Your Betting History Shows What You Did. Can You See What Your Sportsbook Predicts You’ll Do Next?

Your betting history tells you what happened. A sportsbook data request can ask what the company inferred from that activity, including retained information relevant to the personalized offers it chooses to send you.

AI is changing the product around the bet

On September 24, the Massachusetts Gaming Commission directed staff to engage with DraftKings and examine AI use across licensed sportsbooks. That inquiry creates an opening to examine what customers can learn about the information used to personalize their experience. It follows reporting already examined in Dyutam’s coverage of DraftKings AI targeting and player-protection tools.

The technology reaches beyond bonus selection. In its 2025 annual report, DraftKings describes sportsbook recommendation engines that present betting markets using past play and location. It also describes data-science and machine-learning services that support conversion and monetization, alongside functions in fraud and compliance. Those are the company’s descriptions of its systems, not independent measurements of their effectiveness.

This is a change in how an online gambling product is assembled for each customer. The selection of markets, recommendations and offers can depend on an interpretation of previous activity. Dyutam’s earlier analysis of AI in gambling explored that wider shift. The question here concerns the customer’s ability to inspect information about themselves within it.

The commercial incentive is understandable: make a product more relevant and encourage activity that justifies the cost of attracting and retaining a customer. Protective uses pursue different objectives. A system’s purpose and the action taken on its output matter more than the AI label. Technology used for fraud checks does not, by its existence, establish that a separate marketing system protects vulnerable customers.

Your betting record and your customer profile answer different questions

A transaction history can establish that a wager was placed at a particular time and later settled. A profile can add an interpretation: a classification of commercial value, an estimate of future activity or a prediction of responsiveness to an offer. Some classifications can be produced through ordinary rules; calling every field an AI prediction would overstate the evidence.

Explaining a particular bonus requires another connection. A retained profile might describe a customer without showing which information was used when that offer was selected. Useful evidence would identify the relevant inputs, applicable rules and timing. This research has not obtained that decision record from a US operator.

A historical UK file shows what profiling can contain

There is a documented example beyond general privacy-policy language. Cracked Labs’ 2022 investigation, commissioned by Clean Up Gambling, examined data-access responses involving two UK Sky Betting & Gaming customers from 2020–2021. Its technical report describes one disclosed CSV containing 186 profile attributes, some of them empty.

These are historical UK examples, not a verified inventory of current US sportsbook records. The report does not establish that every attribute was a prediction or that these fields selected a documented individual bonus. Their importance is more specific: they demonstrate how a customer file can contain conclusions and expectations alongside recorded activity.

Personalized sportsbook bonuses have a commercial purpose

DraftKings’ March 2026 investor presentation supplies the financial context. The company presents customer analytics as a driver of personalization and reports the following figures on slide 39.

The margin conversion is straightforward: 100 basis points equal one percentage point, so 1,300 divided by 100 equals 13 percentage points. It is not a 13% relative increase. The presentation does not supply a starting margin on that slide, and these company-reported aggregates do not establish what happened to any individual customer or what was spent in Massachusetts.

A bonus is a cost the operator expects to justify through customer activity. Personalization aims to improve that calculation. That commercial logic can coexist with relevant, convenient offers, but it gives customers a reason to ask how they have been classified. A reward’s friendly presentation does not explain the business decision behind it.

What Massachusetts access rights establish

Massachusetts’ sports-wagering privacy rules provide a concrete starting point. Section 257.04 addresses requests for copies of personal information and descriptions of its use, including relevant records held by vendors and subcontractors. It provides for machine-readable access and written decisions, with reasons for denial and directions for complaints to the commission.

That framework supports asking about retained information beyond transactions. It does not expressly promise a particular marketing score, an operator’s source code or an explanation of every offer. The scope of the records, applicable exceptions and the response itself still need examination. Massachusetts provisions should not be presented as a nationwide guarantee.

This distinction matters for accountability. A rule can establish an access process without demonstrating what a customer actually receives. The next useful evidence would be redacted responses that can be compared with the requests that produced them.

What to ask for in a sportsbook data request

DraftKings directs customers to its Privacy Center, accessible through their account, to request personal information. Its help page says transaction history may be included and describes a typical US response period of 45 days, with possible extensions. That is the company’s stated process; Section 257.04 does not itself specify that deadline.

This is a checklist of requests, not a guarantee of disclosure. This article reviewed public procedures and documented historical responses; it did not submit or test a current US request. An absent field alone cannot establish concealment. It may never have existed, may no longer be retained or may be subject to a valid exception.

Access also differs from changing how information is used. Sky Betting & Gaming’s current UK privacy statement separates direct marketing, personalized marketing and cookie-controlled advertising. Stopping messages therefore should not be assumed to stop every form of personalization. Its policy illustrates the distinction; customers elsewhere need to check their own operator’s applicable controls.

Our view: transparency should follow the prediction

Dyutam’s view is that useful customer access should extend to understandable retained conclusions about the customer. Returning a field name without its meaning may satisfy an export format while leaving the recipient unable to interpret it. If a classification is disclosed, its purpose, relevant date and status as a prediction deserve a plain-language explanation.

This is an editorial standard for useful disclosure, not a claim that every element is legally required today. A prediction can be uncertain, outdated or appropriate for one purpose and misleading for another. Explaining those limits would help a customer assess the record without requiring the company to publish its entire model.

The Massachusetts review can establish how operators use these systems. Customer-access evidence would address a complementary issue: whether the person being classified can understand the information retained about them. Research should test that process with actual responses, and criticism should follow what those responses establish.

AI’s expanding role makes that standard more consequential. As recommendations and offers become more individualized, a customer needs a way to distinguish their recorded behavior from a company’s interpretation of it. Data access also serves a different purpose from limits, breaks or exclusion; Dyutam’s responsible-gambling resources cover those forms of support and control.

FAQs

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Sources

• September 24, 2026 commission meeting, discussion from 16:00 — Massachusetts Gaming Commission
• 205 CMR 257: Sports Wagering Data Privacy, including Section 257.04 — Massachusetts Gaming Commission
• 2025 annual report, product and technology descriptions — DraftKings
• 2026 Investor Day presentation, slide 39 — DraftKings
• Privacy Center overview and access-request process — DraftKings
• Digital Profiling in the Online Gambling Industry: project background and commissioning disclosure — Cracked Labs
• Technical report, pages 13 and 18–20 — Cracked Labs
• Privacy statement, marketing and customer-rights sections — Sky Betting & Gaming