Predictive Modeling
[pri-dik-tiv mod-uh-ling]
/prɪˈdɪktɪv ˈmɒdəlɪŋ/
Noun
Defintion for Predictive Modeling
The process of using statistical techniques and algorithms to create models that can predict future outcomes based on historical data.
Long Definition
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.
Kaizen Insights
Kaizen uses predictive modeling to analyze training data and provide personalized insights, such as estimating VO2 Max, to enhance performance predictions and optimize training plans.
Category
Race Prediction & Kaizen Metrics
