{
  "slug": "marathon-predictor",
  "title": "Marathon Time Predictor",
  "category": "Running",
  "category_slug": "running",
  "tier": 1,
  "summary": "Estimate your marathon finish time from a recent half-marathon performance using Riegel's formula.",
  "description": "This calculator estimates marathon finish time from a recent half-marathon performance using the Riegel formula, a widely-used endurance prediction model published in Runner's World in 1977. It applies a fatigue exponent of 1.06 to extrapolate race time across the distance ratio (21.0975 km to 42.195 km), taking half-marathon time in minutes as input and returning a predicted marathon time with average pace. The estimate assumes similar training status, race conditions, and pacing strategy between the two distances, and tends to be most accurate for runners who have trained specifically for the marathon distance.",
  "page_url": "https://fitmetriclab.com/en/tools/running/marathon-predictor/",
  "api_url": "https://fitmetriclab.com/api/tools/marathon-predictor.json",
  "formula": {
    "id": "marathon_predictor",
    "expression": "T_{42.2} = T_{half} \\times \\left(\\frac{42.2}{21.1}\\right)^{1.06}",
    "variables": [
      {
        "symbol": "T_{half}",
        "description": "Half-marathon time in minutes"
      }
    ]
  },
  "inputs": [
    {
      "id": "half_time_min",
      "label": "Half-Marathon Time",
      "type": "number",
      "unit": "min",
      "default": 100,
      "min": 30,
      "max": 300,
      "step": 0.5
    }
  ],
  "worked_example": {
    "inputs": {
      "half_time_min": 100
    },
    "expected_output": "3:28:30"
  },
  "result_summary_template": "Given a half-marathon time of {half_time_min} minutes, the Riegel formula with fatigue exponent 1.06 estimates a marathon finish time of {result}.",
  "methodology": "Applies the Riegel formula T₂ = T₁ × (D₂/D₁)^1.06 with a fatigue exponent of 1.06, extrapolating from half-marathon (21.0975 km) to marathon (42.195 km) distance. Developed by Peter Riegel and published in Runner's World (1977).",
  "sources": [
    {
      "label": "Riegel, P. Athletic records and human endurance. American Scientist, 1981.",
      "url": "https://www.americanscientist.org/article/athletic-records-and-human-endurance"
    },
    {
      "label": "Vickers, A.J., Vertosick, E.A. An empirical study of race times in recreational endurance runners. BMC Sports Science, Medicine and Rehabilitation, 2016.",
      "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5121943/"
    },
    {
      "label": "Daniels, J. Daniels' Running Formula (3rd ed.). Human Kinetics, 2013.",
      "url": "https://us.humankinetics.com/products/daniels-running-formula-3rd-edition"
    }
  ],
  "faqs": [
    {
      "question": "Why does the tool use a 1.06 exponent instead of simply doubling?",
      "answer": "The 1.06 exponent reflects fatigue accumulation over longer distances. Doubling half-marathon time assumes linear pace degradation, but empirical data show that pace slows more steeply as distance increases beyond lactate-threshold duration. Riegel's model captures this nonlinear slowdown with an exponent derived from aggregate race-performance data."
    },
    {
      "question": "How recent should my half-marathon time be for an accurate prediction?",
      "answer": "Predictions are most reliable when the input race occurred within 8–12 weeks of the target marathon and reflects current fitness. Older performances may not account for gains or losses in aerobic capacity, neuromuscular efficiency, or body composition. Seasonal detraining or injury layoffs reduce the validity of older race times."
    },
    {
      "question": "Can this calculator predict ultra-marathon times?",
      "answer": "No. The Riegel formula with exponent 1.06 is calibrated for road-race distances from 5K to marathon. Ultra distances introduce additional variables—terrain technicality, mandatory aid-station stops, sleep deprivation—that fall outside the model's scope. Separate prediction equations exist for ultra events, typically with higher exponents (1.08–1.10)."
    },
    {
      "question": "What if my half-marathon was hilly or had poor weather?",
      "answer": "The tool applies a mathematical ratio without adjusting for course difficulty or environmental conditions. A half-marathon completed on a hilly course or in heat may underestimate marathon potential if the goal race is flat and cool. Conversely, a fast, downhill half may overestimate marathon capability. Comparing performances on similar courses improves accuracy."
    },
    {
      "question": "Does the prediction change if I add marathon-specific training?",
      "answer": "The calculator outputs a static estimate based on current half-marathon performance. Marathon-specific training—progressive long runs, tempo work at goal pace, glycogen-depletion runs—can improve the fatigue resistance that Riegel's exponent approximates. Structured training may enable results faster than the initial prediction, while inadequate long-run volume may lead to slower outcomes."
    }
  ],
  "related_tools": [
    {
      "slug": "race-time-predictor",
      "title": "Race Time Predictor (Riegel Formula)",
      "api_url": "https://fitmetriclab.com/api/tools/race-time-predictor.json",
      "page_url": "https://fitmetriclab.com/en/tools/running/race-time-predictor/"
    },
    {
      "slug": "marathon-splits",
      "title": "Marathon Splits Calculator",
      "api_url": "https://fitmetriclab.com/api/tools/marathon-splits.json",
      "page_url": "https://fitmetriclab.com/en/tools/running/marathon-splits/"
    },
    {
      "slug": "vdot-calculator",
      "title": "VDOT Calculator (Jack Daniels)",
      "api_url": "https://fitmetriclab.com/api/tools/vdot-calculator.json",
      "page_url": "https://fitmetriclab.com/en/tools/running/vdot-calculator/"
    }
  ],
  "last_updated": "2026-04-22",
  "price": {
    "value": 0,
    "currency": "USD"
  },
  "runs_in_browser": true,
  "disclaimer": "Educational estimate produced from a published formula. Not medical, nutritional, or training advice. Calculations are deterministic — apply the formula to the inputs to reproduce the result."
}