Positional maps now available

5 August 2025

Queensland punters will now have access to insights and data analysis on thoroughbred racing than ever. 

Sitting alongside the post-meeting sectional data, Racing Queensland will now publish predictive positional maps on its website the morning of all race meetings across the state. 

The positional maps show the expected position – track distance and distance off rail – of the field after the first 200 metres of the race. 

It uses recency and distance weighted timing system data from tripleSdata’s timing chips along with calculated logic that accounts for barrier. 

The maps also utilise logic that dictates if a horse will prioritise being nearest to the rail, only being pushed out wider if there is no ‘space’ for it to drop into. 

Finally, if a horse does not have any data available to use (first starts/interstate/has only run at tracks that do not have tripleSdata) then it will be expected to perform at the average of the rest of the field. 

These horse names are coloured in red as seen below.

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tripleSdata continues to deliver real-time tracking technology and sectional timings for thoroughbred racing in the Sunshine State.

The service is provided to customers and stakeholders via Sky Racing’s broadcast and digital platforms, through the individual clubs, and on Racing Queensland’s website.

Last month, tripleSdata expanded its partnership with RQ, deploying its technology across four additional thoroughbred racecourses – Dalby, Gatton, Kilcoy and Warwick. 

As a result, more than 90% of TAB meetings in Queensland will have sectional and analytical data available on the RQ website. 

In 2024, RQ unveiled a number of enhancements to its sectional offerings, headlined by a raft of innovative new data points including a horse’s stride frequency and length across each furlong.   

Each report also features individualised breakdowns of average and top speeds, as well as racing position and distance from the rail in run.  

Click here to access RQ’s thoroughbred racing data and analytics.