Select your cookie preferences

We use essential cookies and similar tools that are necessary to provide our site and services. We use performance cookies to collect anonymous statistics, so we can understand how customers use our site and make improvements. Essential cookies cannot be deactivated, but you can choose “Customize” or “Decline” to decline performance cookies.

If you agree, AWS and approved third parties will also use cookies to provide useful site features, remember your preferences, and display relevant content, including relevant advertising. To accept or decline all non-essential cookies, choose “Accept” or “Decline.” To make more detailed choices, choose “Customize.”

Sign in
Your Saved List Become a Channel Partner Sell in AWS Marketplace Amazon Web Services Home Help

Australian Horse Racing Data for Machine Learning (Large)

Provided By: SHENIT

Australian Horse Racing Data for Machine Learning (Large)

Provided By: SHENIT

More than 5 years of most recent Australian horse racing data in CSV format. The data is detailed per horse per race. The data is curated and featured and is ready to be used for developing machine learning algorithms. The dataset is refreshed monthly at the beginning of a month.

Product offers

The following offers are available for this product. Choose an offer to view the pricing and access duration options for the offer. Select an offer and continue to subscribe. Your subscription begins on the date that you accept the offer. Additional taxes or fees might apply.

Public offer

Payment schedule: Upfront payment | Offer auto-renewal: Supported
$495 for 1 month$695 for 6 months$795 for 12 months

Overview

Most recent Australian horse racing (thoroughbred) data points (approx 1,000,000 data points) are in one CSV file.

  • Each data point has race details such as Meeting Name, Meeting Date, location, and Weather Condition. All column names are listed below
  • Each data point represents a horse (runner) stats before the race and the finishing position for the coming race such as Overall Starts, Overall Wins, Overall Placings
  • Each data point has the stats of the jockey and the trainer such as Last 12 Months Trainer Starts, Last 12 Months Trainer Wins, Last 30 Days Rider Wins

The data is cleaned, featured and interpreted into numbers, which helps speed up data engineering and feature engineering processes and saves your time and cost on data sourcing, data cleaning, and data transformation.

For developing your machine learning algorithms, you could simply split the CSV file with 80 (Training)/20 (Testing) or whatever ratio you would like. Column 'finishingPosition' represents the result that the horse has raced:

  • '1' means the horse finished at 1st place
  • '2' means the horse finished at 2nd place
  • '3' means the horse finished at 3rd place
  • '4' means the horse finished at 4th place
  • '0' means the horse finished at out of the first 4 or 3 places
  • '-2' means the horse was scratched

The data points from the previous month are appended to the dataset at the start of the subsequent month.

The columns with examples:

  • finishingPosition: 1
  • meetingName: CAULFIELD
  • meetingDate: 17/9/2022 12:00:00 am
  • raceNumber: 5
  • runnerNumber: 5
  • runnerName: BOOGIE DANCER
  • riderName: L.NOLEN
  • location:
  • weatherCondition: SHWRY
  • trackCondition: HVY9
  • raceName: THOUSAND GUINEAS PRELUDE
  • raceStartTime: 17/9/2022 2:55:00 pm
  • raceDistance: 1400
  • trackDirection:
  • raceClassConditions: 3F-GP2
  • FixedWinOpen_Reference: 6.5
  • FixedWinClose_Reference: 5.5
  • overall_runner_starts: 5
  • track_runner_starts: 1
  • firm_runner_starts: 0
  • good_runner_starts: 0
  • dead_runner_starts: 1
  • slow_runner_starts: 2
  • soft_runner_starts: 3
  • heavy_runner_starts: 2
  • distance_runner_starts: 2
  • classSame_runner_starts: 0
  • classStronger_runner_starts: 0
  • firstUp_runner_starts: 1
  • secondUp_runner_starts: 1
  • trackDistance_runner_starts: 1
  • overall_runner_wins: 3
  • track_runner_wins: 1
  • firm_runner_wins: 0
  • good_runner_wins: 0
  • dead_runner_wins: 1
  • slow_runner_wins: 1
  • soft_runner_wins: 2
  • heavy_runner_wins: 1
  • distance_runner_wins: 2
  • classSame_runner_wins: 0
  • classStronger_runner_wins: 0
  • firstUp_runner_wins: 0
  • secondUp_runner_wins: 1
  • trackDistance_runner_wins: 1
  • overall_runner_placings: 0
  • track_runner_placings: 0
  • firm_runner_placings: 0
  • good_runner_placings: 0
  • dead_runner_placings: 0
  • slow_runner_placings: 0
  • soft_runner_placings: 0
  • heavy_runner_placings: 0
  • distance_runner_placings: 0
  • classSame_runner_placings: 0
  • classStronger_runner_placings: 0
  • firstUp_runner_placings: 0
  • secondUp_runner_placings: 0
  • trackDistance_runner_placings: 0
  • track_trainer_starts: 74
  • region_trainer_starts: 248
  • last30Days_trainer_starts: 48
  • last12Months_trainer_starts: 481
  • jockey_trainer_starts: 139
  • track_trainer_wins: 9
  • region_trainer_wins: 35
  • last30Days_trainer_wins: 11
  • last12Months_trainer_wins: 96
  • jockey_trainer_wins: 29
  • track_trainer_placings: 20
  • region_trainer_placings: 63
  • last30Days_trainer_placings: 8
  • last12Months_trainer_placings: 128
  • jockey_trainer_placings: 38
  • track_rider_starts: 28
  • region_rider_starts: 150
  • last30Days_rider_starts: 51
  • last12Months_rider_starts: 382
  • runner_rider_starts: 1
  • track_rider_wins: 1
  • region_rider_wins: 18
  • last30Days_rider_wins: 8
  • last12Months_rider_wins: 61
  • runner_rider_wins: 0
  • track_rider_placings: 5
  • region_rider_placings: 28
  • last30Days_rider_placings: 10
  • last12Months_rider_placings: 88
  • runner_rider_placings: 0
  • runner_scratched: 0
  • race_abandoned: 0
Provided By
Fulfillment Method
AWS Data Exchange

Data sets (1)

You will receive access to the following data sets

Revision access rules
Last 1 revision | All future revisions
Name
Type
Data dictionary
AWS Region
Australian Horse Racing Runner's Data for Machine Learning (Large)
Not included
Asia Pacific (Sydney)

Data dictionaries and samples

Sample data is for evaluation purposes only and may not accurately represent the actual content of the product.

Name
Resource
File type
File size
Description
Australian Horse Racing Runner's Data for Machine Learning (Large)
Data set
-
-
-
Horse_Racing_Sample.csv
Sample
text/csv
-

Usage information

By subscribing to this product, you agree that your use of this product is subject to the provider's offer terms including pricing information and Data Subscription Agreement . Your use of AWS services remains subject to the AWS Customer Agreement  or other agreement with AWS governing your use of such services.

Support information

Support contact email address
Support contact URL
Refund policy
Refunds are not available for this product
General AWS Data Exchange support