Physiology & performance prediction
Critical speed, running economy, and how finish times are actually predicted.
Two threads run through this section. The first is the machinery of endurance: running economy, the critical power and critical speed models, the long-running argument over what the anaerobic threshold even is. The second is prediction, with a set of papers on estimating half-marathon and marathon times from training data rather than from a recent race.
That second thread is the one Leo leans on most, because it is what lets him give you a finish-time range without asking you to race first. The papers here are also honest about the limits: prediction degrades badly when training volume is low, when the terrain changes, and in the specific case of late-race collapse, which one large-scale analysis in this section treats as its own phenomenon rather than as a pacing error. Leo therefore presents estimates as ranges with a stated reliability, never as a single confident number.
Papers in this domain
27 peer-reviewed references. Titles link to the publisher via DOI.
Cardiorespiratory fitness, body mass index and mortality: a systematic review and meta-analysis
Weeldreyer et al. · 2024 · DOI 10.1136/bjsports-2024-108748
Martínez-Vizcaíno et al. · 2024 · DOI 10.1186/s12889-024-19383-z
Van Hooren et al. · 2024 · DOI 10.1007/s40279-024-01997-3
Prediction of Half-Marathon Power Target Using the 9/3-Minute Running Critical Power Test
Olaya-Cuartero et al. · 2023
Prediction of Marathon Performance Using Artificial Intelligence
Lerebourg et al. · 2023
Predictors of Half-Marathon Performance in Male Recreational Athletes
Nikolaidis, Knechtle · 2023 · DOI 10.17179/excli2023-6198
Tarp et al. · 2021 · DOI 10.1136/bjsports-2021-104827
How Recreational Marathon Runners Hit the Wall: A Large-Scale Data Analysis of Late-Race Pacing Collapse in the Marathon
Smyth · 2021
The Anaerobic Threshold: 50+ Years of Controversy
Poole, Rossiter, Brooks, Gladden · 2021 · DOI 10.1113/JP279963
Calculation of Critical Speed from Raw Training Data in Recreational Marathon Runners
Smyth, Muniz-Pumares · 2020
Vassallo, Gray et al. · 2020 · DOI 10.1007/s00421-019-04266-8
Blüher et al. · 2020 · DOI 10.1210/endrev/bnaa004
Predictive Performance Models in Long-Distance Runners: A Narrative Review
Alvero-Cruz et al. · 2020
Uphill and Downhill Running: Biomechanics, Physiology and Modulating Factors
Lu, Suo et al. · 2020 · DOI 10.3389/fbioe.2025.1690023
Critical Velocity Estimated Using Statistically Appropriate Fitting Procedures
Patoz, Spicher et al. · 2019 · DOI 10.1007/s00421-021-04675-8
Faelli, Panascì et al. · 2019 · DOI 10.3390/ijerph18168386
Predictive Variables of Half-Marathon Performance for Male Runners
Gómez-Molina et al. · 2017
McHugh · 2017 · DOI 10.1034/j.1600-0838.2003.02477.x
VO2max Trainability and High Responders/Low Responders
Montero & Lundby · 2017 · DOI 10.1249/MSS.0000000000001215
Altered Running Economy Directly Translates to Altered Distance-Running Performance
Hoogkamer, Kipp, Spiering, Kram · 2016
Prediction of Half-Marathon Race Time in Recreational Female and Male Runners
Knechtle et al. · 2014
Running Speed During Training and Percent Body Fat Predict Race Time in Recreational Male Marathoners
Barandun, Knechtle et al. · 2012
Precision in the Prediction of Middle Distance Running Performances Using Either a Nomogram or the Modeling of the Distance-Time Relationship
Coquart, Bosquet · 2010
The Concept of Critical Power: Applications to Sports Performance, with Emphasis on High-Intensity Intermittent Exercise
Jones, Vanhatalo et al. · 2010
Validity of a Nomogram to Predict Long Distance Running Performance
Coquart, Alberty, Bosquet · 2009
Factors Influencing Running Economy in Trained Distance Runners
Saunders et al. · 2004
Energy Cost of Walking and Running on Extreme Slopes (Uphill and Downhill)
Minetti et al. · 2002
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