data-raw/strength_standards.R

In MarijnJABoer/befitteR: A bundle of health, fitness, food and body related equations, formula's and more, so you can become fit

bench_male <- tibble::tribble(
  ~ body_weight,
  ~ untrained,
  ~ novice,
  ~ intermediate,
  ~ advanced,
  ~ elite,
  "52",
  37.5,
  50,
  60,
  82.5,
  100,
  "56",
  40,
  52.5,
  62.5,
  90,
  110,
  "60",
  45,
  57.5,
  70,
  95,
  117.5,
  "67",
  50,
  65,
  77.5,
  107.5,
  132.5,
  "75",
  55,
  70,
  85,
  115,
  145,
  "82",
  60,
  75,
  90,
  125,
  157.5,
  "90",
  62.5,
  80,
  97.5,
  132.5,
  162.5,
  "100",
  62.5,
  82.5,
  102.5,
  137.5,
  172.5,
  "110",
  65,
  85,
  105,
  142.5,
  180,
  "125",
  67.5,
  87.5,
  107.5,
  147.5,
  185,
  "145",
  70,
  90,
  112.5,
  152.5,
  190,
  "145+",
  72.5,
  92.5,
  115,
  155,
  192.5
) %>%
  dplyr::mutate(exercise_name = "bench",
                sex = "male")

bench_female <- tibble::tribble(
  ~ body_weight,
  ~ untrained,
  ~ novice,
  ~ intermediate,
  ~ advanced,
  ~ elite,
  "44",
  22.5,
  30,
  35,
  42.5,
  52.5,
  "48",
  25,
  32.5,
  37.5,
  45,
  57.5,
  "52",
  27.5,
  35,
  37.5,
  50,
  62.5,
  "56",
  30,
  37.5,
  40,
  52.5,
  65,
  "60",
  32.5,
  40,
  42.5,
  57.5,
  67.5,
  "67",
  35,
  40,
  47.5,
  62.5,
  75,
  "75",
  37.5,
  42.5,
  52.5,
  65,
  85,
  "82",
  37.5,
  50,
  55,
  72.5,
  90,
  "90",
  40,
  52.5,
  60,
  75,
  95,
  "90+",
  42.5,
  55,
  62.5,
  80,
  100
) %>%
  dplyr::mutate(exercise_name = "bench",
                sex = "female")

deadlift_male <- tibble::tribble(
  ~ body_weight,
  ~ untrained,
  ~ novice,
  ~ intermediate,
  ~ advanced,
  ~ elite,
  "52",
  42.5,
  82.5,
  92.5,
  135,
  175,
  "56",
  47.5,
  87.5,
  100,
  145,
  187.5,
  "60",
  50,
  95,
  110,
  155,
  200,
  "67",
  57.5,
  107.5,
  122.5,
  172.5,
  217.5,
  "75",
  62.5,
  115,
  135,
  185,
  235,
  "82",
  67.5,
  125,
  142.5,
  200,
  250,
  "90",
  70,
  132.5,
  152.5,
  207.5,
  257.5,
  "100",
  75,
  137.5,
  160,
  217.5,
  265,
  "110",
  77.5,
  145,
  165,
  222.5,
  270,
  "125",
  80,
  147.5,
  170,
  227.5,
  272.5,
  "145",
  82.5,
  152.5,
  172.5,
  230,
  277.5,
  "145+",
  85,
  155,
  177.5,
  232.5,
  280
) %>%
  dplyr::mutate(exercise_name = "deadlift",
                sex = "male")

deadlift_female <- tibble::tribble(
  ~ body_weight,
  ~ untrained,
  ~ novice,
  ~ intermediate,
  ~ advanced,
  ~ elite,
  "44",
  25,
  47.5,
  50,
  80,
  105,
  "48",
  27.5,
  52.5,
  60,
  85,
  110,
  "52",
  30,
  55,
  62.5,
  90,
  115,
  "56",
  32.5,
  60,
  67.5,
  95,
  120,
  "60",
  35,
  62.5,
  72.5,
  100,
  125,
  "67",
  37.5,
  67.5,
  80,
  110,
  135,
  "75",
  40,
  72.5,
  85,
  117.5,
  145,
  "82",
  42.5,
  80,
  92.5,
  125,
  150,
  "90",
  45,
  87.5,
  97.5,
  130,
  160,
  "90+",
  50,
  90,
  105,
  137.5,
  165
) %>%
  dplyr::mutate(exercise_name = "deadlift",
                sex = "female")

ohp_male <- tibble::tribble(
  ~ body_weight,
  ~ untrained,
  ~ novice,
  ~ intermediate,
  ~ advanced,
  ~ elite,
  "52",
  22.5,
  32.5,
  40,
  50,
  60,
  "56",
  25,
  35,
  45,
  52.5,
  65,
  "60",
  27.5,
  37.5,
  47.5,
  57.5,
  70,
  "67",
  30,
  42.5,
  55,
  62.5,
  77.5,
  "75",
  32.5,
  45,
  57.5,
  70,
  85,
  "82",
  35,
  50,
  62.5,
  75,
  100,
  "90",
  37.5,
  52.5,
  65,
  77.5,
  105,
  "100",
  40,
  55,
  70,
  82.5,
  115,
  "110",
  42.5,
  57.5,
  72.5,
  85,
  120,
  "125",
  42.5,
  60,
  75,
  87.5,
  122.5,
  "145",
  45,
  60,
  75,
  90,
  125,
  "145+",
  45,
  62.5,
  77.5,
  92.5,
  130
) %>%
  dplyr::mutate(exercise_name = "ohp",
                sex = "male")

ohp_female <- tibble::tribble(
  ~ body_weight,
  ~ untrained,
  ~ novice,
  ~ intermediate,
  ~ advanced,
  ~ elite,
  "44",
  15,
  17.5,
  22.5,
  30,
  40,
  "48",
  15,
  20,
  25,
  32.5,
  42.5,
  "52",
  17.5,
  22.5,
  27.5,
  35,
  45,
  "56",
  17.5,
  22.5,
  27.5,
  37.5,
  47.5,
  "60",
  17.5,
  25,
  30,
  40,
  50,
  "67",
  20,
  27.5,
  32.5,
  42.5,
  55,
  "75",
  22.5,
  30,
  35,
  47.5,
  62.5,
  "82",
  22.5,
  32.5,
  37.5,
  50,
  65,
  "90",
  25,
  35,
  40,
  52.5,
  67.5,
  "90+",
  27.5,
  37.5,
  42.5,
  57.5,
  72.5
) %>%
  dplyr::mutate(exercise_name = "ohp",
                sex = "female")

squat_male <- tibble::tribble(
  ~ body_weight,
  ~ untrained,
  ~ novice,
  ~ intermediate,
  ~ advanced,
  ~ elite,
  "52",
  35,
  65,
  80,
  107.5,
  145,
  "56",
  37.5,
  70,
  87.5,
  117.5,
  157.5,
  "60",
  40,
  77.5,
  92.5,
  127.5,
  167.5,
  "67",
  45,
  85,
  105,
  142.5,
  185,
  "75",
  50,
  92.5,
  112.5,
  155,
  202.5,
  "82",
  55,
  100,
  122.5,
  167.5,
  217.5,
  "90",
  57.5,
  105,
  130,
  177.5,
  230,
  "100",
  60,
  110,
  135,
  185,
  240,
  "110",
  62.5,
  115,
  140,
  192.5,
  250,
  "125",
  65,
  117.5,
  145,
  197.5,
  257.5,
  "145",
  67.5,
  122.5,
  147.5,
  202.5,
  262.5,
  "145+",
  70,
  125,
  150,
  207.5,
  270
) %>%
  dplyr::mutate(exercise_name = "squat",
                sex = "male")

squat_female <- tibble::tribble(
  ~ body_weight,
  ~ untrained,
  ~ novice,
  ~ intermediate,
  ~ advanced,
  ~ elite,
  "44",
  20,
  37.5,
  45,
  60,
  75,
  "48",
  22.5,
  40,
  47.5,
  65,
  80,
  "52",
  25,
  45,
  52.5,
  67.5,
  87.5,
  "56",
  25,
  47.5,
  55,
  72.5,
  90,
  "60",
  27.5,
  50,
  60,
  77.5,
  95,
  "67",
  30,
  55,
  62.5,
  85,
  105,
  "75",
  32.5,
  57.5,
  67.5,
  90,
  115,
  "82",
  35,
  62.5,
  75,
  97.5,
  122.5,
  "90",
  37.5,
  67.5,
  80,
  105,
  132.5,
  "90+",
  40,
  72.5,
  85,
  110,
  137.5
) %>%
  dplyr::mutate(exercise_name = "squat",
                sex = "female") %>%
  # remove `+` from some body_weight rows.`
  dplyr::mutate(body_weight = gsub("[^0-9.-]", "", body_weight))

standards <-
  dplyr::bind_rows(
    bench_male,
    bench_female,
    deadlift_male,
    deadlift_female,
    ohp_male,
    ohp_female,
    squat_male,
    squat_female
  ) %>%
  tidyr::pivot_longer(
    cols = c(untrained, novice, intermediate, advanced, elite),
    names_to = "level",
    values_to = "lift_weight"
  )

use_data(standards, overwrite = TRUE)