Race Prediction

Estimation Methods

1. From Recent Race Results (Most Accurate)

Use equivalence tables to predict other distances from a known race time.

Riegel Formula: T2 = T1 * (D2/D1)^1.06

• •More accurate for similar distances
• •Overestimates for much longer distances (fatigue factor)

Common Conversions:

Examples:

• •20:00 5K -> ~3:16-3:24 Marathon
• •45:00 10K -> ~3:27-3:36 Marathon
• •1:35 Half -> ~3:18-3:25 Marathon

2. From Training Data (When No Recent Races)

From Threshold Pace:

• •Threshold pace (tempo run pace) ~ half marathon race pace
• •Marathon pace ~ threshold + 15-25s/km
• •Use: recent tempo/threshold workout paces

From Long Run Pace:

• •Long run easy pace is typically 1:00-1:30/km slower than marathon pace
• •If long runs averaging 6:00/km -> marathon pace ~4:45-5:00/km

From Easy Run Pace:

• •Easy pace is typically 1:30-2:00/km slower than threshold
• •Less reliable but useful as a sanity check

3. VDOT-Based Estimation

VDOT is a single number representing running fitness. Key reference points:

Confidence Levels

High Confidence

• •Based on a race within last 6 weeks at a similar distance
• •Training data is consistent and extensive (8+ weeks)
• •Athlete has run the predicted distance before

Medium Confidence

• •Based on training paces only (no recent race)
• •Race was >6 weeks ago
• •Predicting a distance the athlete hasn't raced

Low Confidence

• •Limited training data (<4 weeks)
• •Predicting from a very different distance (5K -> ultra)
• •Significant fitness changes expected before race
• •First-time at the distance

Environmental Adjustments

Heat

• •+5-10s/km for temperatures above 15C
• •+15-30s/km for temperatures above 25C
• •Humidity amplifies the effect

Altitude

• •+3-5% time for every 1000m above sea level
• •Acclimatization takes 2-3 weeks

Terrain

• •Trail races: add 20-50% to road time depending on technicality
• •Hilly courses: roughly +1s/km per 10m elevation gain per km

Wind

• •Headwind costs more than tailwind saves (net negative for out-and-back)
• •Strong headwind can add 10-30s/km

Tracking Prediction Evolution

When saving predictions:

1. •Always record the basis (what data drove the estimate)
2. •Record confidence level
3. •Use save_race_prediction to persist to SQLite
4. •Use get_prediction_history to show trends
5. •Compare predictions over time: are they improving, plateauing, or declining?

Prediction trends inform coaching:

• •Improving: Training is working, stay the course
• •Plateauing: May need stimulus change (new workout types, more volume)
• •Declining: Check for overtraining, life stress, injury