Guide

Plan and log workouts

Use Copy week beside a populated calendar week, choose the destination week, and confirm. Keep existing sessions, edit individual prescriptions, then review the completed workouts against the plan.

Manual planning stays available during the pilot.

Daily check-ins and messages

Record legs feel, energy and RPE after training. Use Messages or a session discussion to share feedback with your coach.

Mark session feedback as needing a response. Your coach can reply, acknowledge review or adjust upcoming training.

Intervention Log

Use the intervention log to record the protocol you chose, the session or race it was tied to, and any notes that matter later. The goal is simple: capture what you tried so Threshold can compare it against how you responded.

This is the core dataset behind intervention insights. The more consistently you log protocols, the faster the platform can separate useful patterns from one-off experiments.

Baseline Tracker

Your baseline settings hold the stable information that makes later comparisons more meaningful: altitude, heart-rate zones, fueling anchors, hydration targets, and supplements you use regularly.

These inputs help Threshold interpret logs in context instead of treating every intervention as if it happened in a vacuum.

Race Profile

Save the race you are training for once, then link interventions to that event as you log them. Keep the race date and course basics current so your history stays tied to the right build.

Race context makes it easier to review a full preparation cycle rather than isolated sessions.

Calculated training comparisons

Training-load estimates and check-in comparisons use rules and formulas applied to your records. Review the sample size, time window and missing inputs before interpreting a result.

These are observations for you and your coach to review. A correlation does not establish cause and effect. Automatic reviews and generated plans are deferred.

Self-Selection Explorer

The explorer lets you choose one input variable and one outcome variable, then see the relationship in a simple chart with a plain-English interpretation. It works best when you already have a decent amount of history for the variables you pick.

This is useful when you want to test your own theory against your own data instead of waiting for the platform to surface a pattern automatically.

Research Library

The research library is where you can browse studies relevant to running from the mile through marathon+, plus gravel and triathlon training, without digging through academic formatting. Use search and filters to narrow the library to the topics you actually care about.

It gives context for why a protocol is worth testing, while your own logs show whether it worked for you.