This dataset provides daily snapshots of UFC/MMA betting odds, automatically updated through a scheduled Kaggle Notebook. It is one of the very few freely available, structured sources of historical MMA betting odds.

What’s inside:

Head-to-head (moneyline) odds for UFC/MMA fights

Fighter-specific odds: win by KO/TKO, Submission, or Decision (when available)

Bookmaker source and region (e.g., DraftKings/US, Unibet/EU)

Event dates and timestamps of data collection

Historical records going back many years, making this a rare resource (most commercial APIs only provide MMA odds history from 2012).

Why it matters:

Historical odds are hard to find online, especially in free, structured format.

Valuable for sports analytics, machine learning models, and betting strategy backtesting.

Safe to use: hosted on Kaggle, a trusted data science platform.

The dataset grows daily: each scheduled run of the notebook appends the newest odds to the master file while preserving the full history.

Dataset

This dataset was created by Evan Hallmark

Contents

Note: The pre-game spread is typically +/- 1.5 goals, in the same way that the pre-game over/under is typically 6.5 total goals.

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

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

Sports Betting Data Feeds Market Outlook

According to our latest research, the global sports betting data feeds market size reached USD 1.75 billion in 2024, reflecting robust growth driven by digital transformation and the increasing legalization of sports betting worldwide. The market is projected to expand at a CAGR of 12.4% from 2025 to 2033, with the total market value forecasted to hit USD 5.06 billion by 2033. This growth trajectory is primarily attributed to the proliferation of online betting platforms, technological advancements in real-time data processing, and the evolving regulatory landscape that continues to favor the adoption of sports betting solutions.

One of the primary growth factors for the sports betting data feeds market is the exponential rise in global sports betting activities, both online and offline. As more countries move towards legalizing sports betting, operators are seeking advanced data feed solutions to enhance their offerings and ensure compliance with regulatory requirements. The surge in popularity of live and in-play betting has created a significant demand for real-time, accurate, and reliable data feeds. Sportsbooks and betting platforms are increasingly relying on sophisticated data feed providers to deliver up-to-the-second information on odds, player statistics, and match outcomes, which not only improves the user experience but also reduces the risk of fraud and errors. Furthermore, the integration of artificial intelligence and machine learning into data feed solutions is enabling operators to provide more personalized and engaging betting experiences, further fueling market growth.

Another key driver is the rapid technological advancements in data transmission and analytics. The emergence of cloud-based infrastructure and API-driven architectures has enabled seamless integration of data feeds into multiple betting platforms, enhancing scalability and operational efficiency. The adoption of advanced analytics tools allows operators to leverage historical and real-time data for predictive modeling, odds calculation, and risk management. In addition, the increasing use of mobile devices for sports betting has necessitated the development of lightweight, high-performance data feed solutions that can deliver instant updates to users regardless of their location. This technological evolution is not only expanding the addressable market but also intensifying competition among data feed providers, leading to continuous innovation and improvement in service quality.

The growing emphasis on regulatory compliance and integrity in sports betting is also shaping the market landscape. Governments and regulatory bodies are imposing stringent requirements on data accuracy, transparency, and anti-fraud measures, compelling operators to invest in high-quality data feed solutions. Data feed providers are responding by enhancing their offerings with features such as real-time monitoring, anomaly detection, and automated reporting to ensure compliance with evolving regulations. The collaboration between sports leagues, betting operators, and data providers is further strengthening the ecosystem, fostering trust and credibility among end-users. As a result, the sports betting data feeds market is witnessing increased adoption across various segments, including sportsbooks, online betting platforms, casinos, and fantasy sports operators.

From a regional perspective, North America and Europe continue to dominate the sports betting data feeds market, accounting for a significant share of global revenues. The United States, in particular, has witnessed a surge in sports betting activities following the repeal of PASPA, with several states legalizing and regulating the industry. Europe, with its well-established betting culture and mature regulatory framework, remains a key market for data feed providers. The Asia Pacific region is emerging as a lucrative market, driven by the rising popularity of online sports betting and the increasing adoption of digital payment solutions. Latin America and the Middle East & Africa are also witnessing steady growth, supported by favorable regulatory developments and expanding internet penetration.

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 trajectory. Software solutions form the backbone of data feed integr

Horse Racing Market Prediction

Tips, Odds, Pool Winnings, and Historical Performance

By Selene Arrazolo [source]

About this dataset

The Horse Racing Market Analysis Dataset is here to help you make informed decisions when it comes to predicting the outcome of a horse race. This comprehensive dataset contains an array of data points that provides insights into factors such as track conditions, weather conditions, total wagers across all runners which can be used to get a clearer understanding on how various elements may influence the outcome of each race. The Markets.csv file also includes crucial details like start time and race number in addition to pool winnings and place margins for each runner in the race. Furthermore, data collected from tipsters can be found within runners.csv along with the odds paid out on each runner's win and place market, form rating of each horse in its past three races, handicap weight and barriers they started from among other metrics. And finally, auxiliary files like conditions CSV which identifies track condition at separate levels or weathers CSV which names weather during particular races provide useful context for understanding when viewing this data set. Through these metrics it is possible gain an insight into what impacts play a bigger role when trying to predict winners so you can increase your chances at placing successful bets!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides data on horse racing market analysis and prediction, including race results, information on the runners and their form, details about the weather and track conditions, odds from various sources, and tips from tipsters.

Research Ideas

• Analyzing betting odds for different races and predicting which horses have the highest probability of winning or placing based on the collected data.
• Comparing weather conditions relative to performance in a race and determining if there is a correlation between the two.
• Creating a predictive model that analyzes different factors such as form ratings, distances, handicap weights or blinkers to provide informed tips for horse racing bettors and punters

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) - You are free to: - Share - copy and redistribute the material in any medium or format for non-commercial purposes only. - Adapt - remix, transform, and build upon the material for non-commercial purposes only. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - You may not: - Use the material for commercial purposes.

Columns

File: runners.csv | Column name | Description | |:-------------------------|:-----------------------------------------------------------------------------------| | collected_at | The date and time the data was collected. (DateTime) | | position | The position of the horse in the race. (Integer) | | margin | The margin of the horse in the race. (Integer) | | handicap_weight | The handicap weight of the horse in the race. (Integer) | | number | The number of the horse in the race. (Integer) | | barrier | The barrier of the horse in the race. (Integer) | | blinkers | Whether the horse is wearing blinkers or not. (Boolean) | | emergency | Whether the horse is an emergency or not. (Boolean) | | form_rating_one | The form rating of the horse in its last race. (Integer) | | form_rating_two | The form rating of the horse in its second last race. (Integer) | | form_rating_three | The form rating of the horse in its third last race. (Integer) | | last_five_starts | The last five starts of the horse. (String) ...

This CSV dataset provides historical odds data for match outcomes of 1, X, and 2 in sports events. Instead of player details, odds values are included, as these encapsulate all relevant information for outcome predictions. The dataset contains

over 30K matches from 2003 to 2024,

covering the top 5 European leagues, the Champions League, and various leagues from Africa and the Americas.

It includes more than 25K odds combinations. (1,X,2)

Winner (Gangant): The target variable, indicating the match outcome, with values:

1: Home team won (odds 1). 0: Match ended in a draw (odds X). 2: Away team won (odds 2). This dataset is ideal for building machine learning or deep learning models aimed at sports betting predictions. For access to the scraping code, please contact me via: LinkedIn: Rayen Jlassi.

github:RayenR1

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

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

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 valued to increase by USD 221.1 billion, at a CAGR of 12.6% from 2024 to 2029. Digital revolution will drive the sports betting market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 33% growth during the forecast period.
By Platform - Online segment was valued at USD 101.20 billion in 2023
By Type - Basketball segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 162.64 billion
Market Future Opportunities: USD 221.10 billion
CAGR from 2024 to 2029 : 12.6%

Market Summary

The market is a dynamic and complex industry, fueled by the intersection of technology and human passion for sports. With an estimated global value of USD155 billion in 2020, this market's growth is driven by the increasing popularity of online betting platforms and the integration of advanced technologies like machine learning. These innovations enable personalized user experiences, real-time data analysis, and more accurate odds calculation. However, the industry faces significant challenges, including stringent government regulations and restrictions. For instance, in some regions, sports betting remains illegal or heavily regulated, limiting market growth potential. Additionally, concerns over problem gambling and match-fixing continue to shape the regulatory landscape.
Despite these hurdles, the future of sports betting looks promising. Technological advancements, such as blockchain and virtual reality, are poised to revolutionize the industry further. As these developments unfold, businesses must adapt and innovate to stay competitive in this rapidly evolving market.

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

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Sports Betting Market 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


  Rest of World (ROW)

By Platform Insights

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

The market is in a constant state of evolution, fueled by technological advancements and regulatory changes. The online betting segment, in particular, is thriving, driven by factors such as the expansion of the overall market, the increasing availability of mobile platforms due to Internet and smartphone penetration, and the structural migration of customers from retail to online betting in emerging markets. Technological innovations include advanced responsible gambling tools, payment gateway integration, customer support ticketing, win probability models, AML compliance software, data visualization tools, and bonus claim processes. Regulatory compliance checks, in-play betting data, sports data providers, geofencing technology, KYC compliance protocols, account management features, transaction processing speed, withdrawal processing times, real-time data feeds, betting exchange liquidity, deposit method integrations, user engagement metrics, customer identity verification, live streaming integration, mobile betting platforms, data analytics dashboards, risk management models, CRM system integration, betting platform security, fraud detection systems, user experience design, player segmentation strategies, and more.

Request Free Sample

The Online segment was valued at USD 101.20 billion in 2019 and showed a gradual increase during the forecast period.

Request Free Sample

Regional Analysis

APAC is estimated to contribute 33% 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.

See How Sports Betting Market Demand is Rising in APAC Request Free Sample

The Asia-Pacific (APAC) region is poised to lead The market due to its rapid expansion and significant population base. Comprising over 60% of the world's population, APAC is a burgeoning market with an increasing number of digital platforms and the adoption of online betting. Key factors contributing to this growth include the presence of gambling hubs like Macau and the rising disposable income of the population.

APAC's dominance in the global sports betting landscape is further reinforced

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

Esports Odds Providers Market Outlook

According to our latest research, the global Esports Odds Providers market size reached USD 1.28 billion in 2024, demonstrating robust momentum with a compound annual growth rate (CAGR) of 13.7% projected through 2033. By 2033, the market is expected to attain a value of USD 3.79 billion, underscoring the rapid expansion and increasing adoption of advanced odds provisioning technologies within the esports betting ecosystem. This impressive growth trajectory is primarily fueled by the proliferation of esports tournaments, the rising integration of real-time data analytics, and expanding partnerships between betting operators and technology providers.

One of the most significant growth factors driving the Esports Odds Providers market is the exponential rise in global esports viewership and participation. The surge in the popularity of competitive gaming, especially among younger demographics, has led to a massive influx of both casual and professional bettors seeking innovative wagering experiences. As esports tournaments attract millions of viewers worldwide, the demand for accurate, real-time, and diverse betting odds has intensified. This, in turn, has prompted odds providers to continuously enhance their offerings, leveraging artificial intelligence and machine learning to deliver dynamic and engaging betting markets. Additionally, the growing acceptance of esports betting as a legitimate and regulated activity in multiple jurisdictions has further legitimized the industry, creating a fertile ground for odds providers to expand their service portfolios.

Another pivotal factor contributing to the market’s growth is the technological evolution within the esports betting landscape. The integration of advanced data analytics, real-time streaming, and cloud-based solutions has revolutionized the way odds are generated and distributed. Odds providers are increasingly adopting sophisticated algorithms to analyze in-game actions, player statistics, and historical data, thereby offering more accurate and appealing odds to betting operators and end-users. The implementation of API-based solutions has also streamlined the delivery of odds across multiple platforms, enhancing user experience and operational efficiency. As a result, technology-driven innovation remains a cornerstone for sustained market growth and competitive differentiation in this space.

Strategic collaborations and partnerships between odds providers, betting operators, and media companies have emerged as a crucial growth catalyst. The convergence of esports content and betting platforms has enabled seamless integration of live odds into broadcasts, interactive streams, and digital platforms, significantly enhancing fan engagement and monetization opportunities. Media companies are increasingly leveraging esports odds data to enrich their content offerings, while betting operators benefit from diversified and customizable odds solutions. This interconnected ecosystem has led to the emergence of new business models and revenue streams, further accelerating the expansion of the Esports Odds Providers market.

Regionally, Asia Pacific continues to dominate the market, accounting for a significant share of global revenues. The region’s vibrant esports culture, coupled with a rapidly expanding digital infrastructure and favorable regulatory environment, has positioned it as a hotspot for both esports betting and odds provisioning services. North America and Europe also represent substantial markets, driven by increasing legalization of sports betting and the presence of established esports organizations. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth, propelled by rising internet penetration and the gradual adoption of esports betting platforms. Each region presents unique opportunities and challenges, shaping the competitive dynamics and growth potential of the global market.

Service Type Analysis

The Service Type&

Access fulltime and halftime results for up to 22 European league divisions from 25 seasons back to 1993/94. Additional match statistics since 2000/01, including shots on goal, corners, fouls, offsides, bookings, red cards and referees, are also available for the major European football leagues, including the English Premiership and lower divisions, the Socttish Premiersip, German Budnesliga, Spanish la Liga, Italian Serie A and French Championnat.

Check out the example csv and Notes.txt that describe the available data.

main Folder --> European main divisions extra Folder --> Extra Leagues

Acknowlegement

Foto von Konstantin Evdokimov auf Unsplash

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.

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