Family of functions to adjust number of repetition

These functions are reverse version of the adj_perc_1RM family of functions. Use these when you want to estimate number of repetitions to be used when using the known %1RM and level of adjustment

Usage

adj_reps_RIR(
  perc_1RM,
  adjustment = 0,
  mfactor = 1,
  max_reps_func = max_reps_epley,
  ...
)

adj_reps_DI(
  perc_1RM,
  adjustment = 1,
  mfactor = 1,
  max_reps_func = max_reps_epley,
  ...
)

adj_reps_rel_int(
  perc_1RM,
  adjustment = 1,
  mfactor = 1,
  max_reps_func = max_reps_epley,
  ...
)

adj_reps_perc_MR(
  perc_1RM,
  adjustment = 1,
  mfactor = 1,
  max_reps_func = max_reps_epley,
  ...
)

Arguments

perc_1RM: Numeric vector. %1RM used (use 0.5 for 50%, 0.9 for 90%)
adjustment: Numeric vector. Adjustment to be implemented
mfactor: Numeric vector. Default is 1 (i.e., no adjustment). Use mfactor = 2 to generate ballistic adjustment and tables
max_reps_func: Max reps function to be used. Default is max_reps_epley
...: Forwarded to max_reps_func. Usually the parameter value. For example klin = 36 when using max_reps_linear as max_reps_func function

Value

Numeric vector. Predicted number of repetitions to be performed

Functions

adj_reps_RIR(): Adjust number of repetitions using the Reps In Reserve (RIR) approach
adj_reps_DI(): Adjust number of repetitions using the Deducted Intensity (DI) approach
adj_reps_rel_int(): Adjust number of repetitions using the Relative Intensity (RelInt) approach
adj_reps_perc_MR(): Adjust number of repetitions using the % max reps (%MR) approach

Examples

# ------------------------------------------
# Adjustment using Reps In Reserve (RIR)
adj_reps_RIR(0.75)
#> [1] 10.01001

# Use ballistic adjustment (this implies doing half the reps)
adj_reps_RIR(0.75, mfactor = 2)
#> [1] 5.005005

# Use 2 reps in reserve
adj_reps_RIR(0.75, adjustment = 2)
#> [1] 8.01001

# Use Linear model
adj_reps_RIR(0.75, max_reps_func = max_reps_linear, adjustment = 2)
#> [1] 7.25

# Use Modifed Epley's equation with a custom parameter values
adj_reps_RIR(
  0.75,
  max_reps_func = max_reps_modified_epley,
  adjustment = 2,
  kmod = 0.06
)
#> [1] 4.555556
# ------------------------------------------
# Adjustment using Deducted Intensity (DI)
adj_reps_DI(0.75)
#> [1] -150.1502

# Use ballistic adjustment (this implies doing half the reps)
adj_reps_DI(0.75, mfactor = 2)
#> [1] -75.07508

# Use 10% deducted intensity
adj_reps_DI(0.75, adjustment = -0.1)
#> [1] 5.299417

# Use Linear model
adj_reps_DI(0.75, max_reps_func = max_reps_linear, adjustment = -0.1)
#> [1] 5.95

# Use Modifed Epley's equation with a custom parameter values
adj_reps_DI(
  0.75,
  max_reps_func = max_reps_modified_epley,
  adjustment = -0.1,
  kmod = 0.06
)
#> [1] 3.941176
# ------------------------------------------
# Adjustment using Relative Intensity (RelInt)
adj_reps_rel_int(0.75)
#> [1] 10.01001

# Use ballistic adjustment (this implies doing half the reps)
adj_reps_rel_int(0.75, mfactor = 2)
#> [1] 5.005005

# Use 85% relative intensity
adj_reps_rel_int(0.75, adjustment = 0.85)
#> [1] 4.004004

# Use Linear model
adj_reps_rel_int(0.75, max_reps_func = max_reps_linear, adjustment = 0.85)
#> [1] 4.882353

# Use Modifed Epley's equation with a custom parameter values
adj_reps_rel_int(
  0.75,
  max_reps_func = max_reps_modified_epley,
  adjustment = 0.85,
  kmod = 0.06
)
#> [1] 3.222222
# ------------------------------------------
# Adjustment using % max reps (%MR)
adj_reps_perc_MR(0.75)
#> [1] 10.01001

# Use ballistic adjustment (this implies doing half the reps)
adj_reps_perc_MR(0.75, mfactor = 2)
#> [1] 5.005005

# Use 85% of max reps
adj_reps_perc_MR(0.75, adjustment = 0.85)
#> [1] 8.508509

# Use Linear model
adj_reps_perc_MR(0.75, max_reps_func = max_reps_linear, adjustment = 0.85)
#> [1] 7.8625

# Use Modifed Epley's equation with a custom parameter values
adj_reps_perc_MR(
  0.75,
  max_reps_func = max_reps_modified_epley,
  adjustment = 0.85,
  kmod = 0.06
)
#> [1] 5.572222