, and look for any sanctions or revoked credentials. Only operators with valid, current licenses make it into the catalogue.

02

Pulling Data at Scale

Scripts gather information from regulator APIs, public filings, payment processor records, and game studio databases. Thousands of data points are collected automatically - no manual typing of bonus terms, no hand-entered figures, no outdated snapshots.

03

Running the Scoring Formula

Raw data is cleaned and fed into the formula, which rates each casino across six areas: trust & licensing, bonus fairness, payout speed, payment options, user experience & mobile, and player reviews. The formula generates the ranking. I never adjust a score by hand, and no business arrangement can alter the order.

04

Checking the Numbers & Writing It Up

I work through unusual results, verify edge cases manually, and write explanations showing what the data actually reveals. My role is to make sense of the numbers - not to change them.

05

Publishing & Keeping Watch

Once the monthly re-scoring cycle completes, the updated ratings go live. Monitoring systems watch for license changes or shifts in payout performance and flag anything worth a closer look.

The backbone of every rating

Six commitments built into the score

These principles are embedded in the formula. Nothing overrides them.

Position is determined by data, never by money

Casinos cannot purchase placement. The platform runs on affiliate revenue, but the ranking itself comes purely from the formula - financial arrangements have zero influence on position.

The algorithm decides, I do not

I set the weights and select the data sources once. After that point, the scoring engine operates without intervention - no manual adjustments, no exceptions, no override buttons.

Built for the person funding the deposit

Every weight, every predatory term flagged, every feature on this site exists because it helps someone choose a casino more carefully - not because a casino operator requested it.

All methodology is visible and testable

The scoring logic is documented publicly. Data sources are named. Each calculation step is published. Anyone with the same inputs can reproduce any casino's rating.

Every rating recalculates monthly

Outdated scores mislead players. A scraper re-evaluates each casino's rating once per month against current licensing, recent payout test data, and the latest terms snapshot.

Errors and fixes live in the open

When a rating is incorrect or the scraper encounters a failure, I log both the error and the correction in a public changelog. Reader reports are tracked the same way.

Editorial Policy

Why Affiliate Revenue Never Changes a Casino's Score

How the infrastructure and day-to-day process keep casino ratings independent of the revenue stream that funds GambleGrade.

Technical Isolation Protects the Score

I run this platform on my own, and there's no sales team lobbying for ranking bumps. The scoring system draws exclusively from the rating dataset - affiliate records sit in a completely separate database that the formula can't touch.

One Algorithm, Applied Uniformly

Every casino goes through the same six pillars with identical weighting. Trust & licensing, bonus fairness, payout speed, payment methods, mobile experience, user feedback - the inputs and thresholds stay the same for all brands, whether I earn a commission from them or not.

Commission Income Is Transparent

When you click certain links, I receive a referral fee - that's always disclosed right where the link is. Whether a casino pays affiliate commission only determines if I earn from it; it doesn't shift their rating or change where they sit in the catalogue.

Data Corrections Only, Not Score Trading

Casinos can submit factual updates - a new regulator licence, an extra payment option, corrected branding. I check each one by hand before it enters the system. Rating adjustments and ranking changes can't be requested, negotiated, or bought.

How the ratings work

Six pillars. One public formula. Scores that stay honest.

I rate every casino across six areas using fixed weightings and verifiable data. The full breakdown - exact calculation steps, what each flag means, where the data comes from - is published on the methodology page so you can run through any score yourself.

TRS

Trust & License

20%

Regulator jurisdiction, operator history, automated review of terms-of-service pages for dodgy clauses, live support response times.

PS

Payout Speed

15%

Real withdrawal times pulled from transaction data - same-day payouts rank higher than multi-day delays.

FB

Fair Bonuses

20%

Actual bonus value after you factor in wagering friction, cashout caps, and unfavourable term restrictions.

CR

Player Reviews

15%

Feedback collected from Trustpilot, AskGamblers, public forums, and other spaces where players share honest accounts.

PC

Payment Options

15%

Range of deposit and withdrawal methods - cards, e-wallets, bank transfers, cryptocurrencies - plus minimum stakes and maximum cashout rules.

UX

Site Performance & Mobile

15%

Load times, menu layout, mobile experience, and whether the platform stays reliable when traffic picks up.