Online Sports Betting

A State-by-State Comparison

About this dataset

How prevalent is sports betting across the United States? This dataset provides information on the legal status of sports betting, revenue generated by sports betting, the number of sports betting outlets, and more. Use this dataset to compare the revenue generated by sports betting across different states

How to use the dataset

This dataset can be used to understand the prevalence of sports betting across the United States and to compare the revenue generated by sports betting across states.

Research Ideas

• Understand the prevalence of sports betting across the United States and to compare the revenue generated by sports betting across states
• Understand how the legal status of sports betting affects revenue generated
• Understand how the number of sports betting outlets affects revenue generated

Columns

File: New Jersey.csv | Column name | Description | |:------------------|:--------------------------------------------------------------| | date | The date of the data. (Date) | | New Jersey | The amount of money bet on sports in New Jersey. (Numeric) | | Pennsylvania | The amount of money bet on sports in Pennsylvania. (Numeric) | | Delaware | The amount of money bet on sports in Delaware. (Numeric) | | Mississippi | The amount of money bet on sports in Mississippi. (Numeric) | | Nevada | The amount of money bet on sports in Nevada. (Numeric) | | Rhode Island | The amount of money bet on sports in Rhode Island. (Numeric) | | West Virginia | The amount of money bet on sports in West Virginia. (Numeric) | | Arkansas | The amount of money bet on sports in Arkansas. (Numeric) | | New York | The amount of money bet on sports in New York. (Numeric) | | Iowa | The amount of money bet on sports in Iowa. (Numeric) | | Indiana | The amount of money bet on sports in Indiana. (Numeric) | | Oregon | The amount of money bet on sports in Oregon. (Numeric) | | New Hampshire | The amount of money bet on sports in New Hampshire. (Numeric) | | Michigan | The amount of money bet on sports in Michigan. (Numeric) | | Montana | The amount of money bet on sports in Montana. (Numeric) | | Colorado | The amount of money bet on sports in Colorado. (Numeric) | | Washington DC | The amount of money bet on sports in Washington DC. (Numeric) | | Illinois | The amount of money bet on sports in Illinois. (Numeric) | | Tennessee | The amount of money bet on sports in Tennessee. (Numeric) |

File: PopulationStates.csv | Column name | Description | |:--------------|:----------------------------------------------------| | State | The state in which the data was collected. (String) |

File: homeless.csv | Column name | Description | |:----------------|:----------------------------------------------------| | year | The year the data was collected. (Integer) | | unsheltered | The number of people who are unsheltered. (Integer) |

File: income.csv | Column name | Description | |:------------------|:--------------------------------------------------------------| | Pennsylvania | The amount of money bet on sports in Pennsylvania. (Numeric) | | Delaware | The amount of money bet on sports in Delaware. (Numeric) | | Mississippi | The amount of money bet on sports in Mississippi. (Numeric) | | Nevada | The amount of money bet on sports in Nevada. (Numeric) | | Rhode Island | The amount of money bet on sports in Rhode Island. (Numeric) | | West Virginia | The amount of money bet on sports in West Virginia. (Numeric) | | Arkansas | The amount of money bet on sports in Arkansas. (Numeric) | | New York | The amount of money bet on sports in New York. (Numeric) | | Iowa | The amount of money bet on sports in Iowa. (Numeric) | | Indiana | The amount of money bet on sports in Indiana. (Numeric) | | New Hampshire | The amount of money bet on sports in New Hampshire. (Numeric) | | Michigan | The amount of money bet on sports in Michigan. (Numeric) | | Colorado | The amount of money bet on sports in Colorado. (Numeric) | | Washington DC | The amount of money bet on sports in Washington DC. (Numeric) | | Illinois | The amount of money bet on sports in Illinois. (Nume...

According to a January 2025 survey conducted among adults in the United States, ***percent of male respondents said they had an online sports betting account. Meanwhile, the figure for women stood at ** percent. Sports betting has been allowed in certain states in the U.S. since the federal ban was lifted by the Supreme Court in May 2018.

According to a 2025 survey, the age group with the largest share of individuals with an online sports betting acount in the United States was ********-years-old. In total, ** percent of U.S. adults belonging to this demographic had an account with an online sportsbook.

This dataset contains simulated sports betting data representing 100,000 bets placed by 5,000 users across a variety of sports. It was created trying to reproduce realistic betting behavior, including betting amounts, sports distributions, win/loss outcomes, and user-specific statistics.

Each user could fall into a betting profile based on their behaviour.

In 2024, ** percent of sports betting handle in Asia came from bets on soccer. This was a higher share than any other continent. On the other end of the scale, soccer bets only made up only *** percent of the sports betting handle in North America.

Yearly and monthly growth charts for sports betting in Pennsylvania , including handle, revenue, and growth metrics

Notes: (1) Monthly payments are due to the State by the 15th of the following month. (2) The operation of the online sports wagering began on October 12, 2021. (3) Monthly resettlements are wagers where the original settled wager result is modified due to an error or change in result of the underlying event. (4) Federal Excise Tax is 0.25% of Net Wagers. (5) This amount shall only include coupons and credits issued for use for gaming in the state and redeemed in the State of Connecticut. (6) Per Public Act 21-23, from October 2021 – September 2022 the promotional deduction is limited to the lesser of 25% of sports wagering Win/Loss, or actual promotional coupons or credits wagered. From October 2022 – September 2023 this limit drops to 20%, and to 15% thereafter.. (7) Payment rate is 13.75% of Gross Gaming Revenue. Monthly payment is the greater of the calculated payment or $0 (if calculated payment is negative). (8) In May 2022, MPI Master Wagering License CT, LLC reclassified $2.6M of certain bets from October 2021 - March 2022 originally reported as resettlements, as winnings. This had no impact on Gross Gaming Revenue or payments to the state because winnings and resettlements are treated the same in the GGR calculation. Corrected amounts are reported above. (9) In May 2022, MPI Master Wagering License CT, LLC revised its October 2021 filing to reflect patron winnings that were cashed after the close of operations during the limited hours of Soft Launch. This adjustment reduced the payment due to the State of Connecticut by $31,669; taken as a credit against the May 2022 payment due. (10) In July 2024, Mohegan Digital, LLC's online gaming operator identified and reported data latency issues that caused errors in the May 2024 payment calculations submitted to the State of Connecticut. Mohegan Digital, LLC amended their May 2024 return, which resulted in an increase of $15,952 in both Wagers and Cancelled Wagers, an Increase of $5,375 in Patron Winnings, and a decrease of $5,375 in Monthly Resettlements. Amended figures are shown above.

Yearly and monthly growth charts for sports betting in Tennessee , including handle, revenue, and growth metrics

Yearly and monthly growth charts for sports betting in Rhode Island , including handle, revenue, and growth metrics

In July 2023, a survey was conducted to determine the share of sports bettors in the United States that place bets online vs. in person. The majority of respondents, almost **********, stated that they preferred to place bets online or via mobile. Comparatively, **** percent of survey participants said that they liked placing bets in-person.

Yearly and monthly growth charts for sports betting in Colorado , including handle, revenue, and growth metrics

In 2023, Sports Betting Market reached a value of USD 113.54 billion, and it is projected to surge to USD 223.66 billion by 2030

Yearly and monthly growth charts for sports betting in Ohio , including handle, revenue, and growth metrics

Yearly and monthly growth charts for sports betting in South Dakota , including handle, revenue, and growth metrics

The global sports betting data service market size was valued at USD 1.3 billion in 2025 and is projected to grow from USD 1.5 billion in 2026 to USD 3.1 billion by 2033, exhibiting a CAGR of 10.4% during the forecast period. The increasing popularity of sports betting and the growing demand for data-driven insights to make informed betting decisions are driving the growth of the market. Furthermore, the advancements in technology, such as artificial intelligence (AI) and machine learning (ML), are enabling the provision of more accurate and personalized data, which is further fueling the market growth. The market is segmented into various applications including sports media, sports teams, sponsor brands, and others. The sports media segment held the largest market share in 2025 and is expected to continue its dominance throughout the forecast period. This is attributed to the increasing demand for sports betting data by media companies to enhance their coverage and provide value-added services to their viewers. Other key segments include sports teams, which use data to analyze player performance and make strategic decisions, and sponsor brands, which use data to measure the effectiveness of their campaigns and optimize their marketing strategies. Geographically, North America accounted for the largest market share in 2025 and is projected to maintain its dominance during the forecast period. The region's high adoption of sports betting and the presence of major sports leagues are driving the growth of the market. Europe and Asia Pacific are other key regions with significant market potential due to the growing popularity of sports betting and the increasing investment in data analytics. Introduction The global sports betting data service market has witnessed a surge in demand as the legalization of sports betting expands across jurisdictions. These services provide valuable data and insights to sportsbooks, media companies, and other stakeholders to enhance their operations and engage audiences.

Sports Betting Data Feeds Market Outlook

According to our latest research, the global sports betting data feeds market size stood at USD 1.35 billion in 2024, reflecting robust industry momentum and significant technological advancements. The market is poised to expand at a CAGR of 10.7% from 2025 to 2033, reaching a forecasted value of USD 3.13 billion by 2033. This impressive growth trajectory is primarily driven by the increasing legalization of sports betting across various jurisdictions, the proliferation of digital betting platforms, and the rising demand for real-time, accurate, and comprehensive sports data feeds among bookmakers and operators worldwide.

The primary growth driver for the sports betting data feeds market is the rapid expansion of online sports betting, fueled by widespread internet penetration and the proliferation of smartphones. As more countries move towards legalizing and regulating sports betting, the need for reliable, real-time data has become paramount for both operators and bettors. This surge in digital engagement is compelling bookmakers and betting operators to invest heavily in advanced data feed solutions that deliver pre-match, in-play, and historical data, thereby enhancing user engagement and optimizing betting outcomes. Furthermore, the integration of artificial intelligence and machine learning into data feed platforms is enabling more precise odds-making and fraud detection, further bolstering market growth.

Another significant growth factor is the increasing collaboration between sports leagues, federations, and data feed providers. Sports organizations are recognizing the value of monetizing their data assets and partnering with technology firms to distribute official and exclusive data feeds. These alliances not only ensure the authenticity and integrity of data but also open new revenue streams for sports bodies. Additionally, as consumer expectations for immersive and interactive betting experiences rise, data feed providers are innovating with enriched content such as live statistics, player tracking, and video feeds, which are rapidly becoming standard offerings in the competitive landscape.

The globalization of sports betting is also contributing to the upward trajectory of the sports betting data feeds market. Emerging markets in Asia Pacific, Latin America, and Africa are witnessing a surge in sports betting activities, driven by favorable regulatory shifts and the growing popularity of international sports. This global expansion is compelling data feed providers to diversify their offerings, support multiple sports and languages, and ensure scalability and compliance across jurisdictions. As a result, the market is experiencing an influx of new entrants and increased investments, further intensifying competition and accelerating innovation in data delivery and analytics.

From a regional perspective, Europe continues to dominate the sports betting data feeds market, accounting for the largest revenue share in 2024, closely followed by North America. The mature regulatory environment, high consumer adoption, and presence of leading sports data providers have positioned these regions at the forefront of industry innovation. Meanwhile, Asia Pacific is emerging as the fastest-growing region, with a projected CAGR exceeding 12% through 2033, driven by the rapid legalization of sports betting and the increasing popularity of esports and mobile gaming. Latin America and the Middle East & Africa are also witnessing steady growth, supported by evolving regulatory frameworks and increased investments in digital infrastructure.

Component Analysis

The sports betting data feeds market is segmented by component into software and services, each playing a pivotal role in shaping the industry’s ecosystem. Software solutions form the backbone of data feeds, providing the infrastructure necessary for the aggregation, processing, and dissemination of sports data. These platforms are designed to handle vast volumes of real-time information, in

Context

A dear friend of mine has a sport betting company in Brazil called Game Winner (https://gamewinner.com.br/), and I asked him to provide their data so I could publish and analyze.

Content

All data (dates, bets, criterias results) is from 2022.

Acknowledgements

I would like to thank Rodrigo Mota (https://www.linkedin.com/in/rodrigo-mota-358b939a/) for providing the data and some explanations about it.

Inspiration

Is the company perfoming really well all the time? Is it possible to predict outcomes?

Sports Betting Predictive Analysis Dataset

This comprehensive synthetic dataset contains 1,369 rows and 10 columns specifically designed for predictive modeling in sports betting analytics. The dataset provides a rich foundation for machine learning applications in the sports betting domain, featuring realistic match data across multiple sports with comprehensive betting odds, team information, and outcome predictions.

Dataset Overview Table

Key Applications

Machine Learning Use Cases

• Outcome Prediction Models: Train classification algorithms to predict match winners
• Odds Analysis: Analyze betting market efficiency and identify value bets
• Feature Engineering: Create derived features for advanced predictive models
• Model Validation: Compare predicted vs actual outcomes for performance metrics
• Risk Assessment: Evaluate betting strategy performance and risk management

Data Science Applications

• Exploratory Data Analysis: Understand patterns in sports betting markets
• Statistical Modeling: Build probabilistic models for outcome prediction
• Time Series Analysis: Analyze temporal trends in betting odds and outcomes
• Comparative Analysis: Study performance differences across sports and teams
• Visualization Projects: Create interactive dashboards for betting analytics

Research Applications

• Academic Research: Study sports betting market dynamics
• Algorithm Development: Test new machine learning approaches
• Benchmarking: Compare different predictive modeling techniques
• Educational Projects: Learn data science concepts with realistic data
• Portfolio Development: Demonstrate skills in sports analytics domain

Data Characteristics

Realistic Market Simulation

• Betting odds within industry-standard ranges (1.2 - 5.0)
• Sport-specific logic (draws only applicable for Football and Hockey)
• Strategic null value placement to simulate real-world data gaps
• Temporal consistency across 2-year historical period
• Unique match identifiers for easy reference and tracking

Comprehensive Coverage

• Multi-Sport Analysis: Five major sports for diverse modeling scenarios
• Balanced Distribution: Even representation across all sports categories
• Team Diversity: Unique city-based team names preventing data leakage
• Outcome Variety: Includes wins, losses, and draws where applicable
• Prediction Comparison: Both model predictions and actual results included

This dataset offers a comprehensive and dynamic overview of the evolving landscape of online sports betting within the state.

Notes: (1) Monthly payments are due to the State by the 15th of the following month. (2) The operation of the online sports wagering began on October 12, 2021. (3) Monthly resettlements are wagers where the original settled wager result is modified due to an error or change in result of the underlying event. (4) Federal Excise Tax is 0.25% of Net Wagers. (5) This amount shall only include coupons and credits issued for use for gaming in the state and redeemed in the State of Connecticut. (6) Per Public Act 21-23, from October 2021 – September 2022 the promotional deduction is limited to the lesser of 25% of sports wagering Win/Loss, or actual promotional coupons or credits wagered. From October 2022 – September 2023 this limit drops to 20%, and to 15% thereafter.. (7) Payment rate is 13.75% of Gross Gaming Revenue. Monthly payment is the greater of the calculated payment or $0 (if calculated payment is negative). (8) In May 2022, MPI Master Wagering License CT, LLC reclassified $2.6M of certain bets from October 2021 - March 2022 originally reported as resettlements, as winnings. This had no impact on Gross Gaming Revenue or payments to the state because winnings and resettlements are treated the same in the GGR calculation. Corrected amounts are reported above. (9) In May 2022, MPI Master Wagering License CT, LLC revised its October 2021 filing to reflect patron winnings that were cashed after the close of operations during the limited hours of Soft Launch. This adjustment reduced the payment due to the State of Connecticut by $31,669; taken as a credit against the May 2022 payment due.

When surveyed between July 2024 and October 2024, it was found that **** percent of adults in Great Britain had participated in online sports betting. In comparison, **** percent had bet on sports in person.