| Metric | Value | Copy |
|---|---|---|
| {{ row.label }} | {{ row.value }} |
| Marker | Distance | Cumulative time | Segment pace | Copy |
|---|---|---|---|---|
| {{ split.label }} | {{ split.distanceDisplay }} | {{ split.timeDisplay }} | {{ split.paceDisplay }} |
The pacing timeline plots cumulative finish time versus distance using the Tanda projection and your adjustment.
Marathon pace predictions translate your recent training into an estimated finish time so you can tell whether a planned race target feels realistic. The idea is to link weekly distance, average steady run speed and the number of sessions you complete to the performance you can usually sustain over a full marathon.
You provide your typical weekly distance, your average speed across steady aerobic runs and how many times you run in a week. The calculator then turns those values into a predicted finish time, headline pace per kilometre or per mile and an overview of how race effort compares with your everyday training.
Once a prediction is available you see checkpoint splits for common markers such as five kilometres, ten kilometres and the halfway point, along with a pacing timeline that traces your progress across the race distance. This gives you concrete numbers to write on a wristband, feed into a watch or share with a coach before race day.
For example you might average sixty kilometres per week at a comfortable training speed and run four sessions each week. The prediction then shows a marathon finish time with even splits that match that profile and makes it easier to spot goals that would need a clear change in training.
Predictions are most reliable for runners who log at least forty to forty five kilometres each week and whose training has been steady for roughly two months, and they can become optimistic or conservative at very low or very high workloads. Always treat the result as a starting point instead of a promise, and be especially cautious if you are new to running, returning from injury or managing health conditions. This tool provides informational estimates and does not substitute professional advice.
Marathon performance here is modelled from three training quantities measured over a recent eight week block. These are total weekly running distance, average speed on steady aerobic runs and the number of runs completed per week. Together they summarise how much you run, how hard you usually run and how often you train.
Internally the calculator follows the Tanda marathon performance model, treating weekly distance as the variable T, average training speed as V and weekly runs as R, all expressed in kilometre based units. The model outputs a baseline predicted finish time in minutes, which is then optionally scaled by a user defined percentage adjustment to reflect how aggressive or conservative you find the original formula.
From the adjusted finish time the tool derives average race speed in kilometres per hour and miles per hour, pace per kilometre and per mile, and an efficiency ratio comparing predicted race speed with your everyday training speed. It also distributes the race time across key checkpoints, assuming constant effort, so that you see cumulative times and segment paces for each marker.
The implementation applies calibration checks based on the original study. Weekly distance below about 40 km/week or above roughly 180 km/week, training speeds far from 8–15 km/h and marathon predictions faster than 140 minutes or slower than 330 minutes trigger warnings that the formula is being used outside its main evidence base. In such cases the numeric output still appears, but should be read with extra care.
| Symbol | Meaning | Unit/Datatype | Source |
|---|---|---|---|
| Weekly training distance | km/week | Input | |
| Average training speed | km/h | Input | |
| Runs per week | sessions/week | Input | |
|
|
Baseline Tanda marathon time | minutes | Derived |
| Adjustment percentage | percent | Input | |
|
|
Adjusted marathon time | minutes | Derived |
| Marathon race distance | 42.195 km | Constant | |
|
|
Average race speed | km/h, mph | Derived |
|
|
Average training speed | km/h, mph | Derived from input |
| Efficiency ratio vrace / vtrain | dimensionless | Derived |
As a worked example, consider a runner averaging 60 km/week, training at 10 km/h and running 4 sessions per week, with no manual adjustment. The baseline Tanda time is:
With zero adjustment this corresponds to an adjusted time of about 2 hours 44 minutes 56 seconds, from which the tool derives pace and splits for the full 42.195 km.
| Threshold band | Lower bound | Upper bound | Interpretation | Action cue |
|---|---|---|---|---|
| Weekly distance in range | 40 km/week | 180 km/week | Training volume similar to validation cohorts. | Use prediction as your main reference. |
| Weekly distance low | 0 km/week | 40 km/week | Below the volume used to build the model. | Expect times that may be optimistic. |
| Weekly distance high | 180 km/week | 300 km/week | Beyond the upper end of the study data. | Interpret prediction with caution. |
| Finish time in range | 140 min | 330 min | Within the main marathon performance band. | Suitable for most recreational planning. |
| Finish time very fast | 0 min | 140 min | Comparable to elite level performances. | Confirm with race history and caution. |
| Finish time very slow | 330 min | — | Slower than most calibration examples. | Use as a guide, not a strict target. |
Distances and speeds use base ten units, with kilometres and miles converted using 1 mile = 1.609344 km. Weekly distance and speed values are displayed with two decimal places using a dot as the decimal separator, while finish times, paces and splits are rounded to the nearest second. Chart labels compress times to hours and minutes for readability.
| Field | Type | Min | Max | Step/Pattern | Error text | Placeholder |
|---|---|---|---|---|---|---|
| Weekly distance | Number | 0 | 300 | 0.1, km or miles | Enter a weekly distance above zero to run the Tanda estimate. | 80 |
| Average training speed | Number | 0 | 30 | 0.1, km/h or mph | Average training speed must be greater than zero. | 10.5 |
| Runs per week | Number | 0 | 21 | Integer sessions | Set runs per week to at least 1 session. | 6 |
| Model adjustment | Number | -12 | 12 | Slider and numeric box | Clamped silently to the supported range. | 0 |
| Input | Accepted families | Output | Encoding/precision | Rounding |
|---|---|---|---|---|
| Training metrics | Numeric fields in km or miles, decimal dot | Finish time, paces, speeds | Two decimal places for distances and speeds | Nearest second for times |
| Summary table | Internal data rows | CSV or DOCX export | Quoted comma separated values, formatted document | Values as displayed in the table |
| Split checkpoints | Computed markers from 0–42.195 km | CSV or DOCX export | Distances in km and miles, H:MM:SS times | Nearest second per segment |
| Pacing timeline | Derived chart points | PNG, JPEG, WebP, CSV | Image data URLs and plain text CSV | Chart values rounded as above |
| JSON payload | Current inputs and derived metrics | Pretty printed JSON | Two space indentation, UTF-8 text | No extra rounding beyond model outputs |
The pacing timeline chart is built from the split table, adding an origin point at zero distance, and plotting cumulative race time against distance in kilometres or miles. Checkpoint markers, split times and distances in both unit systems are available in chart tooltips and in the downloadable CSV.
With fixed coefficients and deterministic rounding, identical inputs always produce the same finish time, paces and splits. A small debounce window reduces repeated recalculation while you edit values, but there is no long term caching of results.
The model structure follows the published Tanda marathon performance formula, which relates weekly distance, training speed and run frequency to finish time. Its calibration ranges reflect typical values for experienced marathon runners rather than novices. Assumptions about steady aerobic training and even pacing align with common distance running coaching guidelines.
Inputs are limited to training metrics and contain no direct identifiers, and the prediction logic runs entirely on the client without calling external data APIs. Generated CSV, document, image and JSON exports are created from the current page state for immediate download and are not stored by the script.
Turn your recent training into a clear marathon pacing plan by following these steps from raw distance and speed numbers to splits you can carry on race day.
As a concrete example, a runner averaging 60 km/week at about 10 km/h with four runs per week can enter those values, keep the adjustment at zero and immediately see a projected finish time with consistent splits across 5 km, 10 km, half marathon and beyond.
A helpful habit is to log both the raw prediction and any manual adjustment you apply so you can see how training changes shift the baseline over time.
Follow this flow each time you update your training numbers and you will build a consistent record of how training choices shape realistic marathon goals.
The calculator applies the Tanda marathon model, which combines weekly distance, average training speed and runs per week into a linear equation for finish time. That time is then scaled by any adjustment you set and converted into race pace, splits and speeds.
You need three training metrics measured over roughly eight weeks. These are your average weekly distance, your mean speed during steady aerobic runs and the number of times you run in a typical week. Without all three, the model cannot produce a meaningful result.
Accuracy depends on how closely your training matches the calibration data and how consistent your recent weeks have been. For runners logging around 40–180 km/week with stable training, predictions can fall close to actual marathon times. Outside those ranges or after breaks, treat the number as a rough guide only.
The script reads values from the page, performs calculations locally and prepares exports for immediate download. It does not send your training data to remote APIs, and there is no built in account, database or history feature. Any saving or sharing happens only through the files you choose to export. Avoid entering sensitive medical details alongside training metrics.
Yes. You can express weekly distance in kilometres or miles and training speed in kilometres per hour or miles per hour. Internally the model converts everything to kilometres using the standard 1.609344 km per mile factor and then converts back for display, so unit choices do not change the underlying prediction.
Each main panel offers copy and download buttons. From Race Summary and Checkpoint Splits you can copy data directly to the clipboard or download comma separated text and formatted documents. The Pacing Timeline panel exports chart images and a CSV of chart points, while the JSON tab lets you copy or save the full structured payload.
When your training values or predicted time sit near the edges of the calibration ranges, warnings appear above the results. These highlight that the model is extrapolating beyond the runners it was built from. In such cases you may want to apply a conservative manual adjustment or lean more on recent race performances.
Once the page and its supporting scripts have loaded, calculations, tables and exports run locally without further requests. If you open the tool while completely offline, some interactive pieces such as the chart may not initialise correctly. Keeping a cached copy on a device that has loaded it before improves the chance of smooth offline use.
The calculator itself contains no code for payments, logins or usage limits. Availability and any commercial terms are controlled by the site that embeds it. You are free to experiment with different training scenarios within the current session and export the resulting summaries for your personal planning or discussions with a coach.
If no prediction appears and there are also no visible error messages, reload the page completely before re entering your training metrics, as this usually indicates that a required script did not start correctly.