# gambling Published articles for gambling. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Online Gambling Fraud Prevention for iGaming Operators DevFeed: [Online Gambling Fraud Prevention for iGaming Operators]() Original publisher: [Read original article]() Author: Ben Price Published: 2026-09-11T21:00:00Z Content type: article Language: en Sources: [Sift Science]() Topics: [Security, Privacy and Abuse Prevention](), [Bot](), [Sports]() Tags: [2026](), [bonus-abuse](), [bots](), [fraud-prevention](), [gambling](), [gambling-fraud](), [igaming](), [igaming-fraud-prevention](), [online-gambling](), [online-gambling-fraud](), [prevent-fraud](), [sports-betting-fraud]() ### AI overview The article examines fraud in U.S. iGaming and sportsbook operations, focusing on signup, deposit, and cashout risks. It highlights organized bonus abuse involving synthetic identities, stolen credentials, linked accounts, bots, device farms, and fabricated identities. ### Source excerpt In just Q1 2026, U.S. iGaming has generated about $3.04 billion, marking over 20% growth year-over-year and nearly $1 billion in April 2026 alone. For the full 2025 year, iGaming hit over $10 billion in revenue, up 27.6% over the previous year. With it being such a profitable industry, there's no wonder why it's ripe [...] The post Online Gambling Fraud Prevention for iGaming Operators appeared first on Sift. ## Martingales and the Optional Stopping Theorem DevFeed: [Martingales and the Optional Stopping Theorem]() Original publisher: [Read original article]() Published: 2014-03-03T10:00:38Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [math]() Tags: [2-sat](), [conditional-probability](), [expectation](), [gambling](), [martingales](), [mathematics](), [optional-stopping-theorem](), [primer](), [probability-theory](), [random](), [random-variables](), [randomized-algorithm](), [stochastic-processes](), [theory]() ### AI overview This primer introduces martingales as models of fair betting games and explains their connection to probability theory. It begins with a geometric-distribution exercise involving repeated die throws, then introduces the ABRACADABRA problem using a monkey typing random letters. ### Source excerpt This is a guest post by my colleague Adam Lelkes. The goal of this primer is to introduce an important and beautiful tool from probability theory, a model of fair betting games called martingales. In this post I will assume that the reader is familiar with the basics of probability theory. For those that need to refresh their knowledge, Jeremy's excellent primers (1, 2) are a good place to start. ## Optimally Stacking the Deck--Texas Hold 'Em DevFeed: [Optimally Stacking the Deck--Texas Hold 'Em]() Original publisher: [Read original article]() Published: 2012-04-09T09:00:26Z Content type: article Language: en Sources: [Jeremy Kun]() Topics: [math](), [Programming]() Tags: [card-games](), [fairness](), [gambling](), [permutations](), [poker](), [steepest-ascent](), [texas-hold-em]() ### AI overview The article solves a combinatorial puzzle about arranging a standard two-player Texas Hold 'Em deck so that one player wins regardless of where the deck is cut. It explains how cutting the deck normally supports fairness and frames optimal stackings as a measure of game complexity. ### Source excerpt Main Theorem: There exist optimal stackings for standard two-player Texas Hold 'Em. A Puzzle is Solved (and then some!) It's been quite a while since we first formulated the idea of an optimal stacking. In the mean time, we've gotten distracted with graduate school, preliminary exams, and the host of other interesting projects that have been going on here at Math ∩ Programming. And so months later, after traversing the homotopic hills of topology and projective plains of algebra, we've finally found time to solve the problem.