Understanding Classifications
In RUFUS Race Manager (RRM), race classifications are generated dynamically each time they are requested. Unlike systems that “lock” results after initial processing, RRM continuously adapts to changes, ensuring results are always accurate, up to date, and consistent with the raw timing data.
Dynamic Recalculation
Every time classifications are viewed or exported, RRM recalculates them in real time. This provides key benefits:
Modifications without reprocessing → Edits to participants, passings, or race start times are immediately reflected in the results. No batch reprocessing is required.
Error correction → Mistakes (like missing or duplicated passings) can be fixed on the fly, with classifications updating instantly.
Raw data preserved → All passings are stored with their original timestamps. Adjustments never overwrite the source data.
Role of Segments and Checkpoints
Classifications in RRM are built on the structure of checkpoints and segments:
Checkpoints mark specific locations on the course (Start, intermediates, Finish). As participants cross checkpoints, passings are recorded.
Segments are the timing intervals between checkpoints. At least one segment (Start → Finish or Gunshot → Finish) is required for ranking. Additional segments (like Start → 10k or Swim → Bike) allow for splits and transition analysis.
By combining checkpoints and segments, RRM generates meaningful classifications that reflect both total race times and detailed performance insights.
The diagram shows how raw Passings flow into Checkpoints, combine into Segments, and ultimately generate Classifications.
Why This Matters
This approach ensures that:
Last-minute changes don’t break results.
Manual passings or floating passings can be added confidently.
Rankings are always based on the most accurate, current data.
Timers can adapt to real-world conditions (mass starts, late edits, hardware hiccups) without sacrificing the reliability of official results.
Summary
Classifications in RRM are live, dynamic, and resilient. By recalculating on demand and preserving original data, the system guarantees that every result reflects the true state of the race—no matter when or how it’s reviewed.
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