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.

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.

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

This statistic shows sports betting activities U.S. consumers participated in in the past 12 months in 2017 according to a Statista survey. 47 percent of survey respondents said they placed a bet on a sporting event with a friend.

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

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?

The U.S. Online Sports Betting Market Size Was Worth USD 14 Billion in 2023 and Is Expected To Reach USD 33 Billion by 2032, CAGR of 10.3%.

A January 2024 survey in the United States revealed that the highest proportion of fans who placed bets on basketball in the past 12 months were aged between 25 and 34. Meanwhile, only 4.3 percent of fans aged 65 or over placed bets.

Yearly growth chart for sports betting in US states, including handle, revenue, and growth metrics

Our NFL Data product offers extensive access to historic and current National Football League statistics and results, available in multiple formats. Whether you're a sports analyst, data scientist, fantasy football enthusiast, or a developer building sports-related apps, this dataset provides everything you need to dive deep into NFL performance insights.

Key Benefits:

Comprehensive Coverage: Includes historic and real-time data on NFL stats, game results, team performance, player metrics, and more.

Multiple Formats: Datasets are available in various formats (CSV, JSON, XML) for easy integration into your tools and applications.

User-Friendly Access: Whether you are an advanced analyst or a beginner, you can easily access and manipulate data to suit your needs.

Free Trial: Explore the full range of data with our free trial before committing, ensuring the product meets your expectations.

Customizable: Filter and download only the data you need, tailored to specific seasons, teams, or players.

API Access: Developers can integrate real-time NFL data into their apps with API support, allowing seamless updates and user engagement.

Use Cases:

Fantasy Football Players: Use the data to analyze player performance, helping to draft winning teams and make better game-day decisions.

Sports Analysts: Dive deep into historical and current NFL stats for research, articles, and game predictions.

Developers: Build custom sports apps and dashboards by integrating NFL data directly through API access.

Betting & Prediction Models: Use data to create accurate predictions for NFL games, helping sportsbooks and bettors alike.

Media Outlets: Enhance game previews, post-game analysis, and highlight reels with accurate, detailed NFL stats.

Our NFL Data product ensures you have the most reliable, up-to-date information to drive your projects, whether it's enhancing user experiences, creating predictive models, or simply enjoying in-depth football analysis.

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%.

A January 2024 survey in the United States revealed that the largest proportion of fans who placed bets on hockey in the past 12 months were aged between 25 and 34. Meanwhile, only *** percent of fans aged 65 or over placed bets.

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

A January 2024 survey in the United States revealed that the highest proportion of fans who placed bets on baseball in the past 12 months were aged between 25 and 34. Meanwhile, around 3.5 percent of fans aged 65 or older placed bets.

The UNITY Soccer API is a powerful solution for delivering highly accurate, real-time football (soccer) odds to sportsbooks, betting apps, affiliate platforms, and data-driven systems. As part of the broader UNITY Odds Feed API, the Soccer API is engineered for speed, scalability, and flexibility—allowing seamless integration of betting markets across the world’s most popular sport.

The UNITY Soccer API is a robust, enterprise-grade solution that powers football betting platforms with real-time, historical, and highly accurate data. With extensive market coverage, flexible customization, and deep global reach, it supports any betting-related use case—whether you're building a full-scale sportsbook, launching a mobile app, or analyzing data for predictive modeling.

Combined with a powerful support infrastructure, seamless integration tools, and competitive bookmaker data, the UNITY Soccer API is the ideal foundation for your next-generation football betting solution.

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 live-football-betting-odds.com (Domain). Get insights into ownership history and changes over time.