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

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

The market size of the horse racing track industry in the United States was valued at over three billion U.S. dollars in 2020, reflecting a decrease over the previous year's size of almost five billion U.S. dollars. The sector was forecast to reach 3.68 billion U.S. dollars in 2022.

Dataset Description: F1 Races 2000-2024

Overview

This dataset consolidates data from Formula 1 races between 2000 and 2024, designed to facilitate predictive modeling and analytical tasks related to race outcomes. The dataset integrates information from multiple reliable sources, including the Ergast API, VisualCrossing API, and Wikipedia, enriched through feature engineering techniques to enhance its predictive power.

Data Sources

• Ergast API: Provides historical race data including driver and constructor statistics, race results, qualifying times, and more.
• VisualCrossing API: Offers detailed weather data, including precipitation information during race events.
• Wikipedia: Supplies circuit-specific details like the number of turns and track length through automated web scraping.

Dataset Structure

The dataset includes comprehensive race-related attributes categorized as follows: - Race Information: Year, round, circuit ID, and weather conditions. - Driver & Constructor Details: IDs, performance metrics, historical standings, and nationality. - Race Metrics: Grid position, lap times, pit stops, status, and final positions. - Engineered Features: Derived variables such as driver and constructor podium finish percentages, average positions, weighted probabilities based on circuit characteristics, and recent performance trends.

Key Features

• Top 3 Finish: Binary target variable indicating if a driver finished in the top 3.
• Weather Conditions: Binary indicator for rainy conditions during the race.
• Performance Metrics: Historical and seasonal averages for both drivers and constructors.
• Track Characteristics: Number of turns and track length for each circuit.

Potential Use Cases

• Predictive Modeling: Classify and predict podium finishes using machine learning algorithms.
• Performance Analysis: Evaluate driver and constructor performance trends over multiple seasons.
• Feature Engineering Practice: Apply advanced techniques to create new predictive features.

Technical Details

• Data Format: CSV
• Total Records: Over 9,800 race results
• Missing Values: Managed through strategic imputation methods, especially for rookie drivers and new race entries.
• Class Imbalance: Addressed using SMOTE during modeling to ensure balanced predictive outcomes.

Acknowledgments

Special thanks to the contributors of the Ergast API, VisualCrossing API, and the Wikipedia community for providing essential data points that made this dataset possible.

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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.
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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 an

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.

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.

All 311 Service Requests from 2010 to present. This information is automatically updated daily.

Click here to download data from 2011 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2011/fpz8-jqf4

Click here to download data from 2012 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2012/as38-8eb5

Click here to download data from 2013 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2013/hybb-af8n

Click here to download data from 2014 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2014/vtzg-7562

Click here to download data from 2015 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2015/57g5-etyj

Racing Data Acquisition System Market Outlook

In 2023, the global market size of Racing Data Acquisition Systems is estimated to be approximately USD 1.2 billion, with a projected Compound Annual Growth Rate (CAGR) of 6.5% from 2024 to 2032. By 2032, the market size is expected to reach USD 2.1 billion. The growth of this market is largely driven by the increasing adoption of advanced data analytics and telemetry systems in professional racing to enhance performance and improve competitive advantages.

The growth of the Racing Data Acquisition System market can be attributed to several factors. Firstly, the increasing emphasis on precision and performance in professional racing is compelling teams to invest in sophisticated data acquisition systems. These systems help in collecting and analyzing real-time data from various sensors placed on the vehicle, thereby enabling teams to fine-tune performance variables and gain a competitive edge. Additionally, technological advancements such as the integration of machine learning and artificial intelligence in these systems are expected to further drive market growth.

Another significant growth factor is the rising popularity of amateur racing and motorsports. With more enthusiasts entering the racing scene, the demand for high-quality, affordable data acquisition systems is on the rise. This surge in demand is not limited to cars but extends to motorcycles and other racing vehicles as well. As technology becomes more accessible, amateur racers are increasingly seeking robust data acquisition tools to improve their performance and safety on the track.

The integration of Racing Vehicle Engines with data acquisition systems is becoming increasingly prevalent in the motorsport industry. These engines, often the heart of any racing vehicle, provide critical data points that are essential for optimizing performance. By capturing real-time metrics such as RPM, temperature, and pressure, teams can make informed decisions to enhance engine efficiency and reliability. The synergy between advanced engine technology and data acquisition systems allows for precise tuning and adjustments, which are crucial for maintaining a competitive edge on the track. As engine technology continues to evolve, the demand for sophisticated data acquisition tools that can seamlessly integrate with these engines is expected to rise, further driving market growth.

Furthermore, collaborations between racing teams and technology firms are playing a crucial role in driving market expansion. These partnerships facilitate the development of custom solutions tailored to the specific needs of racing teams, covering everything from hardware components to advanced analytics software. This trend is particularly evident in professional racing circuits, where the margin for error is minimal and the stakes are incredibly high.

On the regional front, North America holds a significant share of the Racing Data Acquisition System market, primarily due to the presence of major racing events and teams. The region's advanced technological landscape and high investment capacity make it a hotspot for innovations in data acquisition technologies. Europe follows closely, driven by its rich motorsport heritage and numerous racing leagues. The Asia Pacific region is also witnessing rapid growth, fueled by the rising popularity of motorsports and increasing investments in racing infrastructure.

In addition to data systems, Racing Foot Pedals Kit is gaining attention as a vital component in enhancing driver control and performance. These kits, designed for precision and responsiveness, are crucial for translating driver inputs into vehicle actions with minimal delay. High-quality racing foot pedals kits often feature adjustable settings, allowing drivers to customize the pedal feel and response to suit their driving style. This customization is particularly important in competitive racing, where every millisecond counts. As the racing industry continues to prioritize driver ergonomics and control, the demand for advanced foot pedal kits is expected to grow, complementing the data-driven approach to performance optimization.

Component Analysis

The Racing Data Acquisition System market can be segmented by components into hardware, software, and services. Each of these components plays

Queensland thoroughbred racing club data including scheduled meetings. A specification for this data can be found on the Racing Queensland website.

Employment statistics on the Racing & Individual Sports industry in the US

Market Size statistics on the Horse Racing Tracks industry in United States

Context

This is a data set wrapped from Hong Kong Jockey Club.

Content

There are two parts of the data set, Horse Information and Past Record of the horse, where they came from: http://www.hkjc.com/english/racing/horse.asp?HorseNo=T179 (example link).

The wrapping script in on my github: https://github.com/p768lwy3/HorseRacingHongKong.

Acknowledgements

Thank you for every one who participate in the community.

Inspiration

Hope everyone enjoy.

Context

This dataset contains data of horse racings from 1990 till 2020.

Content

There are two different file types, races and horses, one pair for each year from 1990. I hope to update the current year data on a regular basis.

races_* columns description:

rid - Race id; course - Course of the race, country code in brackets, AW means All Weather, no brackets means UK; time - Time of the race in hh:mm format, London TZ; date - Date of the race; title - Title of the race; rclass - Race class; band - Band; ages - Ages allowed distance - Distance; condition - Surface condition; hurdles - Hurdles, their type and amount; prizes - Places prizes; winningTime - Best time shown; prize - Prizes total (sum of prizes column); metric - Distance in meters; countryCode - Country of the race; ncond - condition type (created from condition feature); class - class type (created from rclass feature).

horses_* columns description:

rid - Race id; horseName - Horse name; age - Horse age; saddle - Saddle # where horse starts; decimalPrice - 1/Decimal price; isFav - Was horse favorite before start? Can be more then one fav in a race; trainerName - Trainer name; jockeyName - Jockey name; position - Finishing position, 40 if horse didn't finish; positionL - how far a horse has finished from the pursued horse, horses corpses; dist - how far a horse has finished from a winner, horses corpses; weightSt - Horse weight in St; weightLb - Horse weight in Lb; overWeight - Overweight code; outHandicap - Handicap; headGear - Head gear code; RPR - RP Rating; TR - Topspeed; OR - Official Rating father - Horse's Father name; mother - Horse's Mother name; gfather - Horse's Grandfather name; runners - Runners total; margin - Sum of decimalPrices for the race; weight - Horse weight in kg; res_win - Horse won or not; res_place - Horse placed or not

forward.csv contains information collected prior a race starts. The odds are averages from from Oddschecker.com, RPRc and TRc also have current values.

Note

Please be aware, the prices provided are the SP (starting prices), and they are not available before race starts. This means prices before start may differ from SP. But usually favorites stay the same, and prices on them often higher then SP. Anyway you can't predict profit with accuracy based only on SP prices.

Inspiration

I suppose prediction of horse racing results by machine learning methods is a difficult task. There is no any highly correlated features, the outcome classes are imbalanced. I tried to make my own predictions, but with no luck. I hope to get some inspirations from your research. Please, share your experience with everyone or just with me. Thank you!

Disclaimer

The data provided has been collected from public open websites, without sign-ups, log-ins and other restrictions from sources. Please, do not use this data for any commercial purposes.

Horse Racing Software Market Outlook

The global horse racing software market size was valued at approximately USD 180 million in 2023 and is forecasted to reach USD 340 million by 2032, growing at a compound annual growth rate (CAGR) of 7.2%. This promising growth trajectory is driven by a variety of factors including the increasing popularity of horse racing as a sport and betting activity, advancements in technology, and the rising demand for sophisticated betting and handicapping software solutions.

One of the key growth factors of the horse racing software market is the increasing adoption of digital platforms and mobile applications. As more users shift from traditional betting methods to online platforms, the demand for reliable, user-friendly, and feature-rich software solutions is steadily rising. This transition is not only making betting and handicapping more accessible but is also attracting a younger demographic, further fueling market expansion. Additionally, the COVID-19 pandemic accelerated the digital transformation across various sectors, including horse racing, thus boosting the market's growth.

Advancements in artificial intelligence (AI) and machine learning (ML) technologies are also playing a pivotal role in the evolution of horse racing software. AI-driven analytics and predictive algorithms have significantly improved the accuracy of handicapping and betting decisions. These technologies enable users to analyze large datasets, consider numerous variables, and generate insights that were previously unattainable. As a result, both novice and experienced bettors are increasingly relying on these advanced software solutions to enhance their betting strategies and outcomes.

The growth of the horse racing software market is further propelled by the rising globalization of horse racing events. Major events like the Kentucky Derby, the Royal Ascot, and the Melbourne Cup attract a global audience, driving cross-border betting activities. This international appeal is fostering the need for software solutions that can cater to diverse markets and comply with various regulatory frameworks. Additionally, the increasing number of racing clubs and betting agencies investing in cutting-edge software to improve their operations and customer experience is contributing to the market's expansion.

Regionally, North America holds a dominant position in the horse racing software market, supported by a strong tradition of horse racing and well-established betting infrastructure. The Asia Pacific region is expected to witness significant growth during the forecast period, driven by the rising popularity of horse racing in countries like Japan, Hong Kong, and Australia. Europe also presents substantial growth opportunities, with countries like the UK and France having a deep-rooted horse racing culture. The Middle East and Africa, while currently a smaller market, are showing potential for growth due to increasing investments in horse racing infrastructure and events.

Product Type Analysis

The horse racing software market is segmented into various product types such as handicapping software, betting software, simulation software, and others. Handicapping software is designed to assist bettors in analyzing racing data and making informed betting decisions. This type of software is increasingly popular among both casual and professional bettors due to its ability to process vast amounts of data and provide statistics, trends, and predictive analytics. The demand for handicapping software is expected to grow significantly as more bettors seek to enhance their betting strategies through data-driven insights.

Betting software, which facilitates the act of placing bets, is another critical segment. These platforms offer a seamless betting experience, often integrating live odds, race schedules, and secure payment gateways. Betting software is particularly popular among betting agencies and individual users who prefer the convenience of online betting. With the growing trend of mobile betting, software developers are focusing on creating mobile-friendly platforms that offer the same functionalities as their desktop counterparts, thereby expanding their user base.

Simulation software provides a virtual racing experience, allowing users to simulate horse races for entertainment or training purposes. This type of software is gaining traction among horse racing enthusiasts who enjoy the thrill of racing without the financial risks associated with real betting. Additionally, racing clubs and training centers use simulation sof

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

The statistic displays the results of a survey on the people who participated in horse race gambling at least once in the past four weeks in Great Britain (GB) from 2015 to 2020. In 2020, approximately *** percent of respondents participated in horse races gambling at least once in the past four weeks, a decrease over the previous year.

Financial overview and grant giving statistics of Fair Circuit Horse Racing

Macau Gaming: Gross Revenue: Horse Racing data was reported at 19.000 MOP mn in Sep 2018. This records a decrease from the previous number of 26.000 MOP mn for Jun 2018. Macau Gaming: Gross Revenue: Horse Racing data is updated quarterly, averaging 91.000 MOP mn from Mar 2005 (Median) to Sep 2018, with 55 observations. The data reached an all-time high of 248.000 MOP mn in Mar 2005 and a record low of 19.000 MOP mn in Sep 2018. Macau Gaming: Gross Revenue: Horse Racing data remains active status in CEIC and is reported by Gaming Inspection and Coordination Bureau. The data is categorized under Global Database’s Macau SAR – Table MO.Q017: Gaming Statistics.

Description The F1 Regulations, Safety, and Racing Performance dataset provides an overview of key factors influenced by the evolving Fédération Internationale de l'Automobile (FIA) regulations from 1990 to 2023. This dataset includes metrics such as the number of teams, drivers, races, fatalities, car weight, DRS implementation, and overtakes. It tracks the introduction of new regulations each season, especially those impacting aerodynamics, making it an essential resource for analyzing the long-term effects of regulatory changes on safety, racing dynamics, and overall spectacle in Formula 1.

The dataset enables detailed investigations into how FIA regulations have shaped the sport in terms of performance, safety improvements, and the number of overtakes, providing valuable insights into the interaction between these factors.

Columns:

Season: The year the data corresponds to (1990–2023). Number of Teams: The number of teams participating in each season. Number of Drivers: The total number of drivers competing each season. Number of Races: The number of races held in each season. Number of New Regulations: The number of new FIA regulations introduced in each season. New Regulations Impacting Aerodynamics: The number of new regulations specifically targeting car aerodynamics. Fatalities: The number of driver fatalities recorded during each season. Average Car Weight (kg): The average weight of Formula 1 cars for the corresponding season. DRS: A Boolean value indicating whether the Drag Reduction System (DRS) was available during the season (True/False). Overtakes: The total number of overtakes recorded in a season.

Related Research For an in-depth analysis based on this data, please refer to the paper: Statistical Analysis of the Impact of FIA Regulations on Safety, Racing Dynamics, and Spectacle in Formula 1.

Data Collection Disclaimer The dataset has been manually collected from various public sources and historical records. Although extensive care has been taken to ensure its accuracy, there may be minor errors or inconsistencies in the data. This limitation is mitigated by cross-referencing data where possible. Users are encouraged to verify critical information where necessary.