DraftKings Appears in 98.9% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Answer Capsule

In November 2026, DraftKings appeared in 271 of 274 AI answers included in the Online Betting Sites benchmark (98.91%). It received 144 recommendations (52.55%), with 130 Top 3 placements and 55 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

• How do DraftKings mentions, recommendations and placements compare with its Online Betting Sites peers?

DraftKings recorded 271 mentions (98.91%) and 144 recommendations (52.55%) across 274 answers included in the benchmark. Top 3 placements numbered 130; first-place recommendations numbered 55. Framing among its mentions was 146 positive, 125 neutral and 0 negative.

DraftKings appears in almost every answer in this selected sample, and it matches FanDuel on mentions and on affirmative recommendations. That breadth is a real strength: the brand is rarely missing when a betting question is answered, which keeps it in front of buyers at the moment they are comparing options.

The placement picture is more mixed. DraftKings receives fewer first-place recommendations than FanDuel, so the gap is about being endorsed first rather than being seen at all. Proposed work would review which question types sit behind that gap, fact-check the underlying answers against current primary sources, and build page briefs and buyer-question content aimed at earning stronger endorsements. These figures cover one selected month and serve as a starting scorecard, not a settled position.

What changed since last month

Questions This Section Answers

• How did DraftKings counts and coverage differ across the available monthly snapshots?

From October 2026 to November 2026, DraftKings' mention count fell from 306 to 271, while its recommendation count fell from 186 to 144. The recommendation rate was 60.39% and 52.55% respectively.

The monthly record shows DraftKings' recommendation rate moving within a wide band across the selected samples, with November lower than October. Mentions also eased. The observed movement is real in the record, but the samples differ between months, so the two months are not directly comparable.

A smaller answer total does not explain the change in counts or rates, and no cause should be assumed from this table alone. The useful reading is that recommendation strength is variable month to month, which makes a stable baseline and repeated measurement more valuable than reacting to a single month.

Proposed work should set that baseline first, then track whether later changes hold across more than one sample.

Step 1. Measure

Questions This Section Answers

• What should the agency measure and verify first for DraftKings?

AI answers contained 12 conflicting claims about DraftKings: 0 critical, 3 high, 6 medium, 3 low. Of these, 3 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

A visibility comparison would show where DraftKings leads, where it is merely present, and where rivals take the first recommendation. Pairing that with a short list of claims to fact-check gives the client a practical order of work rather than a broad ambition.

The recorded conflicts about DraftKings cluster around availability, analyst targets, share price and reported results. Their severity ratings help decide what to check first; they do not show that anyone published an error. Proposed work is to confirm each disputed point against current primary sources before deciding whether any correction is warranted.

Step 2. Make the website consistent

Questions This Section Answers

• Which recorded claim differences about DraftKings should be verified before proposed page edits?

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

The disputed topics are mostly factual and checkable: which states permit daily fantasy sports, the range of analyst price targets, the current share price, and reported revenue and income. Each pair of recorded claims may reflect different dates or different sources rather than a genuine contradiction.

Proposed work is to resolve the entity, the date and the source for each topic, then write page briefs only for points the company can confirm. Where the evidence is ambiguous, the item stays out of the correction queue. Briefs should state approved facts plainly so answers have a clear version to draw on.

Step 3. Align the external narrative

Questions This Section Answers

• Which cited third-party pages are relevant to fact review for DraftKings?

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

The cited pages selected for review are mostly financial and market-data sites, which fits the disputed topics around price targets and reported results. Citation counts show these pages appear in captured answers; they do not show that a page caused a conflicting claim.

Proposed work is a page-by-page review of current contents, followed by evidence-backed requests only where a specific, verifiable inaccuracy is found. Requests should be framed around confirmed facts and dated sources, and responses recorded separately from confirmed edits.

Step 4. Optimize priority company pages

Questions This Section Answers

• Which observed DraftKings website pages should receive review briefs?

The company's website was cited 32 times across 24 distinct page addresses; the table shows 8 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

The company pages cited in answers are few relative to the site's likely breadth, and most recorded citations sit on a small set of how-to-play and availability pages. That suggests the pages answers rely on are narrow, which is a content opportunity rather than a proven gap.

Proposed page briefs should use approved facts and the questions buyers actually ask, and should check existing coverage before proposing anything new. Pages with no recorded citations are not automatically weak; they simply were not observed in this sample.

Step 5. Publish around buyer questions

Questions This Section Answers

• Which observed buyer questions support content briefs for DraftKings?

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

The recorded questions are broad comparison questions: which sportsbook is best, most reliable, or top-ranked, plus app-focused variants and a casino question. DraftKings appears in nearly all of them, so the content opportunity is to strengthen how the brand is framed within comparison answers rather than to fill an absence.

Proposed buyer-question briefs should cover reliability, app quality and top-sportsbook framing, using approved facts and clear comparisons. Existing pages should be checked first, and these observations are not search volume or proof of missing content.

Our 90-day action plan

Questions This Section Answers

• How should the agency sequence the proposed DraftKings work and judge completion?

The first month establishes the baseline scorecard, a scoped fact-review register and a shortlist of pages and sources, each with an owner and a review status. This groundwork decides what can be acted on and what must wait for verification.

The second month produces approved page briefs and justified publisher requests, with confirmed edits, no-change decisions, requests and responses kept separate. The third month adds buyer-content briefs and a fresh scorecard.

Delivered work will be recorded separately from measured answer outcomes. Completing the plan does not guarantee a visibility gain, and later comparisons will carry the same sample limits.

Methodology

Questions This Section Answers

• How are DraftKings answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 274 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 4113 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

Monthly sample coverage:

The answer samples differ between months. These comparisons show how the recorded results changed; they do not establish why they changed.

The answers were collected at dates that have not been verified, and the monthly samples differ in size and coverage. Month-to-month movements show how recorded results changed, not why.

A recommendation requires both endorsement and positive wording, and placement counts sit inside recommendations rather than adding to them. Answers can mention several companies, so counts cannot be summed into distinct answers. Cited pages and disputed claims still need independent verification.

Our first three priorities

First, verify the disputed availability, price-target and results claims against current primary sources, and keep ambiguous items out of the correction queue. This protects the brand from acting on an unconfirmed AI statement.

Second, review the cited financial pages and prepare evidence-backed requests only where a specific inaccuracy is confirmed. Third, draft page and buyer-question briefs around reliability, app quality and top-sportsbook framing, checking existing coverage first.

A fresh scorecard should follow, with completed work reported separately from measured outcomes.