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Association of Road Racing Statisticians Database Now Online
The Association of Road Racing Statisticians is pleased to announce that the ARRS database is now on-line and may be accessed at http://more.arrs.net. The ARRS database currently has more than one million performances by more than 80,000 runners in more than 200,000 races, from 1897 to date. The focus is on elite runners with half of the runners achieving ARRS time qualifying standards, such as men under 2:20 and women under 2:50 for the marathon. The remainder of the runners is mostly elite veteran runners or marathon winners who have not achieved one or more of the ARRS qualifying standards.
Want to find the top results for a marathon? There are more than 58,000 marathons in the database.
Want to review the career of distance running great Ron Clarke of Australia? There are more than 300 performances by Clarke in the database. Emil Zatopek? There are more than 250 performances for Zatopek in the database. Or, Lynn Jennings? There are more than 250 performances for Jennings. Check out Jennings’ PR progression. How did Jennings do against Joan Benoit-Samuelson over their careers? Score: Jennings eight, Samuelson three.
You can directly access the results for any race in the database as well as ancillary information such as the competitive level for the race, the number of finishers, the race time bias values, the course status, including road course certifications, road course type, record or ranking status, net drop for point-to-point courses, etc.
Get up-to-date rankings at standard distances for any year and for any country. Each ranking entry provides links to that particular runner and that particular race.
And, this is just the beginning. Additional utilities will be added as they are developed. These are intended to present the data in forms that are more useful for the user as well as presenting generalized runner rankings based on head-to-head competition. Imagine being able to predict the finish time for an elite runner in an upcoming major race and handicap the race. This utility will use linear regression analysis of the runner’s past performances to yield a probability distribution of his/her expected time. Look at a runner’s career and follow his/her ups and downs based on how well that runner does against his/her competition. It is one thing to run fast times and another thing to beat one’s opponents.
Rather than enlist paying subscribers to this website, the decision was made to make the information on this website available without charge. Instead, users are encouraged to make donations to help support the website. In addition, the ARRS is looking for a few sponsors who would be willing to help support this website.
Contact: Andy Milroy at AndyMilroy@blueyonder.co.uk or: Ken Young at firstname.lastname@example.org