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About the Coach GPT

The Coach GPT App blends data-driven precision with evidence-based training principles. It integrates objective load metrics (TSS, CTL, ATL, HRV, VO₂max) with subjective markers (RPE, mood, recovery) to generate personalized training analysis.

It uses advanced frameworks like ACWR, Strain, Monotony, Durability Index, and Polarisation Index to deliver clear weekly, seasonal, and wellness reports, ensuring balance between hard and easy days.

Core Features

Coach GPT Avatar

Coach Profile

This coach blends data-driven precision with evidence-based training principles. By combining objective load metrics (TSS, CTL, ATL, HRV, VO₂max) with subjective feedback (RPE, mood, recovery), the coach delivers personalized, phase-based training plans.

Using advanced markers like ACWR, Monotony, Strain, Durability Index, and Polarisation Index, the coach quickly flags risks, tracks readiness, and ensures balance between hard and easy days.

With deep expertise across triathlon, cycling, running, and endurance sports, this coach applies frameworks like Seiler’s 80/20 principle, Banister TRIMP load modeling, Foster’s Monotony/Strain, and tapering protocols. Whether preparing for Ironman, Gran Fondo, or Marathon, the coach ensures athletes peak at the right time while minimizing injury risk.

Intervals.icu Dependency

The Coach GPT App is fully dependent on Intervals.icu for data. Training activities, wellness logs, and advanced load calculations are sourced directly from Intervals.icu.

For the best results, athletes should ensure their wellness markers (HRV, resting HR, sleep, mood, stress, soreness) are synchronized to Intervals.icu. This ensures the app can combine objective training load with subjective recovery data for accurate reporting. Also adding custom fields helps coaching accuracy; Garmin users can expose Vo2maxGarmin and PerformanceIndicators, also IF (Intensity Factor) is a useful metric.

Special thanks to David Tinker, the creator of Intervals.icu, for building and maintaining the platform that makes this integration possible.

Sample Reports (Anonymised)

Below are anonymised examples of reports generated by the Coach GPT App using Intervals.icu data.

📊 Weekly Report (2025-09-24 → 2025-09-30)
### Athlete: [Anon] — 2025-09-24 → 2025-09-30
**Summary:** Light training load with more recovery days. ATL dropped, Form improved.

**Key Stats**
- Volume: 4 sessions, ~6h total
- Load: ~440 TSS, CTL 98→92, ATL 92→70, Form +6→+22
- Recovery: HRV 59→53 ms, Resting HR 41→42 bpm, Sleep avg 7.4h
- Subjective: Limited feel/RPE data logged
- Advanced: ACWR 0.7, Monotony 1.1, Strain 480

**Flags**
- ✅ Form improved steadily through reduced load
- ⚠️ Low volume may limit fitness maintenance
        

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📈 42day Report (2025-08-19 → 2025-09-30)
### Athlete: [Anon] — 2025-08-19 → 2025-09-30
**Summary:** Transitioned from high-load block into gradual reduction. CTL dropped ~18 points across the block.

**Key Stats**
- Load: CTL 110→92, ATL 99→70, Form -11→+22
- Recovery: HRV fluctuated 39–71 ms, Resting HR 38→45 bpm, Sleep avg ~7.7h
- Fitness: VO₂max estimates 62→69 ml/kg/min
- Advanced: ACWR stable 0.8–1.2, Monotony 1.1–1.6, Strain peaks ~950

**Phases**
- Build (late Aug): High training stress, CTL peaked at 110
- Overload (early Sept): ATL >110, HRV suppressed
- Deload (mid Sept): ATL dropped, HRV rebounded
- Consolidation (late Sept): CTL decline, Form rising

**Flags**
- ✅ HRV rebound with deload
- ❌ CTL decline may reduce fitness
- ⚠️ Subjective logging incomplete
        

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📆 Full Season Report (2025-01-01 → 2025-09-30)
### Athlete: [Anon] — 2025-01-01 → 2025-09-30 (phase-based)
**Summary:** Nine months of structured training with distinct build, overload, deload, and consolidation phases. CTL peaked above 110 mid-season, but has since declined. Recovery markers show resilience, though HRV dips occurred during overload blocks.

**Key Stats**
- Volume: ~600h total (cycling dominant, ~75%)
- Load: CTL 85→92, ATL 80→70, Form +5→+22
- Recovery: HRV 39→71 ms, Resting HR 38→45 bpm, Sleep avg 7.6h
- Fitness: VO₂max 60→69 ml/kg/min, Decoupling avg ~4%, Polarisation index ~0.72
- Advanced: ACWR 0.8–1.3, Monotony 1.1–1.7, Strain peaks ~1000

**Phases**
- Build (Jan–Mar): CTL 85→100, HRV steady, sleep 7.5h
- Overload (Apr–Jun): ATL >120, HRV 40–47 ms, RestHR up, stress elevated
- Deload (Jul): ATL dropped 30, HRV rebounded, sleep 7.8h
- Consolidation (Aug–Sep): CTL decline, Form +22, VO₂max peak

**Load vs Recovery**
High stress early, recovery in Jul, late-season detraining risk.

**Flags**
- ✅ VO₂max peak at 69
- ❌ CTL decline since Aug
- ⚠️ Under-reporting of RPE/feel

**Actions**
1. Restart controlled build to raise CTL
2. Maintain positive Form for late-season events
3. Improve subjective logs for load balance
        

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💤 Wellness Trend (2025-09-01 → 2025-09-30)
### Athlete: [Anon] — Wellness 2025-09-01 → 2025-09-30
**Summary:** Recovery metrics improved in mid-September after heavy early load. End of month shows stable trends.

**Recovery Metrics**
- HRV 39→71→53 ms
- Resting HR 38→45 bpm (normalized late)
- Sleep avg 7.3→7.8h
- Weight stable ±1 kg

**Subjective**
- Mood steady, dips during overload
- Stress elevated early Sept
- Soreness eased with deload

**Flags**
- ✅ HRV rebound shows adaptation
- ❌ None detected
- ⚠️ Stress elevated outside training early Sept
        

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🚀 Next Steps (Sample Actions for Upcoming Block)
### Athlete: [Anon] — Planning Phase (Oct 2025)
**Summary:** Following the deload and consolidation, the next block should reintroduce progressive overload while maintaining recovery balance.

**Next Steps (Phased Approach)**
1. **Build Phase (2 weeks)** — Increase volume by ~10%, target CTL +5. Maintain 80/20 intensity balance.
2. **Overload Phase (2 weeks)** — Include 2–3 key sessions per discipline (long ride, threshold run, swim intervals). Monitor ATL to avoid >120 spikes.
3. **Deload (1 week)** — Reduce load by 40%. Focus on sleep, HRV tracking, and form recovery (+15 or higher).
4. **Consolidation (race prep)** — Sharpen key intensities, maintain volume, taper in final week.

**Actions**
- Track HRV daily to confirm adaptation.
- Log subjective RPE/Feel consistently.
- Schedule event-specific sessions (brick workouts if triathlon, long tempo if marathon).
        

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🏋️ Suggested Training Sessions (Next 4 Weeks)
### Athlete: [Anon] — Oct 2025 Macrocycle (Examples for Different Athlete Types)

**Cyclist Example**
Week 1–2 (Build):
- Endurance: 3h Z2 ride, 2h steady ride
- Intervals: 4x10min @ 90% FTP, 8x3min @ VO₂max
- Skills: 90min group ride
- Strength: 2x core + leg stability
Week 3 (Overload):
- 4.5h long Z2 ride (last 45min tempo)
- 6x5min @ 110% FTP, 12x30s sprints
- Back-to-back weekend: 4h + 2h tempo
Week 4 (Deload):
- 2h Z2, 90min recovery
- 3x6min sweet spot
- Skills drills + mobility

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**Triathlete Example**
Week 1–2 (Build):
- Swim: 8x200m aerobic, 12x100m threshold
- Bike: 2h Z2, 3x12min @ FTP
- Run: 12km long run, 8x400m intervals
Week 3 (Overload):
- Swim: 20x100m aerobic, 6x50m sprints
- Bike: 4h Z2 ride, 5x5min VO₂max
- Run: 16km long run, 5x1km @ 10k pace
Week 4 (Deload):
- Swim: drills + 1.5km aerobic
- Bike: 2h Z2 + light tempo
- Run: 8km easy, 6x200m strides

---

**Runner Example**
Week 1–2 (Build):
- Long Run: 14–16km Z2
- Intervals: 6x800m @ 10k pace, 10x200m strides
- Easy Runs: 2–3x 45min Z1
- Strength: 2x functional
Week 3 (Overload):
- Long Run: 18km with final 4km tempo
- Intervals: 8x1km @ threshold
- Back-to-back: Sat long run, Sun 12km steady
Week 4 (Deload):
- Long Run: 10km Z2
- 5x200m strides
- Mobility + recovery focus

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**Note:** The Coach GPT adapts plans automatically to athlete type (Cyclist, Triathlete, Runner) using the same phased approach: Build → Overload → Deload → Consolidation.
        

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Get the App

In the GPT Store, search for: "Intervals icu training coach"

Contact

For integration, customization, or coaching inquiries, connect via GitHub or Intervals.icu

github.com/revo2wheels