eval set · question 1 of 22 · graded by hand
Does higher weekly mileage improve marathon performance?
Higher weekly running distance and volume are associated with faster marathon finish times across elite and recreational runners (strong evidence, meta-analysis of 137 cohorts). 1
Higher training volume including weekly distance, sessions, and quality sessions is associated with faster Boston Marathon times. 2
Better marathon performance correlates with higher training volume combined with low-intensity emphasis and limited high-intensity volume. 3
Higher weekly mileage is associated with lower cardiac troponin (cTnI) elevation post-race, suggesting a protective effect, while frequent very long runs (20+ miles) raise cTnI. 4
Higher training mileage is associated with lower injury risk in marathon and half-marathon runners, whereas undertraining and low mileage increase injury risk. 5
Moderate-intensity (Z2) training volume and time-normalized internal load are linked to better endurance performance, suggesting quality/intensity distribution matters alongside volume. 6
Training approach (e.g., polarized vs pyramidal) and individual matching also affect performance improvements, indicating mileage alone isn't the only factor. 7
What we can't tell you
- Exact dose-response threshold beyond which more mileage stops helping or increases injury/harm risk is not specified.
- Whether these mileage findings generalize equally to all skill levels (elite vs beginner) is unclear.
- see a professional for personalized training or injury-related decisions
Sources
Increases in various training parameters (weekly running distance, number of weekly runs, maximum weekly distance, long runs ≥32km, training pace, longest run, and weekly running hours) are associated with faster marathon finish times in elite and recreational marathoners.
pop. Elite and recreational marathon runners (42.2km); 137 cohorts from 85 studies, 25% female · direction Positive (increased training parameters associated with faster finish times) · design Systematic review and meta-regression of observational and interventional studies · strong
An evaluation of the training determinants of marathon performance: A meta-analysis with meta-regression. (2019) · doi 10.1016/j.jsams.2019.09.013
Higher running distance per week, running sessions per week, quality sessions per week, and cross-training in the 4-0 months pre-race, combined with decreased running sessions per week in the final 4 months, are associated with faster Boston Marathon race times.
pop. Adult Boston Marathon registrants (917 athletes: 495 female, 422 male; mean weekly distance 64.4-67.6 km/week) · direction Positive: higher volume and quality sessions associated with faster times; decreased training frequency in final 4 months associated with faster times versus maintained/increased frequency · design Cross-sectional observational study with linear regression · weak
Training Volume and Training Frequency Changes Associated with Boston Marathon Race Performance. (2026) · doi 10.1007/s40279-025-02304-4
Marathon finishers with better performance show higher training volume, higher shares of low-intensity training, continuous velocity increases, and high-intensity runs ≤5% of overall volume.
pop. Marathon finishers (n=6,771) using fitness app data · direction positive (better performance associated with higher volume, low-intensity emphasis, and structured intensity distribution) · design retrospective cohort analysis · weak
Retrospective Analysis of Training and Its Response in Marathon Finishers Based on Fitness App Data (2021) · doi 10.3389/fphys.2021.669884
Female runners experience greater BNP elevation at 24 hours post-marathon, while higher weekly mileage is associated with lower cTnI immediately post-race, and more frequent 20+ mile long runs are associated with higher cTnI immediately post-race
pop. Recreational marathon runners (13 female, 9 male) · direction Gender effect on BNP (greater in females); negative association between weekly mileage and cTnI; positive association between frequency of 20+ mile runs and cTnI · design Prospective cohort · weak
The influence of non-modifiable and modifiable factors on cardiac biomarkers post-marathon running. (2019) · doi 10.23736/S0022-4707.19.09247-8
Previous running injuries, undertraining, lower weekly mileage, and inexperience increase race-related injury risk in marathon runners
pop. Adults participating in half marathons (n=1043) and full marathons (n=624) · direction negative for injury risk with higher training mileage (>23 miles/week for half marathons, >40 miles/week for full marathons); positive for injury risk with previous injury, lower mileage, younger age (half marathons), female sex (half marathons), and less experience (full marathons) · design Observational cross-sectional study · moderate
Factors Associated With Half- and Full-Marathon Race-Related Injuries: A 3-Year Review (2019) · doi 10.1097/JSM.0000000000000775
Moderate-intensity training (Z2) volume and higher time-normalized internal load (eTRIMP/min) are significantly associated with better endurance performance in recreational marathon and half-marathon runners.
pop. 48 recreational runners (22 marathoners, 26 half-marathoners) preparing for marathon or half-marathon · direction negative correlation with Z2 volume and eTRIMP/min indicating better performance with increased moderate-intensity training · design cohort study with correlational analysis · moderate
Training Intensity Distribution, Load Management, and Performance in Recreational Long-Distance Runners. (2026) · doi 10.1123/ijspp.2025-0348
Polarized training produces superior marathon performance improvements compared to pyramidal training in recreational marathon runners, with personalized matching to athlete characteristics improving outcomes.
pop. 120 recreational marathon runners (60 per group) · direction positive for polarized training (11.3±3.2 min vs 8.7±2.8 min improvement; 30% greater enhancement), with training experience as strongest predictor of which method works best for individual · design Randomized controlled trial · moderate
Machine learning-based personalized training models for optimizing marathon performance through pyramidal and polarized training intensity distributions. (2025) · doi 10.1038/s41598-025-25369-7