278 lines
11 KiB
Markdown
278 lines
11 KiB
Markdown
# Wattage predictions
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See:
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* [concept2_prediction.py](concept2_prediction.py)
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* [concept2_prediction.js](concept2_prediction.js)
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## Zones
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See:
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* Indoor Rowing Training Guide, Version 2 by Terry O’Neill and Alex Skelton.
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* [Interactive_Training_Plans.xlsx](Interact_Training_Plans.xlsx)
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Heart rate zones are calculated based on HRR calculated from:
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Resting heart rate (RHR) 58
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Maximum heart rate (MHR) 165
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Heart rate reserve (HRR) (MHR minus RHR) 107
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| Training Band | s.min-1 | %HRR | %2k (W) | range |
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|------------------------------|---------|--------|---------------|-------|
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| Oxygen Utilisation 2 (UT2) | 16-20 | 65-70 | 45-60 | 15% |
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| Oxygen Utilisation 1 (UT1) | 20-24 | 70-80 | 60-70 | 10% |
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| Anaerobic Threshold (AT) | 24-28 | 80-85 | 70-80 | 10% |
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| VO2 Max/Transport (TR) | 28-32 | 85-95 | 80-105 | 25% |
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| Peak Power/Anaerobic (AN) | 32+ | 95-100 | 105-115 | 10% |
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*s.min-1 is scientific notation for strokes/minute
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**%2k (w) is the % of power output, measured in watts of a 2000m test – from
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this it is possible to calculate pace (time/500m)
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***HRR% is Heart Rate Reserve %. When resting and maximum heart rates are know
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it is possible to calculate the heart rate at which one should train to have
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the most appropriate effect on the body’s systems.
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## Example 1
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### Heart rate 132 for 110W after 10 minutes
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UT2 is 65%-70%, so 128-133 bpm.
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132 is 4 (132 minus 128) into UT2 range of 5 (133 minus 128)
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UT2 power is 45%-60% of max 2k power.
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UT2 power range is 15% (60% minus 45%)
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so 132 bmp should be 4 fifths into that 15% = 12%
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so expected power is 110W/(45%+12%) = 193W
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## Example 2
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### Take the result of example 1 and a zone and provide a suitable training session
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Given zone: UT2 is midpoint of range:
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0.5*(45+60) = 52.5% of 192W = 101.3W
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Given zone: AT:
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0.5*(70+80) = 75% of 193W = 144.7W
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## Examples 3
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### Return a training zone from a [training table](Interactive_Training_Plans.xlsx)
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See: [parse_ITP_spreadsheet.py](parse_ITP_spreadsheet.py) for a pandas
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dataframe parsing and querying the spreadsheet.
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Given a level 1-5, a session number and a week number return the associated
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session eg 3x16'UT1
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#### Available Levels
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Level 1 | 3 Sessions | 26 Weeks
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Level 2 | 3 Sessions | 26 Weeks
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Level 2 | 4 Sessions | 26 Weeks
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Level 3 | 4 Sessions | 26 Weeks
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Level 4 | 4 Sessions | 26 Weeks
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Level 4 | 5 Sessions | 26 Weeks
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Level 4 | 6 Sessions | 26 Weeks
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Level 5 | 6 Sessions | 26 Weeks
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Level 5 | 7 Sessions | 26 Weeks
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Level 5 | 8 Sessions | 26 Weeks
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cat level-1_3-session_26-weeks.csv
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```csv
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"Interactive 2,000m Programme",,,
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2000m 26 Week Training Programme,,,
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"Athlete Level 1, 3 Sessions a Week",,,
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Week,Session 1,Session 2,Session 3
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1,TEST,12'UT2,15'UT2
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2,14'UT2,16'UT2,18'UT2
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3,17'UT2,19'UT2,20'UT2
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4,10'UT1,25'UT2,30'UT2
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5,12'UT1,18'UT1,8'AT
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6,30'UT2,2x10'UT1,2x7'AT
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7,15'UT1,20'UT2,7'AT
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8,18'UT1,25UT2,9'AT
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9,4x2'TR,30'UT2,2X12'UT1
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10,2x2'TR,15'UT1,20'UT2
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11,4x2'TR,18'UT1,25'UT2
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12,6x2'TR,2X12'UT1,30'UT2
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13,TEST,2x3'TR,2x7'AT
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14,4x2'TR,16'UT1,25'UT2
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15,2x4'TR,2x12'UT1,3x7'AT
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16,6x2'TR,2x8'UT1,20'UT2
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17,2x9'AT,18'UT1,30'UT2
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18,2x10'AT,3x2'TR,20'UT1
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19,4x1.5'AN,2x12UT1,2x8'AT
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20,3x2'TR,25'UT1,2x9'AT
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21,2x4'TR,30'UT2,2x10'AT
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22,2x4'TR,15'UT1,2x7'AT
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23,30'UT2,18'UT1,2x9'AT
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24,3x2'TR,30'UT2,2x12'UT1
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25,5x2'TR,6x1.5'AN,3x3'TR
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26,2x1.5'AN,3x45s AN,RACE
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```
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Interactive 2,000m Programme
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2000m 26 Week Training Programme
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Athlete Level 5, 8 Sessions a Week
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| Week | Session 1 | Session 2 | Session 3 | Session 4 | Session 5 | Session 6 | Session 7 | Session 8 |
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|------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
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| 1 | TEST | 2x15'UT1 | 55'UT2 | 2x18'UT1 | 68'UT2 | 3x15'UT1 | 55'UT2 | 2x15'UT1 |
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| 2 | 65'UT2 | 2x21'UT1 | 72'UT2 | 3x16'UT1 | 80'UT2 | 4x13'UT1 | 72'UT2 | 3x12'UT1 |
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| 3 | 76'UT2 | 3x17'UT1 | 85'UT2 | 3x19'UT1 | 90'UT2 | 3x20'UT1 | 85'UT2 | 2x25'UT1 |
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| 4 | 45'UT2 | 2x15'UT1 | 2x6'AT | 3x12'UT1 | 2x7'AT | 3x15'UT1 | 2x10'AT | 3x12'UT2 |
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| 5 | 65'UT2 | 2x24'UT1 | 4x5'AT | 3x16'UT1 | 3x8'AT | 3x18'UT1 | 2x12'AT | 3x16'UT1 |
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| 6 | 76'UT2 | 2x25'UT1 | 3x7'AT | 3x19'UT1 | 3x10'AT | 5x12'UT1 | 3x8'AT | 3x18'UT1 |
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| 7 | 45'UT2 | 2x15'UT1 | 2x8'AT | 3x12'UT1 | 2x10'AT | 3x15'UT1 | 2x9'AT | 2x3'TR |
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| 8 | 65'UT2 | 3x14'UT1 | 2x9'AT | 75'UT2 | 2x8' AT | 4x14'UT1 | 2x7'AT | 3x4'TR |
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| 9 | 76'UT2 | 3x17'UT1 | 3x7'AT | 90'UT2 | 4x5'TR | 4X15'UT1 | 3x8'AT | 4x4'TR |
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| 10 | 45'UT2 | 2x15'UT1 | 2x8'AT | 60'UT2 | 4x2'TR | 3x12'UT1 | 2x9'AT | 3x3'TR |
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| 11 | 65'UT2 | 3x15'UT1 | 2x10'AT | 75'UT2 | 4x3'TR | 3x15'UT1 | 2x10'AT | 4x3'TR |
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| 12 | 75'UT2 | 4x15'UT1 | 3x8'AT | 90'UT2 | 4x4'TR | 4x12'UT1 | 3x10'AT | 5x4'TR |
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| 13 | TEST | 2X15'UT1 | 2x8'AT | 60'UT2 | 3x1'AN | 3x15'UT1 | 2x8'AT | 4x2'TR |
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| 14 | 65'UT2 | 3X15'UT1 | 2x10'AT | 75'UT2 | 4x1.5'AN | 4x12'UT1 | 3x7'AT | 6x2'TR |
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| 15 | 75'UT2 | 5x12'UT1 | 3x10'AT | 90'UT2 | 6x1'AN | 5x12'UT1 | 3x10'AT | 6x4'TR |
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| 16 | 45'UT2 | 2X15'UT1 | 2x9'AT | 60'UT2 | 8x45sAN | 4x14'UT1 | 2x10'AT | 5x2'TR |
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| 17 | 65'UT2 | 3X15'UT1 | 3x10'AT | 75'UT2 | 6x1.5'AN | 3x12'UT1 | 3x8'AT | 6x3'TR |
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| 18 | 75'UT2 | 4x15'UT1 | 4x8'AT | 90'UT2 | 8x1'AN | 2x15'UT1 | 4x9'AT | 7x4'TR |
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| 19 | 45'UT2 | 2X15'UT1 | 2x10'AT | 60'UT2 | 4x1.5'AN | 3x12'UT1 | 3x8'AT | 6x2'TR |
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| 20 | 65'UT2 | 3X15'UT1 | 3x12'AT | 75'UT2 | 6x1'AN | 3x15'UT1 | 3x10'AT | 7x3'TR |
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| 21 | 75'UT2 | 5x12'UT1 | 5x8'AT | 90'UT2 | 8x45sAN | 5x12'UT1 | 4x10'AT | 8x4'TR |
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| 22 | 45'UT2 | 2x15'UT1 | 2x10'AT | 60'UT2 | 8x1.5'AN | 3x12'UT1 | 2x7'AT | 4x2'TR |
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| 23 | 65'UT2 | 3x15'UT1 | 3x8'AT | 75'UT2 | 10x45sAN | 3x15'UT1 | 3x7'AT | 4x3'TR |
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| 24 | 76'UT2 | 4x15'UT1 | 4x8'AT | 90'UT2 | 2(6x1')AN | 4x15'UT1 | 2x10'AT | 4x4'TR |
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| 25 | 50'UT2 | 2x12'UT1 | 6' AT | 40'UT2 | 2x1.5'AN | 20'UT2 | 2x2'TR | 3x45sAN |
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| 26 | OFF | 1x15'UT1 | 5'AT | 1x3'TR | 20'UT2 | 2x2'TR | 3x45sAN | RACE |
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cat level-5_8-session_26-weeks.csv
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```csv
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"Interactive 2,000m Programme",,,,,,,,
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2000m 26 Week Training Programme,,,,,,,,
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"Athlete Level 5, 8 Sessions a Week",,,,,,,,
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Week,Session 1,Session 2,Session 3,Session 4,Session 5,Session 6,Session 7,Session 8
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1,TEST,2x15'UT1,55'UT2,2x18'UT1,68'UT2,3x15'UT1,55'UT2,2x15'UT1
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2,65'UT2,2x21'UT1,72'UT2,3x16'UT1,80'UT2,4x13'UT1,72'UT2,3x12'UT1
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3,76'UT2,3x17'UT1,85'UT2,3x19'UT1,90'UT2,3x20'UT1,85'UT2,2x25'UT1
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4,45'UT2,2x15'UT1,2x6'AT,3x12'UT1,2x7'AT,3x15'UT1,2x10'AT,3x12'UT2
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5,65'UT2,2x24'UT1,4x5'AT,3x16'UT1,3x8'AT,3x18'UT1,2x12'AT,3x16'UT1
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6,76'UT2,2x25'UT1,3x7'AT,3x19'UT1,3x10'AT,5x12'UT1,3x8'AT,3x18'UT1
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7,45'UT2,2x15'UT1,2x8'AT,3x12'UT1,2x10'AT,3x15'UT1,2x9'AT,2x3'TR
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8,65'UT2,3x14'UT1,2x9'AT,75'UT2,2x8' AT,4x14'UT1,2x7'AT,3x4'TR
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9,76'UT2,3x17'UT1,3x7'AT,90'UT2,4x5'TR,4X15'UT1,3x8'AT,4x4'TR
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10,45'UT2,2x15'UT1,2x8'AT,60'UT2,4x2'TR,3x12'UT1,2x9'AT,3x3'TR
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11,65'UT2,3x15'UT1,2x10'AT,75'UT2,4x3'TR,3x15'UT1,2x10'AT,4x3'TR
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12,75'UT2,4x15'UT1,3x8'AT,90'UT2,4x4'TR,4x12'UT1,3x10'AT,5x4'TR
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13,TEST,2X15'UT1,2x8'AT,60'UT2,3x1'AN,3x15'UT1,2x8'AT,4x2'TR
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14,65'UT2,3X15'UT1,2x10'AT,75'UT2,4x1.5'AN,4x12'UT1,3x7'AT,6x2'TR
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15,75'UT2,5x12'UT1,3x10'AT,90'UT2,6x1'AN,5x12'UT1,3x10'AT,6x4'TR
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16,45'UT2,2X15'UT1,2x9'AT,60'UT2,8x45sAN,4x14'UT1,2x10'AT,5x2'TR
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17,65'UT2,3X15'UT1,3x10'AT,75'UT2,6x1.5'AN,3x12'UT1,3x8'AT,6x3'TR
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18,75'UT2,4x15'UT1,4x8'AT,90'UT2,8x1'AN,2x15'UT1,4x9'AT,7x4'TR
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19,45'UT2,2X15'UT1,2x10'AT,60'UT2,4x1.5'AN,3x12'UT1,3x8'AT,6x2'TR
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20,65'UT2,3X15'UT1,3x12'AT,75'UT2,6x1'AN,3x15'UT1,3x10'AT,7x3'TR
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21,75'UT2,5x12'UT1,5x8'AT,90'UT2,8x45sAN,5x12'UT1,4x10'AT,8X4'TR
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22,45'UT2,2x15'UT1,2x10'AT,60'UT2,8x1.5'AN,3x12'UT1,2x7'AT,4x2'TR
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23,65'UT2,3x15'UT1,3x8'AT,75'UT2,10x45sAN,3x15'UT1,3x7'AT,4x3'TR
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24,76'UT2,4x15'UT1,4x8'AT,90'UT2,2(6x1')AN,4x15'UT1,2x10'AT,4x4'TR
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25,50'UT2,2x12'UT1,6' AT,40'UT2,2x1.5'AN,2x15'UT1,4'TR,2x12'UT1
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26,OFF,1x15'UT1,5'AT,1x3'TR,20'UT2,2x2'TR,3x45sAN,RACE
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```
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cat concept2_prediction.py
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```python
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def calculate_wattage(resting_heart_rate, maximum_heart_rate, heart_rate, base_power_output):
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def get_zone_percentile(heart_rate, resting_heart_rate, maximum_heart_rate):
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HRR = maximum_heart_rate - resting_heart_rate
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zone = ((heart_rate - resting_heart_rate) / HRR) * 100
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return round(zone, 2)
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def get_hrr_range(zone):
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if zone <= 65:
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return (0, 65)
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elif zone <= 70:
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print("UT2 Zone")
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return (65, 70)
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elif zone <= 80:
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print("UT1 Zone")
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return (70, 80)
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elif zone <= 85:
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print("AT Zone")
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return (80, 85)
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elif zone <= 95:
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print("TR Zone")
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return (85, 95)
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else:
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print("AN Zone")
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return (95, 100)
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def get_power_range(zone):
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if zone <= 65:
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return (0, 45)
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elif zone <= 70:
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print("UT2 Zone")
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return (45, 60)
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elif zone <= 80:
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print("UT1 Zone")
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return (60, 70)
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elif zone <= 85:
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print("AT Zone")
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return (70, 80)
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elif zone <= 95:
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print("TR Zone")
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return (80, 105)
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else:
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print("AN Zone")
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return (105, 115)
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zone_percentage = get_zone_percentile(heart_rate, resting_heart_rate, maximum_heart_rate)
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print("Zone: " + str(zone_percentage))
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min_power, max_power = get_power_range(zone_percentage)
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print("Min power: " + str(min_power))
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print("Max power: " + str(max_power))
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min_hrr, max_hrr = get_hrr_range(zone_percentage)
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print("Min hrr: " + str(min_hrr))
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print("Max hrr: " + str(max_hrr))
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power_range = max_power - min_power
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print("Power range: " + str(power_range))
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hrr_range = max_hrr - min_hrr
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print("HRR range: " + str(hrr_range))
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print("Zone minus min hrr: " + str(zone_percentage - min_hrr))
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# Calculate percentage of hrr range
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hrr_percentage = ((zone_percentage - min_hrr) / hrr_range)
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print("hrr %: " + str(hrr_percentage))
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power_percentage = (min_power + hrr_percentage * power_range) / 100
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print("Power percentage: " + str(power_percentage))
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# Add base power output
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# predicted_power = power_percentage + base_power_output
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predicted_power = base_power_output / power_percentage
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return round(predicted_power, 0)
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# Example usage
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resting_heart_rate = 58
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maximum_heart_rate = 165
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heart_rate = 132
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base_power_output = 110
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watts = calculate_wattage(resting_heart_rate, maximum_heart_rate, heart_rate, base_power_output)
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print(f"Predicted power: {watts} watts")
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``` |