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A Quantitative Guide to Running Training: The Scientific Application of TRIMP, rTSS, and GAP Pace

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Quantifying Running Training: The Scientific Application of TRIMP, rTSS, and GAP Pace

Running Training Needs Quantification

For a long time, running training has relied on only two metrics for “measurement”: kilometers and pace. But this ignores the vast differences in terrain, temperature, and individual fitness levels—running the same 10 km with 400 meters of climbing on Qixing Mountain versus a flat riverside park path places vastly different stress on the body. TRIMP, rTSS, and GAP are three tools designed precisely to solve this problem.

TRIMP (Training Impulse)

TRIMP is the earliest training load quantification metric adopted by sports science, proposed by Banister et al. in the 1970s. The core concept is: the higher the heart rate and the longer the duration, the greater the training impulse.

Basic calculation logic:
TRIMP = Training duration (minutes) × Average heart rate intensity coefficient

Banister formula (version accounting for sex differences):

Intensity coefficient (male) = 0.64 × e^(1.92 × heart rate ratio)
Intensity coefficient (female) = 0.86 × e^(1.67 × heart rate ratio)

Heart rate ratio = (Average heart rate − Resting heart rate) ÷ (Maximum heart rate − Resting heart rate)

Practical notes: Watches such as Garmin and Polar automatically calculate TRIMP (in training effect or load analysis), so manual calculation is usually unnecessary. TRIMP allows you to compare the physiological and psychological load of different intensity sessions—a 60-minute easy run versus a 45-minute interval session; the latter often yields a higher TRIMP.

rTSS (Running Training Stress Score)

rTSS is TrainingPeaks’ running-specific variant of TSS, based on pace rather than power. Its calculation baseline is your lactate threshold pace (typically close to 10K race pace or half-marathon pace).

Calculation formula:
rTSS = (Running seconds × NGP × rIF) ÷ (FTPa × 3600) × 100

Where:

  • NGP (Normalized Graded Pace) = pace normalized for grade
  • rIF = NGP ÷ FTPa (threshold pace)
  • FTPa = your lactate threshold pace

Reference rTSS values for common workouts:

Workout Type Distance/Duration Reference rTSS
Easy recovery run 40 minutes 35–45
Aerobic base long run 90 minutes 90–110
Tempo run 60 minutes 100–120
Marathon race 3.5–4 hours 250–350

GAP (Grade Adjusted Pace)

GAP is an algorithm developed by Strava that converts actual running pace into an “equivalent flat-ground pace,” so hill runners are no longer disadvantaged by terrain.

Core GAP formula (Strava version):
Uphill: GAP ≈ Actual pace / (1 + Grade × Adjustment coefficient)

Practical application example:

  • Running uphill at an 8% grade, actual pace 6:30/km
  • GAP converts to an intensity roughly equivalent to 4:50/km on flat ground
  • If your aerobic base pace is 5:00/km, this hill segment indeed reaches above-threshold intensity

GAP allows runners to compare the “true intensity” of hill training versus flat training, enabling more reasonable hill training goals.

Combining the Three Tools

  • TRIMP: Best suited for tracking daily training load; works best when combined with HRV
  • rTSS: Best suited for use in the PMC (Performance Management Chart) to track long-term fitness (CTL) and fatigue (ATL)
  • GAP: Best suited for analyzing the actual intensity of hill training and setting pace targets for hill workouts

Practical Recommendations

  • Establish your personal lactate threshold pace baseline: use your half-marathon race pace from the last 90 days, or 10K pace × 1.05
  • Keep weekly rTSS increases within 10%
  • After long sessions (over 90 minutes), allow ATL to spike temporarily, then proactively reduce volume the following week to recover
  • Using Strava’s Relative Effort feature provides a simplified approximation of TRIMP

Conclusion

Taiwan’s road running culture has long measured success by kilometers, but simply chasing mileage overlooks the importance of intensity distribution. The combination of TRIMP, rTSS, and GAP helps you convert every run into comparable training units, giving your training plan adjustments a clear data foundation rather than relying on guesswork.

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