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Predicting maximal strength
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<iframe 
    src="http://jsxgraph.org/share/iframe/predicting-maximal-strength" 
    style="border: 1px solid black; overflow: hidden; width: 550px; aspect-ratio: 55 / 65;" 
    name="JSXGraph example: Predicting maximal strength" 
    allowfullscreen
></iframe>
This code has to 
<div id="board-0-wrapper" class="jxgbox-wrapper " style="width: 100%; ">
   <div id="board-0" class="jxgbox" style="aspect-ratio: 1 / 1; width: 100%;" data-ar="1 / 1"></div>
</div>

<script type = "text/javascript"> 
    /*
    This example is licensed under a 
    Creative Commons Attribution ShareAlike 4.0 International License.
    https://creativecommons.org/licenses/by-sa/4.0/
    
    Please note you have to mention 
    The Center of Mobile Learning with Digital Technology
    in the credits.
    */
    
    const BOARDID = 'board-0';

    var board = JXG.JSXGraph.initBoard(BOARDID, { boundingbox: [-1, 1.8, 30, 0.8], axis: true });
    
    var w = board.create('slider', [[24, 0.92], [24, 1.7], [0, 50, 200]], { name: 'weight w', snapWidth: 1 });
    
    var f = function(x) { return (0.988 + 0.0104 * x + 0.00190 * x * x - 0.0000584 * x * x * x); };
    
    var c = board.create('functiongraph', [
                 f,
                 1, 22
                 ], { strokeColor: 'black', highlightStrokeColor: 'black' });
    
    var r = board.create('glider', [10, 1, c], { name: '', fillColor: 'black', strokeColor: 'black', style: 6 });
    var t = board.create('text', [function() { return r.X() + 1; },
                                      function() { return r.Y(); },
                                      function() { return "repetitions r = " + Math.floor(r.X()); }]);
    
    board.create('text', [5, 1.6,
                       function() { return "predicted 1RM = " + (w.Value() * f(Math.floor(r.X()))).toFixed(2); }
        ], { fontSize: 24, strokeColor: 'red' });
 </script> 
/*
This example is licensed under a 
Creative Commons Attribution ShareAlike 4.0 International License.
https://creativecommons.org/licenses/by-sa/4.0/

Please note you have to mention 
The Center of Mobile Learning with Digital Technology
in the credits.
*/

const BOARDID = 'your_div_id'; // Insert your id here!

var board = JXG.JSXGraph.initBoard(BOARDID, { boundingbox: [-1, 1.8, 30, 0.8], axis: true });

var w = board.create('slider', [[24, 0.92], [24, 1.7], [0, 50, 200]], { name: 'weight w', snapWidth: 1 });

var f = function(x) { return (0.988 + 0.0104 * x + 0.00190 * x * x - 0.0000584 * x * x * x); };

var c = board.create('functiongraph', [
             f,
             1, 22
             ], { strokeColor: 'black', highlightStrokeColor: 'black' });

var r = board.create('glider', [10, 1, c], { name: '', fillColor: 'black', strokeColor: 'black', style: 6 });
var t = board.create('text', [function() { return r.X() + 1; },
                                  function() { return r.Y(); },
                                  function() { return "repetitions r = " + Math.floor(r.X()); }]);

board.create('text', [5, 1.6,
                   function() { return "predicted 1RM = " + (w.Value() * f(Math.floor(r.X()))).toFixed(2); }
    ], { fontSize: 24, strokeColor: 'red' });
<jsxgraph width="100%" aspect-ratio="1 / 1" title="Predicting maximal strength" description="This construction was copied from JSXGraph examples database: BTW HERE SHOULD BE A GENERATED LINKuseGlobalJS="false">
   /*
   This example is licensed under a 
   Creative Commons Attribution ShareAlike 4.0 International License.
   https://creativecommons.org/licenses/by-sa/4.0/
   
   Please note you have to mention 
   The Center of Mobile Learning with Digital Technology
   in the credits.
   */
   
   var board = JXG.JSXGraph.initBoard(BOARDID, { boundingbox: [-1, 1.8, 30, 0.8], axis: true });
   
   var w = board.create('slider', [[24, 0.92], [24, 1.7], [0, 50, 200]], { name: 'weight w', snapWidth: 1 });
   
   var f = function(x) { return (0.988 + 0.0104 * x + 0.00190 * x * x - 0.0000584 * x * x * x); };
   
   var c = board.create('functiongraph', [
                f,
                1, 22
                ], { strokeColor: 'black', highlightStrokeColor: 'black' });
   
   var r = board.create('glider', [10, 1, c], { name: '', fillColor: 'black', strokeColor: 'black', style: 6 });
   var t = board.create('text', [function() { return r.X() + 1; },
                                     function() { return r.Y(); },
                                     function() { return "repetitions r = " + Math.floor(r.X()); }]);
   
   board.create('text', [5, 1.6,
                      function() { return "predicted 1RM = " + (w.Value() * f(Math.floor(r.X()))).toFixed(2); }
       ], { fontSize: 24, strokeColor: 'red' });
</jsxgraph>
This little application tries to predict the *maximal strength* (1RM) based on a *repetitions to fatigue* (RTF) value. The calculation is based on the so-called *KLW formula*: $$ 1RM = w \cdot \left(0.988 + 0.0104 \cdot x + 0.00190 \cdot x^2 - 0.0000584 \cdot x^3\right) $$ The horizontal axis denotes the number of repetitions, the vertical axis denotes the ratio 1RM/RTF. **How to use this graphical calculator?** Suppose you managed to do 9 repetitions with a weight of 80 kilograms. In the graphical calculator below you have to drag the black dot to r = 9 and the blue dot to weight = 80. Now, you can read off the 1RM prediction of 95.43. 
// Define the id of your board in BOARDID

var board = JXG.JSXGraph.initBoard(BOARDID, { boundingbox: [-1, 1.8, 30, 0.8], axis: true });

var w = board.create('slider', [[24, 0.92], [24, 1.7], [0, 50, 200]], { name: 'weight w', snapWidth: 1 });

var f = function(x) { return (0.988 + 0.0104 * x + 0.00190 * x * x - 0.0000584 * x * x * x); };

var c = board.create('functiongraph', [
             f,
             1, 22
             ], { strokeColor: 'black', highlightStrokeColor: 'black' });

var r = board.create('glider', [10, 1, c], { name: '', fillColor: 'black', strokeColor: 'black', style: 6 });
var t = board.create('text', [function() { return r.X() + 1; },
                                  function() { return r.Y(); },
                                  function() { return "repetitions r = " + Math.floor(r.X()); }]);

board.create('text', [5, 1.6,
                   function() { return "predicted 1RM = " + (w.Value() * f(Math.floor(r.X()))).toFixed(2); }
    ], { fontSize: 24, strokeColor: 'red' });

license

This example is licensed under a Creative Commons Attribution ShareAlike 4.0 International License.
Please note you have to mention The Center of Mobile Learning with Digital Technology in the credits.