Science — Training Load

The question this layer answers

How much training stress was applied, and what pattern did that stress create?

Training Load is the first layer of the Montis Intelligence Stack. It establishes the objective training stimulus before Montis tries to interpret recovery, adaptation or readiness.

Montis uses validated activity and calendar data to resolve training volume and load context. Depending on report type, this can include:

• training duration;
• distance;
• Intervals.icu training load / TSS;
• CTL;
• ATL;
• TSB;
• intensity distribution;
• ACWR;
• monotony;
• strain;
• Load Variability Index;
• daily load;
• completed versus planned training;
• future planned load.

The important distinction is that load describes stress, not adaptation.

A high training load can be productive when the athlete is absorbing it. The same load can become problematic when physiology, durability or forecast signals show that recovery capacity is being exceeded.

CTL, ATL and TSB

Montis uses the fitness-fatigue relationship as part of its load context:

• CTL represents longer-term accumulated training load.
• ATL represents more acute training load.
• TSB is derived from the relationship between CTL and ATL and represents current or projected form/freshness context.

These values are not used as standalone coaching answers.

For example:

• negative TSB can be compatible with productive training;
• positive TSB can reflect useful freshness;
• excessive freshness can also occur after too much unloading;
• the meaning changes when an athlete is building, recovering or tapering for an event.

Load Trend

Montis also evaluates whether future planned load is:

• increasing;
• stable;
• declining.

An increasing load trend is not automatically a negative signal.

If the athlete is load_accepting, risk is normal and forecast fatigue remains controlled, increasing load can be treated as aligned with productive progression.

If increasing load occurs while recovery is already constrained, forecast fatigue is elevated, or the athlete is inside a taper conflict, the same trend can contribute to a more cautious ADE decision.

This is why Forecast Trend: Increasing must always be read together with operational state, forecast fatigue and event context.

Report horizon versus evidence window

The visible dashboard horizon and the evidence window used by a metric are not necessarily the same.

A Micro report can focus on the current short-term training period while using longer baselines to decide whether current load is unusual.

Likewise, a Meso report can use weekly aggregation and longer-term CTL/ATL behaviour to detect the structure of a training block.

The report horizon answers:

"What period am I reviewing?"

The evidence window answers:

"How much historical context does this metric need to be meaningful?"