Running Calculations

A project containing functions to analyse a runners training data (from a specific run).

Getting Started

These instructions will get you a copy of the project up and running in your projects.

Prerequisites

There are no prerequisites required for this project,

Installing

running-calculations can be used in both node.js and in the browser.

Install running-calculations using npm:

npm install running-calculations

Usage

Using Running Calculations is incredibly simple. Examples of every function in use can be seen below:

 Types

Measurements

Enumeration of supported measurement types in this system

Possibilities

    measurements.miles
    measurments.kilometres

Coordinates

Typically used for an array of coordinates. Each object will have a longitude (lng) and latitude (lat) point.

Example

    import { coordinate } from 'running-calculations';
    const coordinatesArr:coordinate[] = [
        {
            lat: [latitude coordinate],
            lng: [longitude coordinate]
        }
    ]

Calculate Elevation

Converts elevation in metres to feet.

Example

    import { calculateElevation, measurements } from 'running-calculations';
    const elevation = calculateElevation(1, measurements.miles); // Answer will be 3.2808

Calculate running speed from 2 coordinates

Returns speed (in metres per second) from 2 coordinate types

    import { speedFromCoordinates, coordinates } from 'running-calculations';

    const coords1:coordinates = {lat: [latitude], lng: [longitude]};
    const coords2:coordinates = {lat: [latitude], lng: [longitude]};
    const speed = speedFromCoordinates(coords1, coords2);

Calculate running efficiency factor

Returns an efficiency factor from a running pace (ideally a graded pace) and a heart rate value. For comparison reasons, this would ideally be used for runs on the same course and conditions (time, weather, etc).

NOTE: Speed value is in metres per second.

    import { calculateEfficiencyFactor } from 'running-calculations';
    const runningPace = 4.76;
    const heartrate = 150;
    const speed = calculateEfficiencyFactor(runningPace, heartrate);

Convert distance from metres

Convert a distance in metres to either miles or kilometres

    import { convertDistance, measurements } from 'running-calculations';
    const distance = 1000;
    const speed = convertDistance(distance, measurements.miles);

Calculate a running pace

Converts running pace from metres per second to minute/miles or minute/kilometres

    import { calculateAveragePace, measurements } from 'running-calculations';
    const pace = 4.76;
    const speed = calculateAveragePace(pace, measurements.miles);

Calculate a running pace to m/s

Converts running pace from minute/miles or minute/kilometres to metres per second

    import { reverseAveragePace, measurements } from 'running-calculations';
    const pace = '6:18';
    const speed = reverseAveragePace(pace, measurements.miles);

Using FTP calculate training zones.

Uses functional threshold pace to calculate training zones for a runner to train in.

    import { calculateZonesFromFTP } from 'running-calculations';
    const pace = 4.76;
    const speed = calculateZonesFromFTP(pace);

Calculating percentage of VO2 MAX

Using the finish time for a race, calculate the % of VO2 Max. Calculation from the Jack Daniels Tables

    import { calculatePercentageVO2Max } from 'running-calculations';
    const raceTime = 5075; // 1:24:35 in seconds
    const VO2Max = calculatePercentageVO2Max(raceTime); // 86.4 %

Calculating VDot score from a race performance

Using the finish time for a race, calculate the VDot score of the race. Calculation from the Jack Daniels Tables

    import { calculateVDOT } from 'running-calculations';
    const raceTime = 5075; // 1:24:35 in seconds
    const VO2Max = calculateVDOT(raceTime); // 54.76 VDot Score

Calculating the training stress score of a run

Using funtional threshold pace, average pace (ideally a graded pace), and time (in seconds), calculate the training stress score of a run

    import { calculateTrainingStressScore, reverseAveragePace, measurements } from 'running-calculations';
    const ngp = reverseAveragePace('6:28', measurements.miles);
    const ftp = reverseAveragePace('6:18', measurements.miles);
    const time = 5075;

    calculateTrainingStressScore(ftp, ngp, time)) // 133.8

Calculating the chronic training load of a runner

Calculate the chronic training load of a runner using their their previous runs TSS over a 42 day period.

  import { calculateChronicTrainingLoad } from 'running-calculations';
  const tssData = [
      50.17, 37.07, 51.68,  68.96,
      61.05, 70.57, 91.11,  52.73,
      55.37, 43.79, 42.06,   2.02,
       7.19, 55.71, 45.72,  36.62,
      32.81, 32.56, 39.39, 114.48,
      10.05, 49.58, 84.34
    ];
  calculateChronicTrainingLoad(tssData) // 49.35

Calculating the acute training load of a runner

Calculate the acute training load of a runner using their their previous runs TSS over a 7 day period.

  import { calculateAcuteTrainingLoad } from 'running-calculations';
  const tssData = [50.17,37.07];
  calculateAcuteTrainingLoad(tssData) // 43.62

Calculating the training stress balance

Calculate the acute training load of a runner using their their previous runs TSS over a 7 day period.

  import { calculateChronicTrainingLoad, calculateAcuteTrainingLoad, calculateTrainingStressBalance } from 'running-calculations';
  const ctl = calculateChronicTrainingLoad(...);
  const atl = calculateAcuteTrainingLoad(...);

  calculateTrainingStressBalance(ctl, atl)) // 5.73

Calculating the chronic training load of a runner

Calculate the acute training load of a runner using their their previous runs TSS over a 7 day period.

  import { reverseAveragePace, calculateIntensityFactor } from 'running-calculations';
  const ngp = reverseAveragePace('6:28', measurements.miles);
  const ftp = reverseAveragePace('6:18', measurements.miles);

  calculateIntensityFactor(ftp, ngp) // 0.97

Running the tests

npm run test

Honourable mentions

The below greatly assisted in the research and authoring of the calculations provided in this package.

• Euadet Training Bot.
• Jack Daniels Tables.

Contributing

To contribute on this project, please contact mattncott.

Authors

• Matthew Nethercott - Initial work - mattncott

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE.md file for details