DraftKings Used AI to Target Losing Bettors
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What happened
A New York Times investigation published Sept. 19, 2026, reported that DraftKings built a 2023 machine-learning system that ranked online casino players by how much they were expected to lose after a free bet or bonus. The Times said it reviewed internal memos, presentations and betting records and interviewed more than 40 former employees; staff called the ranking an "elasticity" score and used higher scores to decide whom to pursue with more promotions. Former data analyst Jayden Butts, who tested the system, told the Times the traits it favored pointed toward problem gamblers. In 2024, data scientist Nestor Hernandez began a separate model to flag customers heading toward crisis; DraftKings later shelved that work, and Chief Responsible Gaming Officer Lori Kalani said leaders made a "collective decision" against predictive tools because they were not "evidence-based." DraftKings disputed the account, saying promotions go to customers with "sustained, engaged use" rather than people singled out for losing, and called Butts's test "preliminary and inconclusive."
Sourcing check · Fully on the record · 3 articles
3 of 3 articles cite a named source for the story. It was on the record from the first report, credited to The New York Times. Lori Kalani denied part of it on the record.
What these terms mean and how they're counted
- On the record · names a source 3 of 3
- On the record means the article cites a source by name for the story's main claim: a person, or an institution speaking officially, such as a company statement or a named agency's spokesperson. The opposite is an unnamed source. The count is how many of the counted articles cite at least one such source; the names are everyone named across them, each once however the articles spell it. Here: Jayden Butts, Bryan Biehl, Jennifer Hoekstra, National Council on Problem Gambling, UCLA study and former FanDuel employee
- Primary evidence · cites a document or data 0 of 3
- Primary evidence means the article cites a record you could check yourself: a court filing or ruling, a dataset or report, a recording or transcript, an official statement or press release, market data. A quote is not a document. The count is how many articles cite one. Here: None cited.
- Credits another outlet 1 of 3
- The article says the story comes from another outlet's reporting (“first reported by Reuters”). Those articles relay the story; they are not independent confirmation. Here: The New York Times
- Unnamed sources 3 of 3
- The main claim is attributed to people who are not identified: “people familiar with the matter”, “officials said”. The count is how many articles do this. Here: e.g. “former DraftKings employees”
- On-record denial 3
- A named person or institution says the claim, or part of it, is not true. It is on the record — someone signed their name to it — but it is not confirmation, so it never counts toward On the record. Criticizing or dissenting from a decision is not a denial. The count is how many people or institutions deny it; each is listed with the first article that carried the denial. Here: Lori Kalani (Daily Caller, Sep 20, 02:06 UTC); FanDuel (CBS News, Sep 20, 13:17 UTC); DraftKings spokesperson (New York Post, Sep 21, 21:21 UTC)
- How it developed
- When the first report landed and whether it named anyone; when the first named source and the first document appeared. Here: First report Sep 20, 02:06 UTC by Daily Caller, crediting The New York Times, naming its source.
- Not counted 0
- Opinion, analysis and video pieces, and articles too short to assess. Every count above is out of the counted articles. An article republished under a new headline is one article.
This is about who is cited, not whether the story is true. Each source below says what it names. How we count
ONE-SIDED THIS WEEK.
Only right-leaning outlets have covered this story in the last two days;
New York Times reported it on 2026-09-19.
Omitted — what each side leaves out
Unpacked
Left-leaning coverage has not reported this investigation at all. Right-leaning coverage says DraftKings built a machine-learning tool that scored casino players by expected losses after a free bet, then used a higher "elasticity" score to justify more perks. The firm says promotions go to engaged users, not people singled out for losing. A reader of left-leaning outlets misses both the targeting claim and that a separate model meant to flag gamblers in crisis was shelved.
Right-leaning coverage splits on the extra. Only Daily Caller mentions a Senate bill that would forbid sportsbooks from using AI to track betting habits. Only the New York Post dwells on a customer who said promotional emails became a relapse risk after he entered therapy.
How many customers received a bonus because an elasticity score said they would lose more?
Bottom line
Left-leaning outlets have not covered the DraftKings targeting story. Their readers never hear a former analyst say the best investment would be a problem gambler.
The receipts — 3 facts one side's coverage lacks
- DraftKings handed out about $3 billion in promotions last year
- Sen. Richard Blumenthal and Rep. Paul Tonko introduced the SAFE Bet Act, which would forbid sportsbooks from using AI to track betting habits and serve personalized offers
- Bryan Biehl received 40 DraftKings promotions during the first two weeks of December 2024 after starting therapy for gambling addiction
The Right View
The Daily Caller and New York Post both rest on the Times investigation and frame it as DraftKings using AI to hunt the customers most likely to lose money, then flooding them with bonuses. They spotlight Butts's line that "the best investment would be a problem gambler," the elasticity score (playing frequency, daily balances, losses-to-wagers), former staff who later called the work predatory, and the company's about $8.7 billion in gross gambling revenue against about $3 billion in promotions. The Post adds Bryan Biehl, who said he lost nearly $70,000 online, received 40 DraftKings promotions in the first two weeks of December 2024, and relapsed on Christmas Day before self-excluding. Both report DraftKings' denial, its responsible-gaming staffing claims, an executive's statement that AI personalized hundreds of millions of dollars in promo spending and improved promo-driven sports-bet margins by 13% in 2025, DraftKings' roughly $900,000 in 2025 federal lobbying, and the SAFE Bet Act from Sen. Richard Blumenthal and Rep. Paul Tonko that would bar sportsbooks from using AI to track betting habits and serve personalized offers.
Our Take (balanced)
The story is substantive: it is anchored in a Times review of internal memos, presentations and betting records, interviews with more than 40 former staffers, named employees (Butts, Hernandez, Kalani), a named customer (Biehl), dated product work (2023 elasticity model; 2024 responsible-gaming model), and checkable figures on revenue, promotions, lobbying and a named bill. Established: DraftKings built promotional-targeting models; former employees say those models optimized for customers who would lose more after bonuses; a crisis-prediction project was not deployed; the company rejects the "target losers" characterization and calls the Butts test preliminary. Alleged, and disputed by DraftKings: that promotions were in fact aimed at problem gamblers rather than at "sustained, engaged" users, and that the responsible-gaming model was dropped for reasons other than Kalani's evidence-based rationale. The New York Times published the original investigation; the Daily Caller and New York Post have run follow-on coverage. Matching independent stories from other left-leaning national outlets are not among the coverage provided here. Watch for release or discovery of the memos and elasticity model, regulator or legislative action on the SAFE Bet Act, and further named-employee or document corroboration beyond the Times account.
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