The UNITY Odds Feed API – Historical Data Access offers a rich dataset of sports betting odds, covering a global array of leagues and events. This API enables users to retrieve detailed historical odds for both pre-match and live/in-play markets. It includes specific betting metrics such as Asian Handicap, Totals (Over/Under), Corners, and Cards, with data sourced from numerous major Asian sportsbooks and exchanges.

This historical feed is particularly well-suited for:

Data scientists and analysts building predictive models

Sportsbooks improving odds-making strategies

Media platforms generating betting insights

Researchers analyzing market efficiency and odds movement

Key Features: Pre-match and In-play Odds: Track how betting lines moved before and during events.

Multi-Sport Coverage: Includes football (soccer), basketball, and tennis—spanning top leagues like the Premier League, NBA, and Grand Slam tournaments.

Market Breadth: Extensive odds data for niche markets such as corners and cards.

Bookmaker Diversity: Historical odds from a wide range of Asian bookmakers and betting exchanges with low spreads and back/lay functionality.

Structured & Filterable: Access raw or formatted data by sport, league, event, or market.

This API delivers the tools needed to extract meaningful insights from betting markets—whether you're building advanced algorithms, enhancing app features, or deep-diving into betting behavior trends.

About this Dataset

Trying to analyze historical betting odds for whether MLB games will go over or under the betting line? This dataset is for you. More than 13,000 rows include data for all games played between 2013 and 2018.

Category

Sports

Keywords

baseball,mlb,Betting,odds,probability

Row Count

13162

Price

$100.00

Context

National Football League historic game and betting info

Content

National Football League (NFL) game results since 1966 with betting odds information since 1979. Dataset was created from a variety of sources including games and scores from a variety of public websites such as ESPN, NFL.com, and Pro Football Reference. Weather information is from NOAA data with NFLweather.com a good cross reference. Betting data was used from http://www.repole.com/sun4cast/data.html for 1978-2013 seasons. Pro-football-reference.com data was then cross referenced for betting lines and odds as well as weather data. From 2013 on betting data reflects lines available at sportsline.com.

Acknowledgements

Helpful sites with interest in football and sports betting include:

https://github.com/fivethirtyeight/nfl-elo-game

http://www.repole.com/sun4cast/data.html

https://www.pro-football-reference.com/

http://www.espn.com/nfl/

http://www.nflweather.com/

http://www.noaa.gov/weather

https://www.sportsline.com/

https://github.com/jp-wright/nfl_betting_market_analysis

http://www.aussportsbetting.com/data/historical-nfl-results-and-odds-data/

Inspiration

Can you build a predictive model to better predict NFL game outcomes and identify successful betting strategies?

Analysis of ‘NFL scores and betting data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tobycrabtree/nfl-scores-and-betting-data on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

National Football League historic game and betting info

Content

National Football League (NFL) game results since 1966 with betting odds information since 1979. Dataset was created from a variety of sources including games and scores from a variety of public websites such as ESPN, NFL.com, and Pro Football Reference. Weather information is from NOAA data with NFLweather.com a good cross reference. Betting data was used from http://www.repole.com/sun4cast/data.html for 1978-2013 seasons. Pro-football-reference.com data was then cross referenced for betting lines and odds as well as weather data. From 2013 on betting data reflects lines available at sportsline.com.

Acknowledgements

Helpful sites with interest in football and sports betting include:

https://github.com/fivethirtyeight/nfl-elo-game

http://www.repole.com/sun4cast/data.html

https://www.pro-football-reference.com/

http://www.espn.com/nfl/

http://www.nflweather.com/

http://www.noaa.gov/weather

https://www.sportsline.com/

https://github.com/jp-wright/nfl_betting_market_analysis

http://www.aussportsbetting.com/data/historical-nfl-results-and-odds-data/

Inspiration

Can you build a predictive model to better predict NFL game outcomes and identify successful betting strategies?

--- Original source retains full ownership of the source dataset ---

The Challenge

The online sports gambling industry employs teams of data analysts to build forecast models that turn the odds at sports games in their favour. While several betting strategies have been proposed to beat bookmakers, from expert prediction models and arbitrage strategies to odds bias exploitation, their returns have been inconsistent and it remains to be shown that a betting strategy can outperform the online sports betting market. We designed a strategy to beat football bookmakers with their own numbers:

"Beating the bookies with their own numbers - and how the online sports betting market is rigged", by Lisandro Kaunitz, Shenjun Zhong and Javier Kreiner.

Here, we make the full dataset publicly available to the Kaggle community. We also provide the codes, raw SQL database and the online real-time dashboard that were used for our study on github.

Our strategy proved profitable in a 10-year historical simulation using closing odds, a 6-month historical simulation using minute to minute odds, and a 5-month period during which we staked real money with the bookmakers. We would like to challenge the Kaggle community to improve our results:

• Can your strategy consistently beat the sports betting market over thousands of bets across leagues around the world?
• Do time series odds movements offer insightful information that a betting strategy can exploit?
• Can you outperform the bookmakers’ predictions included in the odds data by creating a better model?

What's inside the Beat The Bookie dataset

10 year historical closing odds:

• 479,440 football games from 818 leagues around the world
• Games from 2005-01-01 to 2015-07-30.
• Maximum, average and count of active odds at closing time (start of the match)
• Betting odds from up to 32 providers
• Details about the match: date and time, league, teams, 90-minute score

14-months time series odds:

• 92,647 football games from 1005 leagues around the world
• Games from 2015-09-01 to 2016-11-22
• Hourly sampled odds time series, from up to 32 bookmakers from 72 hours before the start of each game
• Details about the match: date and time, league, teams, 90-minute score

The dataset was assembled over months of scraping online sport portals.

We hope you enjoy your sports betting simulations (but remember... the house always wins in the end).

Acknowledgements

Ben Fulcher was of great help when we were drafting the paper. Ben has also developed a very nice toolbox for time-series analysis, which might be relevant for the analysis of this dataset.

Snapshot img

Sports Betting Market Size 2025-2029

The sports betting market size is forecast to increase by USD 221.1 billion, at a CAGR of 12.6% between 2024 and 2029.

The market is experiencing dynamic growth, driven by the digital revolution and the emergence of machine learning technologies. These advancements enable more accurate predictions and personalized betting experiences for consumers, creating a competitive edge for market participants. Popular betting options include football (soccer), basketball, tennis, horse racing, cricket, and various other sports events. However, this market landscape is not without challenges. Stringent government regulations and restrictions pose significant obstacles, requiring companies to navigate complex legal frameworks and comply with evolving policies.
As the industry continues to evolve, staying informed of regulatory changes and adapting to technological advancements will be crucial for market success. Companies that effectively balance innovation and regulatory compliance will be well-positioned to capitalize on the growing opportunities in the market.

What will be the Size of the Sports Betting Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The market continues to evolve, with dynamic market activities shaping its various sectors. Artificial intelligence (AI) is increasingly being integrated into promotional campaigns, enhancing user experience through personalized recommendations and real-time analysis. Spread betting, a popular form of wagering, employs advanced statistical modeling and risk management techniques. Problem gambling remains a significant concern, with player protection measures such as responsible gambling initiatives and KYC procedures being implemented. Betting odds are visualized through data visualization tools, enabling users to make informed decisions. Live streaming and in-play betting provide real-time updates, while API integration and odds comparison tools facilitate seamless data access.

Machine learning algorithms are used for fraud detection and customer segmentation, ensuring secure payment gateways and AML compliance. Bonus offers and loyalty programs are employed as customer acquisition and retention strategies. Data analytics and betting algorithms enable efficient risk management and effective marketing campaigns. Data feeds from sports data providers are crucial for accurate betting odds and real-time score updates. First goalscorer and correct score bets add excitement to the betting experience. Prop bets and Asian handicap betting cater to diverse user preferences. Live score updates and game integrity are ensured through rigorous security protocols and data encryption.

Pre-match betting and futures betting offer opportunities for long-term investment. Ongoing market activities and evolving patterns underscore the continuous dynamism of the market.

How is this Sports Betting Industry segmented?

The sports betting industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Platform

  Online
  Offline


Type

  Basketball
  Horse riding
  Football
  Others


Betting Type

  Fixed Odds Wagering
  Exchange Betting
  Live/In-Play Betting
  eSports Betting


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    Australia
    China
    India
    Japan


  Middle East and Africa

    UAE


  South America

    Argentina
    Brazil


  Rest of World (ROW)

By Platform Insights

The online segment is estimated to witness significant growth during the forecast period.

The online market is experiencing notable expansion, fueled by technological advancements and favorable regulatory shifts. Key drivers of this growth include the expanding betting market due to continuous innovation in online channels, the increasing availability of mobile platforms with the widespread use of the Internet and smartphones, and the structural migration of customers from retail to online betting in emerging markets. Improvements in platform quality and user experience, particularly through betting applications, further enhance the appeal of online betting. With digitalization on the rise and smartphone penetration increasing, regions such as APAC and MEA present significant opportunities for growth in the online sports betting sector.

Technological advancements have also brought about the integration of various features, such as machine learning algorithms for risk management and player protection, responsible gambling initiatives, API integration, and odds comparison tools. In-play betting, live sc

Global Online Sports Betting Market size was USD 54.56 billion in 2023 and is grow to around USD 142.56 billion by 2032 with a CAGR of roughly 10.5%.

Context

There are some great UFC datasets out there, but I could not find one that included gambling odds.... So I went and made one myself. This dataset focuses very generally on the fights and hopes to be able to draw very broad conclusions. More a more in depth statistical fight analysis I would recommend Rajeev Warrier's excellent datasetwhich was the inspiration for my work.

Content

This dataset consists of 11 columns of data with basic information about every match that took place between March 21, 2010 and March 14, 2020.

Column Definitions:

R_fighter and B_fighter: The names of the fighter in the red corner and the fighter in the blue corner R_odds and B_odds: The American odds of the fighter winning.
date: The date of the fight location: The location of the fight country: The country the fight occurred in Winner: The winner of the fight ('Red' or 'Blue') title_bout: Was this fight a title bout? ('True' or 'False') weight_class: What weight class did this fight occur at? gender: Male or Female

Acknowledgements

I was inspired by the work of Rajeev Warrier

Want More?

My work, including a scraper to help gather data for upcoming events, can be found on my GitHub. I promise I'll add more documentation soon.

In 2024, the sport that had the largest sports betting handle worldwide was soccer. That year, around 780 billion U.S. dollars were wagered on soccer. This was nearly 300 percent higher than the betting handle from basketball.

Explore the historical Whois records related to sportsbetting-lines.net (Domain). Get insights into ownership history and changes over time.

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

The global sports betting market size reached USD 103.08 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 224.12 Billion by 2033, exhibiting a growth rate (CAGR) of 8.56% during 2025-2033. The market is propelled by the rising popularity of e-sports and competitive gaming, increasing adoption of advanced technologies such as virtual reality (VR) and AR, increasing demand for personalized and ergonomic gaming peripherals, rising penetration of internet and smartphones, and cultural enthusiasm among individuals.

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the global, regional, and country levels for 2025-2033. Our report has categorized the market based on platform, betting type, and sports type.

Explore the historical Whois records related to free-sports-odds.com (Domain). Get insights into ownership history and changes over time.

Snapshot img

Horse And Sports Betting Market Size 2025-2029

The horse and sports betting market size is forecast to increase by USD 252 million at a CAGR of 11.4% between 2024 and 2029.

The market is experiencing significant growth, driven by several key trends. One of the primary factors fueling market expansion is the increasing digital connectivity, enabling more consumers to place bets online. Another trend is the rising adoption of advanced technologies such as artificial intelligence (AI) and machine learning, which enhance the betting experience and improve accuracy. However, stringent government regulations pose a challenge to market growth, requiring operators to comply with complex rules and restrictions. Despite these challenges, the market is expected to continue its upward trajectory, offering ample opportunities for stakeholders.

What will be the Size of the Horse And Sports Betting Market During the Forecast Period?

Request Free Sample

The market In the US continues to experience significant growth, driven by the increasing number of internet users and smartphone users. Digital infrastructure and wireless connectivity have enabled online betting to become a convenient and accessible option for individuals seeking to place wagers on athletic events.



Horse racing and horse racing wagering remain popular categories within this market, with past performance and track conditions being key factors in bettors' decision-making processes. The trend towards digitalization is further evidenced by the rise of casino organizations offering fixed odds wagering on horse races, as well as the emergence of esports betting. According to Datareportal, there are currently over 300 million monthly active internet users In the US, and the implementation of 5G networks is expected to further enhance the user experience for mobile device users.

How is this Horse And Sports Betting Industry segmented and which is the largest segment?

The horse and sports betting industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Platform

  Offline betting
  Online betting


Type

  Fixed odds wagering
  Exchange betting
  Live betting
  esports betting
  Others


Geography

  Europe

    Germany
    UK
    Italy


  APAC

    China
    India
    Japan


  North America

    Canada
    US


  South America

    Brazil


  Middle East and Africa

By Platform Insights

The offline betting segment is estimated to witness significant growth during the forecast period.

The market encompasses both online and offline platforms. While online betting is growing in popularity, offline betting remains the largest segment due to various factors. Some individuals prefer the traditional betting experience and are not comfortable with technology. Additionally, government regulations in certain regions limit sports betting to offline channels. Offline betting, including horse racing, is accessible through local bookies and betting shops, allowing customers to bet on credit. The convenience and flexibility of paying later contribute to the continued popularity of offline betting. Despite advancements in technology and the rise of online platforms, offline betting maintains a significant presence In the market.

Get a glance at the Horse And Sports Betting Industry report of share of various segments Request Free Sample

The offline betting segment was valued at USD 219.80 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

APAC is estimated to contribute 48% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

For more insights on the market share of various regions, Request Free Sample

In Europe, the market has experienced significant growth due to the increasing popularity of online betting and the widespread use of smartphones. With Internet connectivity rates averaging between 50% and 60% among European internet users, online betting platforms have gained traction. Regulatory frameworks have become more permissive towards both online and offline betting, creating a secure environment for sports enthusiasts. The presence of numerous bookmakers in major European countries such as Germany, the UK, France, Italy, and Poland, along with the popularity of various sports activities, has further fueled market expansion. Overall, the digital infrastructure and wireless connectivity have enabled easy access to athletic events, making horse and sports betting an increasingly popular pastime in Europe.

Market Dynamics

Our horse and sports betting market researchers analyzed the data with

Use our trusted SportMonks Football API to build your own sports application and be at the forefront of football data today.

Our Football API is designed for iGaming, media, developers and football enthusiasts alike, ensuring you can create a football application that meets your needs.

Over 20,000 sports fanatics make use of our data. We know what data works best for you, so we ensured that our Football API has all the necessary tools you need to create a successful football application.

• Livescores and schedules Our Football API features extremely fast livescores and up-to-date season schedules, meaning your app will be the first to notify its customers about a goal scored. This also works to further improve the look and feel of your website.

• Statistics and line-ups We offer various kinds of football statistics, ranging from (live) player statistics to team, match and season statistics. And that’s not all - we also provide pre-match lineups for all important leagues.

• Coverage and historical data Our Football API covers over 1,200 leagues, all managed by our in-house scouts and data platform. That means there’s up to 14 years of historical data available.

• Bookmakers and odds Build your football sportsbook, odds comparison or betting portal with our pre-match and in-play odds collated from all major bookmakers and markets.

• TV Stations and highlights Show your customers where the football games are broadcasted and provide video highlights of major match events.

• Standings and topscorers Enhance your football website with standings and live standings, and allow your customers to see the top scorers and what the season's standings are.

Online Football Betting Market Outlook

The global online football betting market size was valued at USD 65.5 billion in 2023 and is expected to reach USD 111.2 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.2% during the forecast period. This growth is primarily driven by the increasing popularity of football worldwide, advancements in technology, and the legalization of sports betting across various regions.

One of the primary growth factors for the online football betting market is the widespread digital transformation and technological advancements. With the proliferation of smartphones and enhanced internet connectivity, more individuals are gaining access to online betting platforms. Mobile applications have revolutionized the betting experience by providing user-friendly interfaces, real-time updates, and secure payment methods. Moreover, the integration of advanced technologies like artificial intelligence and data analytics helps bookmakers offer personalized experiences and better odds, further enticing bettors.

Another significant driver is the increasing legalization and regulation of sports betting in numerous countries. Governments are recognizing the potential economic benefits of legalizing sports betting, including job creation, increased tax revenues, and decreased illegal betting activities. For example, the United States Supreme Court's decision in 2018 to lift the federal ban on sports betting has led to a surge in the number of states legalizing the activity. Similarly, many European and Latin American countries are revising their gambling regulations to allow for legalized online sports betting.

The rise of social betting and community engagement is also contributing to the market's growth. Platforms that allow users to share tips, strategies, and experiences have created communities that encourage more people to participate in online betting. Additionally, promotional offers, bonuses, and loyalty programs designed to attract and retain bettors are becoming increasingly sophisticated, further driving market expansion. The gamification of betting platforms, where users can earn rewards and achievements, adds an element of entertainment that appeals to a broader audience.

In recent years, the development of Sports Betting Software has played a pivotal role in transforming the online betting landscape. These software solutions provide bookmakers with robust platforms that are not only scalable but also customizable to cater to diverse market needs. By incorporating features such as real-time data analytics, live streaming, and secure payment gateways, Sports Betting Software enhances the user experience, making it more engaging and interactive. The integration of artificial intelligence within these platforms allows for personalized betting experiences, offering tailored odds and recommendations based on user preferences and betting history. As the demand for seamless and efficient betting experiences grows, the role of Sports Betting Software becomes increasingly critical in driving market expansion and innovation.

From a regional perspective, Europe held the largest market share in 2023 due to the region's strong football culture and established online betting infrastructure. However, Asia Pacific is anticipated to witness the highest growth rate during the forecast period. The region's burgeoning middle class, increased internet penetration, and growing acceptance of online gambling are crucial factors driving this growth. North America is also expected to see substantial growth, particularly with the ongoing legalization efforts in the United States.

Platform Analysis

In the realm of online football betting, the platform segment is divided into mobile and desktop. Mobile platforms have seen an unprecedented rise in popularity due to the convenience and accessibility they offer. The proliferation of smartphones, coupled with advancements in mobile technology, has made betting on the go a seamless experience. Mobile applications provide real-time updates, live streaming options, and user-friendly interfaces, making it easier for bettors to place wagers anytime and anywhere. Additionally, the integration of secure payment gateways and one-click betting options has significantly enhanced user experience and security.

On the other hand, desktop platforms continue to hold a significant share of the market, primarily due to their compreh

According to a January 2024 survey, 72 percent of sports bettors in the United States were male. 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.

oddsDataMLB.csv is historic odds data on MLB games for the 2012-2021 seasons. Odds included are closing numbers - money line, game total, over odds, under odds, run line and run line odds. (Run line data not available for 2012 and 2013). Data also includes runs scored and venue information obtained free of charge from and copyrighted by Retrosheet. Interested parties may contact Retrosheet at www.retrosheet.org.