Here are a few use cases for this project:

1. Sports Analytics: The "Horse Racing Level 2" model can be utilized for breaking down video or images from horse races, identifying key features such as the horse's body, number labels, or helmets. This could assist in providing real-time race statistics, horse performance analysis, and tracking the jockey's control by scrutinizing his movement and head orientation.

2. Betting Applications: Computer vision model could be utilized in the creation of platforms for horse racing betting. It can collect data about the horses and their jockeys during the races, enabling users to make informed bets based on a horse's performance or a jockey's strategy visualized by the model.

3. Training Enhancement: Trainers could use this model to monitor and analyze a jockey's form and the horse's performance during training sessions. This could provide crucial insights for improving techniques, strategy and overall performance.

4. Media Coverage: Media outlets could use this model to enhance the viewer's experience by offering deeper insights into the race such as visualizing the number labels, horse details or helmet analysis for audience's better understanding of the race.

5. Event Security: At horse racing events, security officials can use this model to identify specific jockeys or horses based on their helmets and label numbers, respectively. This could assist them in monitoring activities in crowded situations or controlling access to certain areas.

Predicting Horse Races Outcomes

A dataset of horse races collected from multiple sources

About this dataset

The horse races dataset contains information on horse races, runners, and weather conditions. The data can be used to predict the winner of a race, as well as the payout odds for each horse

How to use the dataset

This dataset can be used to predict horse race outcomes. The data includes information on the horses, jockeys, trainers, and other factors that may influence the outcome of a race

Research Ideas

• Use the data to predict which horse will win a race.
• Use the data to predict which horse will place in a race.
• Use the dataset to create features that can be used to train a machine learning model to predict horse races

Acknowledgements

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 at which the data was collected. (DateTime) | | position | The position of the horse in the race. (Integer) | | margin | The margin of the horse in the race. (Float) | | handicap_weight | The handicap weight of the horse in the race. (Float) | | number | The number of the horse in the race. (Integer) | | barrier | The barrier of the horse in the race. (Integer) | | blinkers | Whether or not the horse is wearing blinkers in the race. (Boolean) | | emergency | Whether or not the horse is an emergency in the race. (Boolean) | | form_rating_one | The form rating of the horse in the race. (Float) | | form_rating_two | The form rating of the horse in the race. (Float) | | form_rating_three | The form rating of the horse in the race. (Float) | | last_five_starts | The last five starts of the horse in the race. (List of integers) | | favourite_odds_win | The odds of the horse winning the race if it is the favourite. (Float) | | favourite_odds_place | The odds of the horse placing in the race if it is the favourite. (Float) | | favourite_pool_win | The pool of money that will be won if the favourite horse wins the race. (Float) | | favourite_pool_place | The pool of money that will be won if the favourite horse places in the race. (Float) | | tip_one_win | The odds of the horse winning the race if it is tipped by the first tipster. (Float) | | tip_one_place | The odds of the horse placing in the race if it is tipped by the first tipster. (Float) | | tip_two_win | The odds of the horse winning the race if it is tipped by the second tipster. (Float) | | tip_two_place | The odds of the horse placing in the race if it is tipped by the second tipster. ( |

File: weathers.csv | Column name | Description | |:--------------|:--------------------------------| | name | The name of the horse. (String) |

File: odds.csv | Column name | Description | |:-----------------------------|:------------------------------------------------------------------------------| | collected_at | The date and time at which the data was collected. (DateTime) | | odds_one_win | The odds of the first horse winning the race. (Float) ...

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!

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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) ...

According to a survey conducted in the United States in May 2023, around 10 percent of Hispanic respondents were avid fans of horse racing. Meanwhile, 64 percent of white respondents expressed no interest in the sport.

Unleash the potential of horse racing analytics with our compact yet comprehensive dataset. Whether you're forecasting outcomes, exploring race trends, or assessing performance metrics, this dataset is a crucial asset. It encapsulates race conditions, course details, and performance indicators for horses, trainers, and jockeys. Designed for precision and depth, it equips you with the data to analyze and predict the dynamics of horse racing with confidence. Get ready to transform your strategic bets into winning insights!

The R code used to produce the models in "Predicting the Outcome of a Horse Race"

The Unseen data to test the models created in "Predicting the Outcome of a Horse Race"

Snapshot img

Horse Racing Market Size 2024-2028

The horse racing market size is forecast to increase by USD 114.5 billion, at a CAGR of 14.71% between 2023 and 2028.

The market witnesses an intriguing interplay of trends and challenges. The involvement of younger generations in horse racing is a significant driver, as this demographic brings fresh energy and enthusiasm to the sport. This demographic shift is evident in the increasing popularity of horse racing events that cater to the younger audience, such as music festivals and tech-savvy initiatives. Another trend shaping the market is the growing adoption of online betting platforms. Technology has transformed the way horse racing enthusiasts engage with the sport, allowing for convenient and accessible betting experiences. This shift towards digital platforms is a response to evolving consumer preferences and the convenience they offer.
However, the market is not without challenges. The rising concerns for animal welfare pose a significant obstacle. The horse racing industry faces increasing scrutiny and pressure to ensure the well-being of its equine athletes. Addressing these concerns requires a collaborative effort from all stakeholders, including race organizers, trainers, and governing bodies. By implementing stricter regulations and investing in research and development, the industry can mitigate these challenges and maintain its reputation as a responsible and ethical pastime.

What will be the Size of the Horse Racing Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2018-2022 and forecasts 2024-2028 - in the full report.
Request Free Sample

The market continues to evolve, with various sectors experiencing ongoing dynamics that shape the industry. Veterinary care plays a crucial role in ensuring the wellbeing of equine athletes, with advancements in equine health leading to improved performance and fan engagement. Track conditions and race strategy are critical factors influencing the outcome of races, with media coverage providing real-time updates on these elements. Prize money and performance data are essential tools for horse racing media and gambling regulation, providing valuable insights for fans and stakeholders alike. Social media and online streaming platforms have revolutionized fan engagement, allowing for unprecedented access to racing events and real-time analysis of race statistics.

Governing bodies and racing associations work to maintain integrity and adhere to strict regulations, including drug testing and animal rights. The horse racing industry is a global phenomenon, with events such as the Triple Crown, Royal Ascot, Melbourne Cup, and Breeders' Cup attracting international attention. Racing equipment, including boots, helmets, and racing silks, plays a vital role in ensuring the safety and comfort of horses. Race preparation and training regimens are continually refined to optimize performance, with racing surfaces and race classes catering to various horse breeds and abilities. Pari-mutuel betting and betting exchanges offer fans the opportunity to place wagers on their preferred horses, with fixed odds providing a sense of security and predictability.

Horse racing statistics and betting odds are closely monitored by fans and industry experts, with post-race recovery and race distances influencing the outcome of races. In summary, the market is a dynamic and evolving industry, with various sectors interconnected and influencing one another. From veterinary care and track conditions to fan engagement and gambling regulation, the horse racing industry continues to innovate and adapt to meet the changing needs and expectations of fans and stakeholders.

How is this Horse Racing Industry segmented?

The horse racing industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Type

  Flat racing
  Jump racing
  Harness racing
  Endurance racing


Revenue Stream

  Betting revenue
  Live event revenue
  Broadcasting rights
  Sponsorship and advertising
  Horse sales and breeding


Geography

  North America

    US


  Europe

    France
    UK


  APAC

    Australia
    Japan


  Rest of World (ROW)

By Type Insights

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

Flat horse racing is a globally popular equestrian sport where horses compete over predetermined distances, ranging from 402 to 4,828 meters. The majority of races take place on turf, with North America predominantly using dirt surfaces. This cultural phenomenon attracts millions of spectators annually, particularly in the UK, where it intertwines with fashion and social events. The sport's strategy and uniqu

Introduction:

Greetings, horse racing enthusiasts and data analysts! Today, we embark on an exciting journey into the world of horse racing data analysis. We are pleased to present a comprehensive three-month horse racing dataset available exclusively on Kaggle.

The Kaggle Dataset:

Rich and Comprehensive: Our dataset covers a wide range of horse racing events, including race results, odds, rankings, and more. It's a treasure trove of insights waiting to be discovered.

Ideal for Research: Whether you're a seasoned data scientist, a student conducting research, or simply curious about horse racing, this dataset provides an invaluable resource for your projects.

Limitless Possibilities: Dive into the dataset to analyze historical race outcomes, identify trends, and develop winning strategies. The possibilities for exploration and discovery are boundless.

Unlock More Insights with Horse Racing API:

Looking for real-time updates, deeper statistics, or additional insights? Try Horse Racing API! It complements our Kaggle dataset and offers a wealth of supplementary horse racing data.

To access the API and explore the enhanced features, visit Rapid API.

Take advantage of a limited-time offer: The first 10 users can enjoy FREE access to Horse Racing API. Don't miss out on this opportunity to supercharge your analysis.

If you have questions about using Horse Racing API or need assistance, our support team is here to help. Contact us.

Discover the booming horse racing software market! This in-depth analysis reveals a $500M market in 2025, projected to grow at a 15% CAGR through 2033. Explore key drivers, trends, and regional breakdowns, including top players like Profit Maximizer and BetMix. Learn how data-driven insights are transforming horse racing betting.

According to a survey conducted in the United States in May 2023, around 11 percent of male respondents were avid fans of horse racing. Meanwhile, three quarters of female respondents expressed no interest in the sport.

Between ************** and **************, 2021, a survey was conducted to determine how often adults in the United States bet on horse racing. The majority of respondents, ** percent, stated that they never bet on horse racing. Meanwhile, **** percent of respondents stated that they bet at least once a week.

According to a survey conducted in the United States in May 2023, around 12 percent of respondents aged 35 to 44 were avid fans of horse racing. Meanwhile, 72 percent of respondents aged 65 or older expressed no interest in the sport.

According to a survey conducted in the United States in May 2023, around eight percent of all respondents were avid fans of horse racing. Meanwhile, two thirds of respondents expressed no interest in the sport.

The Horse Racing Licensing report lists all individuals licensed to compete within New York State.

Employment statistics on the Horse Racing Tracks industry in the US

Context

This represents race data for Woodbine Track in Toronto, ON from the period of 06/2015 - 04/2017

In 2023, the total number of runners at horse races administered by the Japan Racing Association (JRA) amounted to approximately **** thousand. The JRA is one of two organs administering horse racing in Japan, the other one being the National Association of Racing (NAR).

Over the past 15 years, the turnover from off course horse race betting in the United Kingdom has been on a general trend of decline. As of March 2024, the figure totaled 3.08 billion British pounds. This was both a decrease over the previous year and 46 percent lower than it had been as of March 2009.

A sample of Betfair data, normally available to those who spend a lot of money wagering. Horse races only. Other sports are available at https://www.kaggle.com/zygmunt/betfair-sports.

See http://data.betfair.com/ for a description.

The file has 688184 data rows. It is 143 MB uncompressed.

Columns:

• EVENT_ID
• COUNTRY
• FULL_DESCRIPTION
• COURSE
• SCHEDULED_OFF
• EVENT
• ACTUAL_OFF
• SELECTION
• SETTLED_DATE
• ODDS
• LATEST_TAKEN (when these odds were last matched on the selection)
• FIRST_TAKEN (when these odds were first matched on the selection)
• IN_PLAY (IP - In-Play, PE - Pre-Event, NI - Event did not go in-play)
• NUMBER_BETS (number of individual bets placed)
• VOLUME_MATCHED (sums the stakes of both back and lay bets)
• SPORTS_ID
• SELECTION_ID
• WIN_FLAG (1 if the selection was paid out as a full or partial winner, 0 otherwise)