Raul Moriarty

Background

As Communications Lead for Poker Bot AI — the umbrella project that runs this site — I sit between the engineers building solver-anchored decision engines, the people studying operator-side detection systems, and the players trying to work out which of the claims they read online are true. The past fifteen years have moved between software-industry roles, business development, and online poker technology specifically; this site is the place I write down what is worth saying publicly about Bet365 Poker and the iPoker Network ecosystem.

Most public writing on "Bet365 Poker bots," "hacks," and "cheating" falls into one of two failure modes. Either it is marketing copy that frames a solver-anchored decision engine as some kind of server-side exploit, or it is a forum thread that treats every form of automated decision support as equivalent to deck-prediction snake oil. Both frames stop the informed reader from understanding what real poker software does, where the engineering problems actually live, and what an operator combination like Bet365 plus Playtech is doing on the detection side.

Areas of focus

The threads I keep returning to:

Modern poker software architecture

Solver-anchored baselines from CFR-derived outputs — PioSolver, GTO+ for heads-up trees, MonkerSolver for the parts of PLO and multiway anyone has the patience to solve — compressed for runtime querying, paired with online opponent models that converge within sessions rather than over years of HUD data.

The Bet365 Poker / iPoker Network ecosystem

The architectural reality that Bet365 Poker is a Playtech-licensed skin on a long-running B2B liquidity network, with shared anti-cheat across skins, network-level RNG audit, and operator-level fraud and KYC layered on top. Most reader-submitted practical problems map back to this network-plus-operator structure in some way.

Detection from the operator side

The four-layer model — behavioural fingerprinting, statistical play-pattern analysis, anti-collusion graph models, human review — extended for the iPoker context by the network-versus-operator split. This is the area where honest explanation helps most: not as a checklist of how to avoid bans, but as an adversarial-classification problem with an asymmetric cost matrix.

Business and product

Fifteen years on the software side gives a useful filter on what part of poker-AI marketing is grounded and what part is sales copy. Most of what is sold as a "Bet365 Poker hack" is sales copy, and saying so directly has been more useful to readers than another neutral review.

Game theory in practice

Where the maths says "stop." Some spots in poker are solved well enough that further automation is rounding error; others — deep-stack multiway turn play, ICM-heavy MTT endgames, Twister multiplier-aware decisions — are still meaningfully open. Knowing the difference is part of taking the field seriously.

About this site

Three long-form notes — hacks, detection, developer FAQ — plus the homepage cover what I think is worth saying publicly about the Bet365 Poker / iPoker Network setting right now. Pages are revised when the field changes; dates at the top of each piece are the last revision, not the original publication.

There is a Telegram chat link in the header and footer of every page. If you have a question about an implementation, a correction to make on something I have written, or a research collaboration to propose, that is the right channel. The Poker Bot AI team reads everything that comes in.