{"id":48366,"date":"2026-07-04T06:05:41","date_gmt":"2026-07-04T06:05:41","guid":{"rendered":"https:\/\/www.europesays.com\/germany\/48366\/"},"modified":"2026-07-04T06:05:41","modified_gmt":"2026-07-04T06:05:41","slug":"sex-differences-in-marathon-pacing-analysis-of-873000-berlin-marathon-runners-reveals-men-are-twice-as-likely-to-hit-the-wall","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/germany\/48366\/","title":{"rendered":"Sex differences in marathon pacing: analysis of 873,000 Berlin marathon runners reveals men are twice as likely to \u201chit the wall\u201d"},"content":{"rendered":"

The primary aim of this study was to determine whether the sex differences in marathon pacing strategies observed in smaller cohorts persist within a massive, high-performance dataset. Our analysis of over 870,000 finishers confirms that male runners exhibit significantly less stable pacing strategies than female runners, validating our hypothesis that men, regardless of performance level, are more prone to aggressive pacing and catastrophic deceleration. Despite a faster mean finish time, men demonstrated a twofold higher risk (OR\u2009=\u20092.00) of \u201chitting the wall\u201d compared to women. This finding corroborates previous observations by Deaner et al.20<\/a> and Hubble & Zhao15<\/a>, who identified similar trends in US-based marathons. However, the unprecedented scale of the current study (n\u2009=\u2009873,334) provides conclusive evidence that this is a pervasive phenomenon across the global running population, robust against variations in course topography or annual weather conditions14<\/a>,21<\/a>.<\/p>\n

Perhaps the most counterintuitive finding of this investigation is the amplification of the sex risk disparity among the highest-performing athletes, revealing that superior physiological conditioning does not inoculate male runners against catastrophic pacing failures. It is often assumed that pacing stability improves linearly with performance level and experience22<\/a>. However, our stratified analysis reveals a paradox: while the absolute incidence of hitting the wall decreases with speed, the relative risk disparity between sexes actually widens. In the Competitive category (<\u20093:00\u00a0h), male runners were 6.06 times more likely to experience catastrophic deceleration than their female counterparts. This contradicts the notion that pacing errors are solely a function of inexperience. Instead, it suggests that high-performance male runners may be prone to adopting high-risk strategies\u2014running closer to their physiological ceiling\u2014potentially shaped by competitive pressures and the complex dynamics of decision-making under physical stress23<\/a>.<\/p>\n

Consistent evidence indicates that men exhibit, on average, greater skeletal muscle mass, a larger cross-sectional area of muscle fibers\u2014particularly type II fibers\u2014greater maximal strength, higher muscle power, higher V\u0307O2max and greater anaerobic capacity compared with women7<\/a>,24<\/a>. These differences are predominantly attributed to greater lifetime exposure to testosterone during and after puberty, which promotes muscle hypertrophy, a higher proportion of fast-twitch fibers, greater cardiac dimension, blood volume, hemoglobin mass and enhanced glycolytic capacity, resulting in superior performance in tasks requiring high force, power output and aerobic capacity7<\/a>,25<\/a>.<\/p>\n

Conversely, women showed to present superior pacing stability, which is likely supported by distinct physiological mechanisms. Research into substrate utilization has consistently demonstrated that women exhibit higher rates of lipid oxidation and lower respiratory exchange ratios26<\/a> during sub-maximal endurance exercise27<\/a>,28<\/a>, and greater relative proportion of type I muscle fibers compared to men7<\/a>,24<\/a>. These differences have been associated with differences in muscle fiber typology, greater oxidative capacity, and hormonal modulation by estradiol28<\/a>,29<\/a>.<\/p>\n

These differences in muscle fiber typology and metabolic profile allows for greater glycogen sparing, effectively delaying the onset of glycogen-depletion-induced fatigue, commonly known as \u201cthe wall\u201d30<\/a>. Consequently, even when running at comparable relative intensities, female runners present a more favourable substrate-utilization profile, which may contribute to the lower prevalence of pronounced second-half deceleration observed in the female cohort28<\/a>.<\/p>\n

Beyond physiological mechanisms, gender-related factors may also contribute to the observed sex disparity in pacing. The behavioral economics literature suggests that men, on average, more often overestimate their competitive ability and tolerate higher risk in competitive contexts31<\/a>,32<\/a>,33<\/a>, which in a self-paced endurance setting could plausibly manifest as more aggressive starting splits and reduced pacing discipline16<\/a>,17<\/a>. The present study, however, did not collect the data required to test these mechanisms directly: psychometric assessment of competitive risk preference, pacing intention and confidence calibration, or qualification-pressure proxies. The behavioral interpretation is therefore presented as a hypothesis to be evaluated by future studies that pair archival pacing data with individual-level psychometric measurement.<\/p>\n

Therefore, current evidence is consistent with the hypothesis that, although sex-specific physiological characteristics modulate the development of fatigue during prolonged endurance exercise, behavioral and strategic factors related to pacing decisions may contribute substantially to sex differences in marathon pacing16<\/a>,17<\/a>. However, the present dataset does not directly measure psychological variables, and alternative mechanisms\u2014including competitive density, qualification pressure, tactical effects, substrate utilization, training distribution, and participation demographics\u2014warrant further investigation7<\/a>.<\/p>\n

The substantial increase from the crude (OR\u2009=\u20092.00) to the adjusted (OR\u2009=\u20093.88) estimate of the male-to-female odds of hitting the wall reflects negative confounding by performance category. In this cohort, female finishers cluster disproportionately in slower performance tiers where the marginal prevalence of pronounced deceleration is higher (Table\u00a02<\/a>); the crude OR therefore reflects a population-level disparity that is attenuated by this differential demographic mix. The stratified ORs in Table\u00a02<\/a> (ranging from 3.32 in the Casual category to 6.14 in the Competitive category) are internally consistent with the adjusted estimate (OR\u2009=\u20093.88) as a category-weighted average of within-stratum effects, all of which exceed the crude OR (2.00) and confirm the direction and magnitude of the negative confounding. We acknowledge that performance category is itself partly determined by sex-related physiological capability and may lie on the causal pathway between sex and pacing failure; we therefore interpret the adjusted OR as the within-category sex effect rather than as a population-level causal contrast, and we report both the crude and the adjusted estimates to make this distinction transparent. Variance inflation factors and model diagnostics (Supplementary Table S6<\/a>) confirm that multicollinearity between sex, age, and performance category is modest (all VIF\u2009<\u20095).<\/p>\n

It is also important to acknowledge the influence of environmental conditions on race dynamics. Recent observational studies of the Berlin Marathon have established that environmental factors are strong predictors of running performance34<\/a>. Furthermore, specific climatic variables, such as temperature and barometric pressure, have been shown to directly modulate the pacing strategies and running speeds of even the fastest elite competitors35<\/a>. However, the strength of the current investigation lies in its 27-year longitudinal scope, which encompasses a wide spectrum of weather patterns. The persistence of the sex-based pacing disparity across this extensive timeline suggests that the male tendency toward more aggressive pacing is a pattern that appears robust across the variety of environmental conditions captured in the 27-year dataset.<\/p>\n

The fine-grained pacing metrics (within-runner coefficient of variation across 5\u00a0km segments, the sustained inflection point, and late-race deceleration) jointly characterize the shape of the slowdown rather than only its endpoint magnitude. They show that the sex disparity is not confined to the tail of the slowdown distribution (Figs.\u00a01<\/a>) but is also expressed in the mean response across performance categories (Fig.\u00a03<\/a>) and earlier in the race trajectory over a wider segment (Fig.\u00a04<\/a>). This strengthens the interpretation that the observed difference reflects a systematic contrast in pacing strategy across the race, rather than a discrete late-race failure event affecting a small fraction of male runners.<\/p>\n

Fig. 1\"Fig.<\/p>\n

Probability density distribution of pacing strategies (Percentage Slowdown) by sex among Berlin Marathon finishers (Men: n\u2009=\u2009659,294 total, of whom n\u2009=\u2009658,790 had valid pacing data plotted; Women: n\u2009=\u2009214,040 total, of whom n\u2009=\u2009213,880 had valid pacing data plotted). The figure illustrates the kernel density estimation of pacing variability for male (grey) and female (red) runners. The horizontal axis represents the Percentage Slowdown, calculated as the relative time difference between the second and first half of the race, where positive values indicate deceleration (positive split). Visually, the peak of the female distribution is shifted to the left relative to the male peak, indicating that women, on average, maintain a strategy closer to an even split. The male distribution is noticeably wider (greater dispersion) and exhibits a more pronounced right tail (higher skewness), demonstrating a higher relative frequency of extreme deceleration compared to the more compactly clustered female cohort.<\/p>\n

Fig. 2\"Fig.<\/p>\n

Prevalence of catastrophic deceleration (\u201chitting the wall\u201d) by sex among Berlin Marathon finishers. The figure displays the proportion of male (grey) and female (red) runners who experienced a pacing collapse, operationally defined as a percentage slowdown of\u2009\u2265\u200920% in the second half of the race relative to the first. Error bars represent 95% confidence intervals computed via the Wilson score interval for proportions. The data illustrates a marked disparity in pacing failure rates, with male runners being significantly more likely to reach this threshold compared to female runners (17.63% vs. 9.66%, with non-overlapping 95% CIs). This difference corresponds to a crude Odds Ratio (OR) of 2.00 (95% CI 1.97\u20132.03), indicating that men face a twofold greater relative risk of pronounced second-half deceleration compared to women within the same event conditions.<\/p>\n

Fig. 3\"Fig.<\/p>\n

Sex disparity in mean percentage slowdown stratified by performance level (Finish Time). Comparison of the mean percentage slowdown between male (grey bars) and female (red bars) runners across five distinct performance categories, ranging from Competitive (<\u20093:00\u00a0h) to Casual (>\u20094:30\u00a0h). Error bars represent the 95% confidence interval of the mean (1.96\u2009\u00d7\u2009standard error); sample sizes per category\u2009\u00d7\u2009sex are indicated above each bar. The data reveals a consistent \u201cpacing gap\u201d where male runners exhibit significantly greater deceleration than female runners within every performance tier (p\u2009<\u20090.001). Notably, while the magnitude of the slowdown increases for both sexes as finish times increase, the relative disparity persists even among the fastest cohorts, challenging the assumption that higher performance levels eliminate sex-based pacing differences.<\/p>\n

Fig. 4\"Fig.<\/p>\n

Fine-grained pacing analysis among runners with valid 5\u00a0km splits (Men: n\u2009=\u2009645,699; Women: n\u2009=\u2009211,060). (a) Violin plot of the coefficient of variation (CV) of pace across 5\u00a0km segments by sex, illustrating greater pacing irregularity in male runners (median higher; broader upper tail). (b) Boxplot of the inflection point (km), defined as the first 5\u00a0km segment with sustained pace deterioration relative to the pre-half-marathon mean, by sex. Boxes show the interquartile range; whiskers extend to 1.5\u2009\u00d7\u2009IQR; the central line marks the median. Runners without a defined inflection\u2014under the strict criterion that pace must exceed the pre-half-marathon mean by\u2009>\u20095% and remain slower for all subsequent segments through the finish\u2014represent\u2009~\u200936% of men and\u2009~\u200952% of women and are excluded from the boxplot.<\/p>\n

Practical applications<\/p>\n

These findings suggest that male runners\u2014particularly those aiming for aggressive time goals\u2014would benefit from pacing strategies that mimic the female approach: conservative starting splits and a focus on negative splitting. Future coaching interventions could explore strategies addressing the apparent tendency in male runners toward aggressive early pacing. Furthermore, while men possess the physiological advantages (e.g., V\u0307O2max, hemoglobin mass) that dictate the upper limits of absolute speed, women appear to possess superior regulatory mechanisms for energy management. Finally, these findings reinforce the importance of considering biological sex as a key determinant in the interpretation of athletic performance and exercise responses7<\/a>.<\/p>\n

LimitationsSeveral limitations should be acknowledged<\/p>\n

First, while the dataset is extensive, it relies on net finish times and splits without direct physiological measures (e.g., heart rate, lactate, or glycogen levels), preventing a definitive causal link between pacing decline and specific metabolic events. The pacing-derived definition of \u201chitting the wall\u201d is an operational proxy for catastrophic deceleration; direct evidence of substrate exhaustion (e.g., muscle biopsy or indirect calorimetry) was not available, and the metabolic mechanisms discussed should be interpreted as plausible inferences rather than directly measured outcomes.<\/p>\n

Second, although the Berlin Marathon course is flat, weather conditions varied across the 27-year period; while our large sample size mitigates individual anomalies, extreme weather years could influence aggregate pacing strategies. The temporal trend analysis (Fig.\u00a05<\/a>) revealed substantial inter-annual variability in the sex prevalence gap (range 2.8 to 19.9 percentage points), likely reflecting environmental and cohort composition differences across editions; the absence of a systematic trend across the 27-year archive supports the interpretation that the disparity is structural rather than era-specific.<\/p>\n

Fig. 5\"Fig.<\/p>\n

Temporal evolution of the sex disparity in wall-hit prevalence across the Berlin Marathon archive (1999\u20132025; 26 editions analyzed; 2020 cancelled due to COVID-19). Annual prevalence by sex (scatter; men grey, women red) with smoothed 3-year rolling-mean trends (lines). The Mann\u2013Kendall trend test indicated no statistically detectable change in the prevalence gap (\u03c4\u2009=\u20090.14, p\u2009=\u20090.33); linear regression with year as predictor of the gap likewise did not reach significance (slope\u2009=\u2009\u2009+\u20090.12 percentage points\/year, p\u2009=\u20090.17). The high inter-annual variability (gap range 2.8\u201319.9 percentage points) likely reflects environmental and cohort composition differences across editions; the absence of a systematic temporal trend supports the interpretation that the sex disparity is a structural feature of marathon pacing across the 27-year archive.<\/p>\n

Third, the operational definition of \u201chitting the wall\u201d as a\u2009\u2265\u200920% slowdown is necessarily a discretization of what is likely a continuous phenomenon. The binary criterion was adopted to enable interpretable risk comparisons between groups, and its robustness was supported by sensitivity analyses at 15% and 25% thresholds (Supplementary Table S2<\/a>). The graded severity distribution (Supplementary Table S2<\/a>) further reveals that the sex disparity persists across the continuum of slowdown magnitudes. Future work could explore individualized pacing expectations (e.g., z-score deviations from predicted pacing) or dynamic fatigue modeling to better characterize the gradual nature of pacing collapse16<\/a>. More advanced trajectory analyses (changepoint detection, mixed-effects pacing models, functional data analysis of full split trajectories) were not pursued in the present descriptive framework and represent natural extensions for future work.<\/p>\n

Fourth, the analytical cohort comprises only those runners who completed the marathon. The official BMW Berlin Marathon results archive, by design, records finishers exclusively; runners who did not finish (DNF) are absent from the dataset and consequently from the present analyses. The true prevalence of catastrophic pacing failure in the broader starting field is therefore likely to be underestimated, since some runners who experience severe pacing collapse may withdraw before the finish line rather than complete the race at substantially reduced pace. This finisher-only constraint is shared with other large-scale archival marathon analysess16<\/a>. While we cannot directly quantify the magnitude of this bias, the sex comparison that constitutes the primary inferential target is unlikely to be qualitatively affected unless DNF rates differ substantially between male and female runners\u2014a question that future work integrating start-line registration data with finish results could address.<\/p>\n

Fifth, the analytical sample comprises race entries rather than uniquely identified runners; the same individual may complete the marathon in multiple years. Although a sensitivity analysis using a deduplicated subset (Supplementary Table S3<\/a>) confirmed the direction and approximate magnitude of the sex disparity, the deduplication relied on imperfect name matching (composite key of normalized name\u2009+\u2009age group) and is therefore conservative; some entries from the same runner may have remained classified as distinct due to spelling variations across editions. We treat the deduplicated analysis as a robustness check rather than a definitive correction; future archival collaborations with race organizers using persistent runner identifiers could provide a more precise estimate of the within-runner variance component.<\/p>\n

Finally, although the multivariable logistic regression and within-cohort percentile re-stratification (Supplementary Tables S1<\/a> and S4<\/a>) provide complementary demographic adjustment, the present study did not employ external age-graded performance standards (e.g., World Masters Athletics tables); future work could extend this normalization to triangulate the magnitude of the sex effect under explicit age-graded benchmarks.<\/p>\n

An additional methodological consideration concerns one of the fine-grained pacing metrics (oscillation count), where the observed direction was opposite to that initially anticipated (women showed slightly more sign-changes in the pace gradient than men, d\u2009=\u2009\u2212\u20090.18; Supplementary Table S5<\/a> The mechanistic interpretation of this pattern requires further investigation and is not advanced in the present work.<\/p>\n","protected":false},"excerpt":{"rendered":"The primary aim of this study was to determine whether the sex differences in marathon pacing strategies observed…\n","protected":false},"author":2,"featured_media":48367,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[14401,18,40323,5485,7102,20876,7103,40319,40321,40320,20393,134,40322],"class_list":["post-48366","post","type-post","status-publish","format-standard","has-post-thumbnail","category-berlin","tag-athletic-performance","tag-berlin","tag-fatigue","tag-health-care","tag-humanities-and-social-sciences","tag-marathon","tag-multidisciplinary","tag-neuroscience","tag-pacing-strategies","tag-physiology","tag-psychology","tag-science","tag-sex-characteristics"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/posts\/48366","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/comments?post=48366"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/posts\/48366\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/media\/48367"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/media?parent=48366"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/categories?post=48366"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/germany\/wp-json\/wp\/v2\/tags?post=48366"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}