Predictive tracking with reads from timing system
Use reads from your timekeeping system for a smooth real-time visualization of your race.
unique algorithm processes sporadic reads from timekeeping into a smooth live visualization

Predictive tracking with any timing system

The set-up guide checks your settings for predictive tracking. For RACE|RESULT timekeeping system Racemap additionally checks the forwarding of detections with emulated track pings. If the forwarding is configured in RACE|RESULT then the emulated pings are sent back to Racemap.
intuitive setup guide pilots to correct settings for predictive live tracking
We recommend testing to gain experience with the prediction. We support your test events.
Reduce the delay of forwarding detections from your timing system to improve the quality of live prediction.
Strategically place hardware along the race course.

Algorithm for predictive tracking

For predictive tracking our system needs to know:
  • transponder ID of each participant you want to display
  • exact race course as .gpx or .kml ("shadowtrack")
  • locations of the timing hardware
    • readers with a GPS module eg. track boxes send their locations to Racemap
    • readers without own locations: define the location of the reader in Racemap
With AI-based features, you flexibly apply predictive tracking.
  • Auto-Mapping to shadowtrack within 30 m distance:
    • If reader is placed in laps the reader will be mapped on each lap automatically.
    • If reader is located > 30 m from the shadowtrack the prediction ignores its reads.
  • Moving reader: Variable locations of reader during the race, e.g. place track boxes on cars or boats. The prediction considers the current location of every detection for live and replay.
  • Multiple contests detection: One reader can detect several contests (shadowtracks), simultaneously. Racemap assigns reads to the correct shadowtrack, corresponding to transponder ID and contest.
  • High performance: prediction calculates location & speed for > 50,000 participants simultaneously, e.g. München Marathon
predictive live tracking at München Marathon, decoder reads forwarded from RACE|RESULT
Different visualization of live and replay
The replay is calculated with each finish detection for separate participants. The recalculation considers reads sent with a delay or even after the event.
appearance of virtual markers
with 2nd read, eg. prediction receives detection from start without delay and markers will show from 1st reader behind
from start detection
movement of virtual markers
speed extrapolation until detection from next reader location;
speed correction depending on difference between marker in visualization from detection of real participant;
As readers (especially track box) might miss detections, marker moves on over location of following reader.
average speed between detections
Speed filters to check the plausibility of reads: You can set splits with expected speed values eg. swimming, transition, and cycling for triathlon.
  • filter_max: ignore reads with two times faster speed than expected speed
  • filter_min: ignore reads with 0.1 x speed than expected speed