Probe profile functions — probe

Family of functions that serve a purpose of probing sprint or force-velocity profile. This is done by increasing individual sprint parameter for a percentage and calculating which parameter improvement yield biggest deduction in sprint tim

probe_FV "probes" F0 and V0 and calculates which one improves sprint time for a defined distance

probe_MSS_MAC "probes" MSS and MAC and calculates which one improves sprint time for a defined distance

Usage

probe_FV(
  distance,
  F0,
  V0,
  bodymass = 75,
  inertia = 0,
  resistance = 0,
  perc = 2.5,
  ...
)

probe_MSS_MAC(distance, MSS, MAC, perc = 2.5)

Arguments

distance

Numeric vector

F0, V0

Numeric vectors. FV profile parameters

bodymass

Body mass in kg

inertia

External inertia in kg (for example a weight vest, or a sled). Not included in the air resistance calculation

resistance

External horizontal resistance in Newtons (for example tether device or a sled friction resistance)

perc

Numeric vector. Probing percentage. Default is 2.5 percent

...

Arguments passed on to get_air_resistance

velocity: Instantaneous running velocity in meters per second (m/s)
bodyheight: In meters (m). Default is 1.75m
barometric_pressure: In Torrs. Default is 760Torrs
air_temperature: In Celzius (C). Default is 25C
wind_velocity: In meters per second (m/s). Use negative number as head wind, and positive number as back wind. Default is 0m/s (no wind)

MSS, MAC

Numeric vectors. Model parameters

Value

probe_FV returns a data frame with the following columns

F0: Original F0
V0: Original F0
bodymass: Bodymass
inertia: Inertia
resistance: Resistance
Pmax: Maximal power estimated using F0 * V0 / 4
Pmax_rel: Relative maximal power
slope: FV profile slope
distance: Distance
time: Time to cover distance
probe_perc: Probe percentage
F0_probe: Probing F0
F0_probe_time: Predicted time for distance when F0 is probed
F0_probe_time_gain: Difference in time to cover distance between time_optimal and time
V0_probe: Probing V0
V0_probe_time: Predicted time for distance when V0 is probed
V0_probe_time_gain: Difference in time to cover distance between time_optimal and time
profile_imb: Percent ratio between V0_probe_time_gain and F0_probe_time_gain

probe_MSS_MAC returns a data frame with the following columns

MSS: Original MSS
MAC: Original MAC
Pmax_rel: Relative maximal power estimated using MSS * MAC / 4
slope: Sprint profile slope
distance: Distance
time: Time to cover distance
probe_perc: Probe percentage
MSS_probe: Probing MSS
MSS_probe_time: Predicted time for distance when MSS is probed
MSS_probe_time_gain: Difference in time to cover distance between probe time and time
MAC_probe: Probing MAC
MAC_probe_time: Predicted time for distance when MAC is probed
MAC_probe_time_gain: Difference in time to cover distance between probing time and time
profile_imb: Percent ratio between MSS_probe_time_gain and MAC_probe_time_gain

Examples

MSS <- 10
MAC <- 8
bodymass <- 75

fv <- create_FVP(MSS, MAC, bodymass)

dist <- seq(5, 40, by = 5)

probe_MSS_MAC_profile <- probe_MSS_MAC(
  distance = dist,
  MSS,
  MAC
)[["profile_imb"]]

probe_FV_profile <- probe_FV(
  distance = dist,
  fv$F0,
  fv$V0,
  fv$bodymass
)[["profile_imb"]]

plot(x = dist, y = probe_MSS_MAC_profile, type = "l", ylab = "Profile imbalance")
lines(x = dist, y = probe_FV_profile, type = "l", col = "blue")
abline(h = 100, col = "gray", lty = 2)