Many readers ask which new online sportsbooks attract the most users and betting volume. The right answer depends on what you mean by popular. This article lays out a practical, repeatable way to measure popularity using three public signals: state operator handle and revenue, web and app traffic, and app satisfaction indices. You will learn what each data source shows and misses, how to combine them into a weighted score, and how to adjust for promotions, tax, and market age so your ranking reflects durable popularity rather than a temporary spike.

Popularity is best judged by combining state-reported handle, web traffic, and app satisfaction.

Use multi-month averages and a weighted score to avoid short-term promotional distortions.

State reports from New York, Ohio, and Arizona provide operator-level volume inputs for defensible local rankings.

What "popularity" means for new online sportsbooks

Popularity for new online sportsbooks is not a single number you can read off a chart. For a defensible view you need to combine operator-level betting volume, public web and app traffic, and measures of user experience. The American Gaming Association shows that the U.S. commercial sports betting market has matured and expanded, making volume-based comparisons meaningful as one part of the picture AGA State of the States 2025.

Web traffic studies add a complementary signal: they measure interest and acquisition rather than dollars wagered, and they tend to concentrate visits among a few national brands, which helps confirm which operators get the most attention online Similarweb rankings and additional context in our evaluation how-fundedplays-evaluations-work.

Build a defensible popularity ranking with a simple checklist

Use the ranking checklist in this article to combine volume, traffic, and satisfaction into a single score you can update for your state and preferences.

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When you read the phrase popular online sportsbooks, think of three core signals working together: handle or gross gaming revenue, site and app traffic, and user satisfaction. Treating popularity as a blended metric reduces the risk that any one transient factor, such as a big promotion, will dominate your view.

Why you need multiple data sources to judge a sportsbook

No single data source captures everything. State operator reports reveal betting volume and revenue but not how many casual visitors a brand attracts. For direct, operator-level volume and revenue data you can examine state reports where they exist, which often publish monthly breakdowns by operator New York Mobile Sports Wagering reports.

State reports are authoritative for local betting volume but they are shaped by different tax regimes, promotional practices, and the age of the market. The AGA notes that market maturity and expansion affect revenue totals, so cross-state comparisons require caution and context AGA State of the States 2025.

By contrast, web traffic is a proxy for acquisition, visibility, and marketing reach. Traffic metrics show which brands attract the most visits and where users begin their journey, but they do not translate directly into dollars wagered or per-user revenue, so treat them as a complementary signal rather than a substitute for handle.

App satisfaction studies fill gaps left by volume and traffic: they indicate whether users stick with an app, whether they find the experience smooth, and whether customer support meets expectations. These retention and experience factors are often decisive for long-term popularity J.D. Power 2025 study.

State operator reports: how New York, Ohio, and Arizona reveal market leaders

Several large states publish operator-level monthly reports that make it possible to compare brands by handle and revenue. New York's mobile sports wagering reports include monthly operator splits that are especially useful because the market is large and transparent New York Mobile Sports Wagering reports and the state's Revenue Reports page Revenue Reports.

Ohio's monthly sports gaming revenue reports provide a similar operator-level view, which you can use to calculate local market share by dividing an operator's handle or revenue by the state's total for the month Ohio Casino Control Commission reports.

How can I determine which new online sportsbooks are the most popular in my state?

Combine state operator handle, web and app traffic, and app satisfaction into a weighted score, use multi-month averages to smooth promotions, and prioritize the signals that match your needs for liquidity or user experience.

Arizona publishes event wagering reports with operator breakdowns that give another large-state perspective on which platforms are capturing volume after launch and over time Arizona Department of Gaming reports and the general reports portal Arizona reports.

Reading these reports is practical: look for the monthly handle and gross gaming revenue columns, note promotional adjustments if provided, and calculate a simple market share percentage. That percentage, repeated over several months, becomes a robust volume input for the blended popularity score.

Limitations and caveats of state-reported data

For example, a brand's market share in one state can be inflated by an early launch or a favorable local partnership; operator market share in a single state may not reflect the operator's national reach. Use multiple state reports when possible to reduce local bias.

State tables also omit several important items: they typically do not show cross-device traffic, app download counts, or promotional spending that drives acquisition. Where possible, supplement state volume with traffic and satisfaction measures to see the fuller picture.

What web traffic and Similarweb rankings tell you about new online sportsbooks

Traffic analysis firms show that a small number of national brands capture most sportsbook website visits, which helps confirm which operators dominate attention and acquisition online Similarweb rankings.

Visit concentration often aligns with volume in many states, but it can diverge when operators run heavy promotions or when an app has better conversion from visitors to depositing users. Look at multi-month traffic trends rather than single-month spikes to track sustainable reach.

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To use traffic as an input, compare relative visitation trends over three to six months, and convert them to a normalized score that can be combined with volume and satisfaction. That approach reduces the effect of short-term promotional campaigns on your popularity ranking.

App satisfaction and user experience: the J.D. Power perspective

User experience matters. J.D. Power's 2025 sports betting app study finds that promotions, app performance, and customer support are key drivers of app satisfaction, and satisfied users are more likely to stay and recommend a product J.D. Power 2025 study.

Higher satisfaction tends to support retention and word-of-mouth, which feed back into traffic and, over time, volume. Quick checks you can run yourself include app store ratings, observed load times during peak hours, and a short test of support responsiveness.

Collect these satisfaction signals as normalized scores. When used alongside handle and traffic, they help distinguish brands that attract visitors from those that keep and monetize them efficiently.

A practical framework to rank new online sportsbooks

Combine operator-level handle, web traffic, and app satisfaction into a weighted score so that each signal contributes to a single, interpretable popularity metric. State reports provide the direct volume input, traffic studies provide reach, and satisfaction studies provide retention signals New York Mobile Sports Wagering reports.

Suggested default weights are operator handle 50 percent, traffic 30 percent, and satisfaction 20 percent. Those weights reflect that betting volume determines market impact, but they leave space for acquisition and retention to change the picture. Adjust weights if you care more about liquidity, or about long-term retention instead.

Simple weighted score template combining handle, traffic, and satisfaction

Use normalized inputs

To calculate a score in practice, normalize each input to a 0 to 100 scale. Example: convert an operator's monthly market share to a 0-100 handle score, convert average monthly visits to a 0-100 traffic score, and convert an app satisfaction index to 0-100. Apply the weights and sum the results to get the weighted popularity score.

Run the calculation for the last three months and average the weighted scores to reduce the influence of a single promotional spike. This gives a more durable ranking of new online sportsbooks in your state or across states.

Applying the framework: short state examples

Screenshot style state report table highlighting handle and revenue columns for new online sportsbooks in a minimalist Funded Plays UI

New York is a practical place to test the framework because the state publishes monthly mobile wagering operator splits. Extract an operator's monthly handle and revenue as your volume input, normalize it, and use the result as the handle component of the weighted score New York Mobile Sports Wagering reports.

For Ohio, the state report format is similar and gives a clear operator split you can plug into the same process. Use the Ohio reports to verify whether national rankings in traffic studies align with local volume in Ohio Ohio Casino Control Commission reports.

Arizona's event wagering reports provide another point of comparison, especially useful in newer markets where launch timing can shift early market shares. Combine Arizona's operator splits with traffic and satisfaction scores to see where the raw volume ranking changes once experience and reach are included Arizona Department of Gaming reports.

How promotions, launch timing, and taxes can skew popularity measures

Heavy promotional activity can temporarily inflate traffic and handle; J.D. Power highlights promotions as a key satisfaction driver but also a factor that can distort short-term popularity indicators J.D. Power 2025 study.

Launch timing gives first movers an advantage in early reports. As the AGA explains, market maturity changes revenue totals over time, so adjust for market age when comparing states AGA State of the States 2025.

Tax and regulatory differences affect reported revenue and the apparent efficiency of operator models. To reduce distortion, use multi-month averages and, where possible, compare operators within the same state or region before drawing national conclusions.

Decision criteria: choose the right "most popular" for your needs

If your priority is liquidity and market depth, weight operator handle more heavily. State reports such as those from New York, Ohio, and Arizona provide the most direct support for this choice because they report handle and revenue by operator New York Mobile Sports Wagering reports.

If you prioritize app experience and retention, give more weight to satisfaction and traffic indicators. J.D. Power and traffic studies help identify platforms with higher user satisfaction and steady acquisition, which often predict sustainable popularity J.D. Power 2025 study.

Use this short checklist when choosing which signal to prioritize: do you need deep lines and liquidity, or a smooth app and support? Pick weights accordingly and document your choices so your comparisons stay consistent over time.

Common mistakes and pitfalls when ranking sportsbooks

Avoid relying on a single month of data. Single-month spikes driven by promotions can create misleading impressions of market position; use three- to six-month averages instead and check traffic for signs of sustained interest Similarweb rankings.

Do not equate site visits with betting market share. Lots of traffic does not always mean lots of handle; you need operator-level volume to confirm market share where possible and state reports are the best source for that New York Mobile Sports Wagering reports.

As a verification step, cross-check state reports, traffic trends, and satisfaction scores. If the three signals point in different directions, investigate promotion calendars, app launch dates, or local partnerships before deciding which platform is the most popular for your purpose.

Practical examples: three short scenarios

Scenario A, a large mature state: use New York operator splits as the primary volume input and combine them with multi-month traffic and satisfaction scores to rank stable national leaders. This produces a ranking that favors operators with sustained handle and consistent app experience New York Mobile Sports Wagering reports and traffic confirmation.

Scenario B, a new market with heavy promos: expect promotional spikes in traffic and handle. Smooth the data with a three-month average, discount one-off sign-up offers, and let satisfaction scores indicate whether the operator is retaining users after promotions subside Similarweb rankings.

Scenario C, choosing based on app experience: prioritize J.D. Power-style satisfaction metrics and recent app store trends. This favors platforms with higher retention likelihood even if their current handle is lower in a given state J.D. Power 2025 study.

Conclusion: a balanced way to name the most popular new online sportsbooks

Popularity is multi-dimensional. The most defensible approach combines state operator reports for volume, traffic studies for reach, and satisfaction studies for retention and experience AGA State of the States 2025.

Account for promotions, tax, and market age by using multi-month averages and by comparing operators within the same state where possible. Apply the weighted scoring framework and keep your assumptions transparent so others can reproduce your findings.

Use the methods here to build a repeatable, local-aware ranking of new online sportsbooks that balances market impact with the user experience you care about.

How should I interpret a state's operator report?

Treat it as the best direct source for local betting volume and revenue, then normalize operator numbers to calculate market share over multiple months.

Can web traffic replace volume data?

No. Traffic shows interest and acquisition but does not indicate dollars wagered or revenue per user; use it alongside state volume reports.

Why does app satisfaction matter when measuring popularity?

High satisfaction supports retention and word-of-mouth, helping a sportsbook sustain traffic and volume over time.

Apply the weighted framework to your state, document your weights, and use three- to six-month averages to reduce noise from promotions. If you want to prioritize liquidity, weight handle more heavily; if you value retention, increase the weight for satisfaction. The approach here is reproducible and local-aware, so you can update it as new state reports and traffic studies arrive.