This function create simple example using progression_table
Arguments
- progression_table
Progression table function
- reps
Numeric vector. Default is
c(3, 5, 10)- volume
Character vector. Default is
c("intensive", "normal", "extensive")- type
Character vector. Type of max rep table. Options are grinding (Default) and ballistic
- ...
Extra arguments forwarded to
progression_table
Value
Data frame with the following structure
- type
Type of the set and rep scheme
- reps
Number of reps performed
- volume
Volume type of the set and rep scheme
- Step 1
First progression step %1RM
- Step 2
Second progression step %1RM
- Step 3
Third progression step %1RM
- Step 4
Fourth progression step %1RM
- Step 2-1 Diff
Difference in %1RM between second and first progression step
- Step 3-2 Diff
Difference in %1RM between third and second progression step
- Step 4-3 Diff
Difference in %1RM between fourth and third progression step
Examples
create_example(progression_RIR)
#> # A tibble: 18 × 10
#> type reps volume `Step 1` `Step 2` `Step 3` `Step 4` `Step 2-1 Diff`
#> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 grinding 3 intensive 83.3 85.7 88.2 90.9 2.38
#> 2 grinding 3 normal 81.1 83.3 85.7 88.2 2.25
#> 3 grinding 3 extensive 79.0 81.1 83.3 85.7 2.13
#> 4 grinding 5 intensive 79.0 81.1 83.3 85.7 2.13
#> 5 grinding 5 normal 76.9 79.0 81.1 83.3 2.02
#> 6 grinding 5 extensive 75.0 76.9 79.0 81.1 1.92
#> 7 grinding 10 intensive 69.8 71.4 73.2 75.0 1.66
#> 8 grinding 10 normal 68.2 69.8 71.4 73.2 1.59
#> 9 grinding 10 extensive 66.7 68.2 69.8 71.4 1.51
#> 10 ballistic 3 intensive 71.4 75.0 79.0 83.3 3.57
#> 11 ballistic 3 normal 68.2 71.4 75.0 79.0 3.25
#> 12 ballistic 3 extensive 65.2 68.2 71.4 75.0 2.96
#> 13 ballistic 5 intensive 65.2 68.2 71.4 75.0 2.96
#> 14 ballistic 5 normal 62.5 65.2 68.2 71.4 2.72
#> 15 ballistic 5 extensive 60.0 62.5 65.2 68.2 2.50
#> 16 ballistic 10 intensive 53.6 55.6 57.7 60.0 1.98
#> 17 ballistic 10 normal 51.7 53.6 55.6 57.7 1.85
#> 18 ballistic 10 extensive 50.0 51.7 53.6 55.6 1.72
#> # ℹ 2 more variables: `Step 3-2 Diff` <dbl>, `Step 4-3 Diff` <dbl>
# Create example using specific reps-max table and k value
create_example(
progression_RIR,
max_perc_1RM_func = max_perc_1RM_modified_epley,
kmod = 0.0388
)
#> # A tibble: 18 × 10
#> type reps volume `Step 1` `Step 2` `Step 3` `Step 4` `Step 2-1 Diff`
#> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 grinding 3 intensive 83.8 86.6 89.6 92.8 2.81
#> 2 grinding 3 normal 81.1 83.8 86.6 89.6 2.64
#> 3 grinding 3 extensive 78.6 81.1 83.8 86.6 2.48
#> 4 grinding 5 intensive 78.6 81.1 83.8 86.6 2.48
#> 5 grinding 5 normal 76.3 78.6 81.1 83.8 2.33
#> 6 grinding 5 extensive 74.1 76.3 78.6 81.1 2.19
#> 7 grinding 10 intensive 68.2 70.1 72.0 74.1 1.86
#> 8 grinding 10 normal 66.5 68.2 70.1 72.0 1.76
#> 9 grinding 10 extensive 64.8 66.5 68.2 70.1 1.67
#> 10 ballistic 3 intensive 70.1 74.1 78.6 83.8 4.03
#> 11 ballistic 3 normal 66.5 70.1 74.1 78.6 3.62
#> 12 ballistic 3 extensive 63.2 66.5 70.1 74.1 3.26
#> 13 ballistic 5 intensive 63.2 66.5 70.1 74.1 3.26
#> 14 ballistic 5 normal 60.3 63.2 66.5 70.1 2.96
#> 15 ballistic 5 extensive 57.6 60.3 63.2 66.5 2.69
#> 16 ballistic 10 intensive 50.8 52.8 55.1 57.6 2.08
#> 17 ballistic 10 normal 48.8 50.8 52.8 55.1 1.92
#> 18 ballistic 10 extensive 47.1 48.8 50.8 52.8 1.78
#> # ℹ 2 more variables: `Step 3-2 Diff` <dbl>, `Step 4-3 Diff` <dbl>