Evidence-based training

The Science Behind
Eventyr Performance

Every metric in Eventyr's training load model is grounded in peer-reviewed sports science. This article explains the research, the formulas, and the reasoning - so coaches and athletes understand exactly what they are looking at.

Banister TRIMPCTL / ATL / TSBACWRSupercompensationOvertraining prevention

Section 1

Supercompensation - the foundation of all training

Every training adaptation begins with the same biological principle: apply a stimulus, recover, and emerge stronger. This cycle - called supercompensation - was formally described by Yakovlev (1977) and remains the cornerstone of modern periodization theory.

The four phases are:

  1. Training stress: A session disrupts homeostasis - muscles fatigue, glycogen depletes, microtrauma accumulates.
  2. Recovery: The body repairs and rebuilds, targeting the specific systems stressed.
  3. Supercompensation: Fitness rises above the pre-training baseline - this is the adaptation window.
  4. Detraining: If no new stimulus arrives, fitness returns to baseline within 10–14 days.

Key insight for coaches

The productive zone (moderate negative TSB) represents repeated training stress without full recovery between sessions. This is intentional - sustained supercompensation accumulates over weeks into genuine long-term fitness gains, especially when followed by a recovery or taper block.

Critically, adaptation only occurs during recovery - not during the session itself. An athlete who never recovers does not improve; they degrade. The art of coaching is managing the stress-recovery balance across days, weeks, and seasons.

Section 2

Training load - why we need a number

Two sessions of equal duration can have vastly different physiological impacts. A 60-minute low-intensity paddle and a 60-minute race-intensity interval session are not the same stress on the body. Any useful training model must account for both duration andintensity.

Heart rate is the most practical and validated proxy for internal training intensity. It responds to exercise intensity, environmental conditions, and fatigue - capturing factors that external load metrics (speed, watts) cannot. For sports like windsurfing where power meters are impractical, heart rate is the gold standard.

The challenge is combining duration and heart rate into a single, meaningful number. That is precisely what Eric Banister solved in 1975.

Section 3

Banister TRIMP - quantifying each session

TRIMP (Training Impulse) was introduced by Banister et al. (1975) and refined by Morton et al. (1990). It weights each minute of exercise by the relative heart rate intensity - giving high-intensity minutes far more load value than easy ones, which reflects the non-linear physiological cost of hard effort.

Banister TRIMP formula (Morton 1990)

TRIMP = duration(min) × ΔHR × 0.64 × e^(1.92 × ΔHR) where ΔHR = (HRavg − HRrest) / (HRmax − HRrest) ΔHR is clamped to [0, 1]

The exponential term e^(1.92 × ΔHR) is the key innovation. It captures the well-established physiological fact that blood lactate - and therefore metabolic stress - rises exponentially above the lactate threshold. A session at 90% of max HR is not three times harder than one at 30% - it is far more than that.

Normalisation to 0–100 scale

Because raw TRIMP values vary between athletes (a fitter athlete with a lower resting heart rate produces different raw numbers than a deconditioned one), Eventyr normalises daily TRIMP values against the athlete's own 95th-percentile session - making the scale personal and comparable across time.

When heart rate data is unavailable (GPS-only sessions), Eventyr falls back to a conservative estimate of 50 TRIMP per hour, equivalent to moderate aerobic effort. This keeps the model populated even for incomplete data sessions.

Section 4

CTL, ATL, and TSB - the Performance Management Model

The Performance Management Chart (PMC) was formalised by Banister (1991) and popularised for endurance sport by Dr Andrew Coggan in the early 2000s. It models fitness and fatigue as two competing exponential moving averages of daily training load, and derives form as the difference between them.

CTL - Chronic Training Load (fitness)

CTL(today) = CTL(yesterday) + [Load(today) − CTL(yesterday)] × (1 − e^(−1/42)) 42-day exponential moving average of daily TRIMPRepresents the athlete's aerobic base built over months

ATL - Acute Training Load (fatigue)

ATL(today) = ATL(yesterday) + [Load(today) − ATL(yesterday)] × (1 − e^(−1/7)) 7-day exponential moving average of daily TRIMPRepresents recent training stress - recovers in days

TSB - Training Stress Balance (form)

TSB = CTL − ATL Positive TSB → more recovered than fatiguedNegative TSB → more fatigued than recovered

The 42-day and 7-day time constants are not arbitrary. They approximate the biological half-lives of fitness gains and fatigue dissipation, validated across endurance sports in research by Banister, Coggan, and others. A longer window (42 days) captures the slow accumulation of aerobic adaptations; a shorter window (7 days) captures how quickly fatigue accumulates and resolves.

Why CTL goes up slowly but ATL spikes fast

Adding a single hard training block raises ATL rapidly but barely moves CTL. This is physiologically accurate - true aerobic fitness (mitochondrial density, cardiac output, capillarisation) takes months to build but acute fatigue resolves in 48–72 hours. TSB will temporarily drop sharply, then rebound as ATL falls faster than CTL.

Section 5

TSB zones - what each state means for the athlete

TSB is not simply a measure of how tired the athlete is. It describes the balance between fitness and fatigue - and crucially, the ideal TSB for training is different from the ideal TSB for competition (Bosquet et al., 2007; Mujika & Padilla, 2003).

Eventyr uses a six-zone model that reflects this nuance:

ZoneTSB rangeMeaning
Detraining
Insufficient load
> +15
Aerobic fitness is regressing. Without adequate training stimulus, mitochondrial density, cardiac output, and capillarisation all decline. Sustained beyond 10–14 days, measurable fitness loss occurs (Mujika & Padilla, 2000).
Race Ready
Post-taper
+5–+15
Optimal state for competition or key performance tests. Fatigue is fully dissipated; fitness is preserved from recent training. Not suitable for long-term training - adaptation slows significantly in this zone.
Balanced
Maintenance
−5–+5
Maintaining current aerobic base. Recovery weeks and transition periods typically sit here. Not enough overload for meaningful supercompensation, but sustainable indefinitely without breakdown.
Productive
Adaptation zone
−5–−20
The training sweet spot. CTL is accumulating faster than ATL is dissipating, meaning genuine fitness is being built. Athletes at the elite level spend the majority of their training blocks in this zone. The green colour reflects that this is a desirable, intentional state.
Heavy Load
Monitor recovery
−20–−30
Fatigue is outpacing recovery capacity. Short exposures here are tolerable and can produce training peaks when followed by a recovery block (Meeusen et al., 2013). Prolonged stays increase overtraining and illness risk significantly.
Overreaching
Reduce load now
< −30
Chronic overload state. Performance will decline despite continued training. Immune function is markedly suppressed (Gleeson, 2006). Risk of illness, injury, and non-functional overreaching (NFO) is high. Immediate volume reduction is required.

Productive (negative TSB) is intentionally green

It is a common misconception that a negative TSB means the athlete is in a bad state. For competitive athletes, mild to moderate negative TSB is the normal and desirable consequence of progressive overload. The supercompensation model predicts that fitness peaks precisely because of the controlled fatigue that accumulated during productive training - released through a taper.

Section 6

ACWR - predicting overtraining and illness risk

The Acute:Chronic Workload Ratio (ACWR) was described by Gabbett (2016) in The British Journal of Sports Medicine and has since become one of the most widely adopted injury and illness prediction metrics in professional sport.

ACWR formula

ACWR = ATL ÷ CTL In Eventyr terms: ACWR = 7-day EMA load ÷ 42-day EMA load

The ratio compares how hard the athlete is currently working (ATL) relative to what their body is conditioned for (CTL). A ratio close to 1.0 means the current load matches fitness - sustainable and productive. A ratio significantly above 1.0 means the athlete is working well beyond their conditioned capacity - a physiological red flag.

ACWR rangeRisk levelInterpretation
< 0.8UndertrainingLoad is below conditioning level. Fitness will regress without intervention.
0.8–1.1OptimalLoad and fitness are well matched. Sustainable progressive overload.
1.1–1.3CautionLoad rising faster than conditioning. Monitor recovery indicators closely.
1.3–1.5High riskSignificantly elevated injury and illness risk (Gabbett, 2016). Reduce volume.
> 1.5CriticalVery high overtraining risk. Likelihood of illness or injury within days if load continues.

The 'sweet spot' concept (Gabbett, 2016)

Gabbett's landmark paper demonstrated that athletes with higher chronic loads (higher CTL) are more protected against injury - even when exposed to high acute loads - because their bodies are better conditioned. Building a large aerobic base (CTL) over time is itself a protective strategy, not just a performance one.

Eventyr displays ACWR as a live metric and applies colour coding that matches the risk zones above. When ACWR exceeds 1.3, the platform generates a coach warning with specific recommended actions.

Section 7

Overtraining Syndrome - when too much becomes harmful

The European College of Sport Science and American College of Sports Medicine published a joint consensus statement (Meeusen et al., 2013) defining the progression from productive overreaching to pathological overtraining:

  1. Functional overreaching (FOR)
    Short-term performance decrement with full recovery in days to weeks. This is normal, intentional, and the mechanism behind training camp and loading blocks.
  2. Non-functional overreaching (NFOR)
    Sustained performance decline despite rest. Recovery takes weeks to months. Often associated with mood disturbance, elevated resting HR, and frequent illness.
  3. Overtraining Syndrome (OTS)
    Chronic, severe performance decline with systemic hormonal disruption (elevated cortisol, suppressed testosterone). Recovery takes months to years. OTS is a medical diagnosis requiring physician involvement.

Immune suppression and illness risk

Exercise immunology research (Gleeson, 2006; Mackinnon, 2000) has established the "open window" hypothesis: in the hours immediately following a hard training session, immune function is transiently suppressed. White blood cell activity decreases, salivary IgA (the first line of defence against respiratory infections) drops, and susceptibility to upper respiratory tract infections rises sharply.

When this window occurs repeatedly without adequate recovery - as happens when ACWR exceeds 1.5 or TSB stays below −30 - the immune system remains chronically suppressed. Athletes in this state are significantly more likely to fall ill, which itself forces training interruption and compounds fitness loss.

Biological markers of overtraining

Coaches and athletes should watch for:
  • Elevated resting heart rate (> 5–7 bpm above baseline)
  • Suppressed HRV (Heart Rate Variability)
  • Elevated cortisol / decreased testosterone:cortisol ratio
  • Low ferritin (< 30 μg/L) - impairs oxygen transport
  • Vitamin D deficiency - linked to immune suppression and fatigue
  • Persistent mood disturbance, motivation loss, sleep disruption

Section 8

Practical guidance for coaches

The following principles distil the research above into actionable coaching practice:

01
Build CTL gradually
Research consistently supports an increase in chronic load of no more than 5–10% per week (the progressive overload principle). Rapid CTL spikes drive ACWR above safe limits.
02
Spend most of the block in the Productive zone
For competitive athletes, a TSB of −5 to −20 across the majority of a training block is not only acceptable - it is the mechanism of improvement. Avoid the temptation to keep athletes 'fresh' during training periods.
03
Schedule recovery before competition
A 7–14 day taper bringing TSB from the productive zone back toward +5 to +15 will maximise competition readiness. During a taper, CTL falls slowly while ATL falls quickly - TSB rises rapidly.
04
Monitor ACWR as a daily early warning
If ACWR exceeds 1.3, reduce volume before performance suffers. Most athletes do not feel overreached until 3–5 days after the threshold is crossed - meaning subjective reports lag the data.
05
Detraining is real and fast
More than 10–14 days of very low load causes measurable fitness decline. During competition travel, off-season, or injury periods, use cross-training or easy sessions to keep CTL stable.
06
Consistency beats heroic sessions
A high 14-day consistency score indicates the athlete is training regularly - which accumulates CTL faster and more safely than sporadic high-load sessions separated by long rest periods.

Section 9

References

  • 01.Banister, E.W., Calvert, T.W., Savage, M.V., & Bach, T. (1975). A systems model of training for athletic performance. Australian Journal of Sports Medicine, 7(3), 57–61.
  • 02.Banister, E.W. (1991). Modeling elite athletic performance. In H.J. Green, J.D. McDougal & H.A. Wenger (Eds.), Physiological Testing of the High-Performance Athlete (pp. 403–424). Human Kinetics.
  • 03.Morton, R.H., Fitz-Clarke, J.R., & Banister, E.W. (1990). Modeling human performance in running. Journal of Applied Physiology, 69(3), 1171–1177.
  • 04.Coggan, A.R. (2003). Training and racing using a power meter: an introduction. TrainingPeaks Technical Paper.
  • 05.Gabbett, T.J. (2016). The training-injury prevention paradox: should athletes be training smarter and harder? British Journal of Sports Medicine, 50(5), 273–280.
  • 06.Bosquet, L., Montpetit, J., Arvisais, D., & Mujika, I. (2007). Effects of tapering on performance: a meta-analysis. Medicine & Science in Sports & Exercise, 39(8), 1358–1365.
  • 07.Mujika, I., & Padilla, S. (2003). Scientific bases for precompetition tapering strategies. Medicine & Science in Sports & Exercise, 35(7), 1182–1187.
  • 08.Mujika, I., & Padilla, S. (2000). Detraining: loss of training-induced physiological and performance adaptations. Sports Medicine, 30(2), 79–87.
  • 09.Meeusen, R., Duclos, M., Foster, C., et al. (2013). Prevention, diagnosis and treatment of the overtraining syndrome: joint consensus statement of the European College of Sport Science and the American College of Sports Medicine. European Journal of Sport Science, 13(1), 1–24.
  • 10.Foster, C. (1998). Monitoring training in athletes with reference to overtraining syndrome. Medicine & Science in Sports & Exercise, 30(7), 1164–1168.
  • 11.Gleeson, M. (2006). Can nutrition limit exercise-induced immunodepression? Nutrition Reviews, 64(3), 119–131.
  • 12.Mackinnon, L.T. (2000). Overtraining effects on immunity and performance in athletes. Immunology and Cell Biology, 78(5), 502–509.
  • 13.Yakovlev, N.N. (1977). Sports Biochemistry. Leipzig: Deutsche Hochschule für Körperkultur.

Built on the evidence

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