Training guide
Overtraining: what the research says
Overtraining syndrome is a long lasting drop in performance, with fatigue and mood changes, after a mismatch between training and recovery. It is different from a hard week that leaves you tired. Most athletes who feel flat are not overtrained.
A joint consensus statement from the European College of Sport Science and the American College of Sports Medicine describes a range: functional overreaching, nonfunctional overreaching and overtraining syndrome. No single test settles which one an athlete is in.
Overreaching and overtraining syndrome
The consensus statement says successful training needs overload but must avoid excess overload combined with too little recovery. A short drop in performance after a hard block, called functional overreaching, is followed by better performance after recovery. When training and recovery are out of balance, nonfunctional overreaching can occur. Telling it apart from overtraining syndrome is very difficult and depends on the clinical picture and on excluding other causes.
A key idea in the statement is prolonged maladaptation: performance, mood and several body systems fail to recover as expected. The statement lists other causes to rule out first, such as illness, infection, too little energy or carbohydrate intake, and iron deficiency. A doctor makes that diagnosis, not an app.
Why there is no single marker
The consensus statement reviews hormones, performance tests, psychological tests and biochemical and immune markers. It says none of them meets all the criteria for general use. A review of training load monitoring reaches a similar conclusion: few markers have strong scientific support and there is no single definitive one. It stresses individualization.
In practice, researchers look at several things together: the training load, performance, sleep, heart rate measures and how the athlete feels. HRV and resting heart rate are one input, and they depend on method and context.
What your AI can read in Memory.fit
Memory.fit puts those inputs in one place: training load as fitness, fatigue and form with weekly bars, HRV and resting heart rate against your usual range, sleep, skipped sessions, and planned versus done hours. Your AI reads them with get_training_load, get_recovery, get_daily_metrics and get_workouts.
Memory.fit reports numbers and gives no verdict such as tired or overtrained. If you feel unwell or your performance keeps falling, talk to a doctor or coach.
In your AI
The AI you already use, with your data in Memory.fit.
- ChatGPTChatGPT can schedule tasks, but OpenAI does not say a scheduled task can use a custom connector like Memory.fit. Try it once.Set up ChatGPT
- ClaudeClaude runs scheduled tasks in the cloud, and they use your connectors.Set up Claude
Grok BotGrok Bot keeps working after you close the app, so it can write your weekly review while you train.Set up Grok Bot
MuseMuse checks in when you open a chat. Whether it runs on a schedule with Memory.fit isn't checked yet.Set up Muse
DotsDots are always on, each with its own cloud computer, so your dot can check in on its own.Set up Dots- GeminiGemini checks in when you open a chat. Whether it runs on a schedule with Memory.fit isn't checked yet.Set up Gemini
- GrokGrok checks in when you open a chat. Whether it runs on a schedule with Memory.fit isn't checked yet.Set up Grok
- Perplexity ComputerPerplexity Computer checks in when you open a chat. Whether it runs on a schedule with Memory.fit isn't checked yet.Set up Perplexity Computer
- Claude CodeClaude Code checks in when you open a chat. Whether it runs on a schedule with Memory.fit isn't checked yet.Set up Claude Code
CueYour Cue agents check in from your real training, sleep and recovery.Set up Cue
What to send
Copy one, send it to your AI.
“Show my training load, HRV, resting heart rate and sleep from Memory.fit for the last 6 weeks on one timeline and describe what changed.”
Tools:
get_training_loadget_recoveryget_sleep“Every Sunday, review my week in Memory.fit: hours planned versus done, skipped sessions and my recovery numbers against my usual range. Tell me what you see.”
Tools:
get_workoutsget_recoveryget_updates“Compare the last 4 weeks of my training load in Memory.fit with the 4 weeks before, and list the biggest weeks.”
Tools:
get_training_load“Have I skipped sessions or had low sleep in the last 3 weeks in Memory.fit? Summarize with dates.”
Tools:
get_workoutsget_sleep
Questions
In short.
Functional overreaching is a short drop in performance that improves after recovery. Nonfunctional overreaching and overtraining syndrome are longer, and the consensus statement says telling them apart is very difficult.
No. The consensus statement found that no marker meets the criteria for general use. HRV is one input among several.
The statement lists illness, infection, too little energy or carbohydrate or protein intake, iron or magnesium deficiency and allergies, among others.
No. Memory.fit shows load, recovery and sleep numbers with no verdict. Your AI can describe the changes.
A doctor or sports medicine professional, since diagnosis requires ruling out other causes.
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