Running Glossary

Predictive Modeling

Running Glossary

Predictive Modeling

Running Glossary

Predictive Modeling

Predictive Modeling

[pri-dik-tiv mod-uh-ling]

Phonetic (Standard)

/prɪˈdɪktɪv ˈmɒdəlɪŋ/

IPA

Noun

The process of using statistical techniques and algorithms to create models that can predict future outcomes based on historical data.

Predictive modeling uses statistical techniques to forecast future outcomes based on historical data. It involves algorithms like regression, decision trees, or machine learning to identify patterns. In running, predictive models can estimate race times, injury risks, or training outcomes. For example, apps use past performance data to predict marathon finish times. This matters to runners as it helps tailor training plans, optimize performance, and prevent injuries by anticipating potential issues. Accurate predictions enable runners to set realistic goals and make informed decisions about their training and recovery strategies.

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Predictive Modeling

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Weekly Distance Target

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Cross-Training

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Lactate Threshold

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Strava Integration

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Dynamic Pacing

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Goal Pace

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Personal Best (PB)

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Mile Better Podcast

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Fastest Marathons List

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Training Stress Score (TSS)

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TRIMP (Training Impulse)

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Running Economy

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Critical Speed

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Functional Threshold Pace (FTP)

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Fitness Fatigue Model

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Load Management

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Performance Decay

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Predictive Analytics

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Personalized Coaching

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Periodic Fitness Testing

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