Flag and Remove Reps – App

Protect the Data. Instantly.

A control tool that automatically flags abnormal spikes across all connected data sources and allows staff to remove invalid reps with a single action—without breaking downstream systems.

Performance data is powerful, but it isn’t perfect. Misreads, device errors, bad reps, or mistimed captures can introduce extreme values that skew averages, trends, and decisions. Identifying those outliers manually—and then cleaning them everywhere they live—is slow and error-prone.

The Flag & Remove Reps app eliminates that risk.

This product runs all incoming data through parameters you define to automatically flag suspicious spikes. Each flagged rep is displayed alongside the athlete’s top three all-time maxes, giving immediate context to determine whether the value is legitimate or noise.

If the rep doesn’t belong, you simply press a button—and it’s removed from every connected database.


Features & Advantages

FeatureAdvantages
Multi-source spike detectionIdentify abnormal values across all connected platforms
Custom threshold parametersDefine what qualifies as a spike based on your standards
Contextual max comparisonView flagged reps next to top three all-time maxes
One-click rep removalRemove invalid data instantly without manual cleanup
Database-wide consistencyEnsure bad reps don’t persist in downstream reports
Time-saving workflowEliminate manual auditing and reprocessing
Data integrity protectionKeep longitudinal trends accurate and trustworthy

Why It Matters

Bad data doesn’t just affect one chart—it affects every decision downstream.

By catching spikes early and removing them cleanly, staff protect the integrity of long-term trends, benchmarks, and evaluations. This tool ensures that decisions are based on real performance, not device errors or outliers.

Instead of reacting to questionable numbers, staff can resolve them immediately and move on.


Built for Trustworthy Analytics

The Flag & Remove Reps app puts control back in the hands of the staff. It ensures that your data ecosystem remains clean, consistent, and defensible—without slowing down workflows or requiring technical intervention.

See the spike.
Validate the context.
Remove it everywhere.