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    Science & AI methodology

    Published science, applied every day.

    AthleteSpace combines proven endurance science with modern AI to deliver personalized, responsible, and explainable training intelligence.

    Start with my coachReferences

    The fitness-fatigue model

    • Fitness
    • Fatigue
    • Form

    An illustration of the model, not an athlete's data.

    Science first, always

    AthleteSpace does not invent new physiology. We implement well-established, peer-reviewed endurance training models that have been used for decades by Olympic programs, professional teams, and elite coaches.

    Our core framework is the fitness-fatigue model: a long-term Fitness line, a short-term Fatigue line, and Form, the gap between them, all computed from a Training Load for every session, alongside validated heart-rate and perceived-exertion models.

    What the AI actually does

    AI in AthleteSpace is used to apply science correctly and consistently, not to replace it.

    • Select the most appropriate stress model based on available data
    • Personalize training load calculations to each athlete
    • Adapt thresholds as fitness changes
    • Detect mismatches between external load and physiological strain
    • Translate complex metrics into clear, actionable guidance

    Research-led and responsible

    AthleteSpace is built by one athlete-engineer, Bruno Artacho, who holds a PhD in AI. It applies the published models listed below rather than inventing new physiology, and every plan passes fixed safety rules (ramp limits, recovery weeks, session caps) before you see it.

    We prioritize explainability, athlete safety, and scientific validity. AthleteSpace does not provide medical diagnosis or treatment and does not replace professional coaching or medical advice.

    Before you see it

    Every plan passes fixed safety rules.

    • Ramp limits
    • Recovery weeks
    • Session caps

    References

    The published work the plans and metrics are built on.

    1. The fitness-fatigue model behind Fitness, Fatigue and Form. Banister EW, Calvert TW, Savage MV, Bach T. A systems model of training for athletic performance. Australian Journal of Sports Medicine. 1975;7:57-61.
    2. Training load from power relative to threshold. Allen H, Coggan A. Training and Racing with a Power Meter. 2nd ed. Boulder, CO: VeloPress; 2010.
    3. Session RPE, the load estimate when there is no power, pace or heart rate. Foster C, Florhaug JA, Franklin J, et al. A new approach to monitoring exercise training. Journal of Strength and Conditioning Research. 2001;15(1):109-115.
    4. HRV trends as a guide to readiness and adaptation. Plews DJ, Laursen PB, Stanley J, Kilding AE, Buchheit M. Training adaptation and heart rate variability in elite endurance athletes: opening the door to effective monitoring. Sports Medicine. 2013;43(9):773-781.
    5. Heart-rate measures for monitoring training status. Buchheit M. Monitoring training status with HR measures: do all roads lead to Rome? Frontiers in Physiology. 2014;5:73.
    6. VDOT and the running pace zones. Daniels J. Daniels' Running Formula. 3rd ed. Champaign, IL: Human Kinetics; 2014.

    Bottom line

    AthleteSpace applies published endurance science, personalized to you and updated every day. AI can make mistakes. Always verify important information and consult a professional for medical decisions.