How does the previous marathon affect the next one?
Across the displayed race-interval bands, median next-finish change ranged from -0.7% to +0.1%. Individual outcomes were much more variable than those medians. The data do not identify an optimal recovery interval.
These are observed scheduling choices, not recommendations for a recovery interval.
How we measured it. Use only linked identity groups for which every eligible record has a unique supplied race date. Order by that date, pair adjacent races and retain intervals of 1–1095 days. Unlike the year-based analyses, this includes same-year pairs. Dates come from the supplied calendar overlay and have not all been independently reverified.
Full methodology & sources
Calculate 100 × (next finish / previous finish − 1) and its 10th/50th/90th percentiles in the displayed day bands. The second view requires the earlier race to beat every recorded finish in earlier calendar years; same-year bests are not used for that label. Fitness, course, motivation and selection into short or long intervals remain confounders.
For explicitly audited canonical-ID releases, validate unique matching CORE/FULL ID sets and matching recorded edition/name labels, then join by record ID with matching finish and all nine section durations. Legacy exports retain the one-to-one edition, trimmed lowercase name and full-timing join because their IDs are incompatible. Durations are compared to milliseconds. Keep only supplied non-ambiguous runner identities without conflicting recorded gender, inferred birth years spanning more than two years, or duplicate editions. These are candidate cross-race identities, not independently verified people; unlinked runners are absent. The linkage audit records which join was used.
Use complete, strictly increasing elapsed checkpoints at 3.11, 6.21, 9.32, 12.43, 15.53, 18.64, 21.75, 24.85 and 26.22 mi. Clock strings must parse as H:MM:SS or M:SS. No missing splits are interpolated.
Remove exact duplicate race records, ignoring database IDs, ingestion timestamps and source URLs. Retain finishes from 90 minutes to 12 hours with every section between 3.22 and 32.19 minutes/mi. These quality filters can exclude genuine unusual performances; the analysis describes this eligible cohort, not every entrant.
Full source records are available in public GitHub Releases. These chart tables require at least 100 eligible observations per cell for estimate reliability. Counts refer to finishes, linked pairs or event observations as specified in that answer.
These are observational results. Fitness changes, intentions, training, selection into the dataset and unmeasured conditions can explain differences. Outcome percentiles describe variation among performances, not confidence intervals or advice about the best strategy.
Apply the reviewed source-quality edition exclusions for this exact export after the timing checks. Known invalid split grids, incomplete ingestion, unreconciled HOLD editions and a selected top-finisher field do not contribute to the analyses or prior benchmarks. Report source exclusions separately; an already invalid timing row is not counted twice. Missing age or recorded gender alone does not exclude an otherwise eligible finish from the overall cohort. Other sparse editions are not declared incomplete merely from their size.
Next performance by recorded race interval
Finish-time change (%) · below zero is faster
View exact values and sample sizes
| Group | 10th percentile | Median | 90th percentile | 10th percentile: Observations | Median: Observations | 90th percentile: Observations |
|---|---|---|---|---|---|---|
| 1–89 days | -11.1% | -0.4% | 13.2% | 7,378 | 7,378 | 7,378 |
| 90–179 days | -10% | -0.7% | 10.4% | 20,400 | 20,400 | 20,400 |
| 180–364 days | -9.6% | -0% | 11.8% | 279,156 | 279,156 | 279,156 |
| 365–729 days | -9.6% | 0% | 10% | 214,418 | 214,418 | 214,418 |
| 730–1095 days | -12.3% | 0.1% | 15.2% | 82,473 | 82,473 | 82,473 |