minami-uonuma-analysis

JBCF南魚沼ロードレースの出力を分析

## 
## Attaching package: 'dplyr'
## 
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## 
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

d <- read.csv('jbcf-minami-uonuma.csv')
head(d)

##   Minutes Torq..N.m.  Km.h Watts      Km Cadence Hrate ID Altitude..m.
## 1 0.01667          0  0.00     0 0.00000       0     0  0        262.6
## 2 0.03333          0  0.00     0 0.00000       0     0  0        262.6
## 3 2.36667          0  8.01     0 0.00000       0     0  0        262.2
## 4 2.40000          0 15.25   337 0.00697      70     0  0        262.2
## 5 2.41667          0 17.30   337 0.01164      70     0  0        262.2
## 6 2.43333          0 21.67   305 0.01751      71     0  0        262.2

d <- d[1:4982,]
qplot(Minutes, Watts, data = d, geom = 'line')

changepointによる解析

library(changepoint)
change <- cpt.mean(data = d$Watts, method='BinSeg', Q=30)

## Warning: The number of changepoints identified is Q, it is advised to
## increase Q to make sure changepoints have not been missed.

plot(change)

セグメントを抽出

segs <- data.frame(duration=diff(c(0,change@cpts)), power=change@param.est$mean)
segs

##    duration  power
## 1        33 159.24
## 2       333 325.11
## 3       389 217.01
## 4        18 636.19
## 5       158 271.18
## 6        90 152.13
## 7         5 493.60
## 8        45  44.24
## 9       100 255.35
## 10       12  45.58
## 11        7 588.00
## 12      337 314.28
## 13      339 179.30
## 14       11 490.09
## 15      151 226.91
## 16      146 297.70
## 17      193 158.73
## 18        9 469.44
## 19       35 224.60
## 20       85 450.14
## 21      166 345.10
## 22       94 255.98
## 23      779 192.20
## 24      286 379.11
## 25      726 277.73
## 26       28  68.50
## 27        3 621.67
## 28       91 197.70
## 29      220 354.11
## 30       31 636.90
## 31       62  21.34

segs %>% filter(duration > 60, 300 < power)

##   duration power
## 1      333 325.1
## 2      337 314.3
## 3       85 450.1
## 4      166 345.1
## 5      286 379.1
## 6      220 354.1

power weight ratioに換算

segs %>% filter(duration > 60, 300 < power) %>% mutate(pwr=power / 60) %>% arrange(power)

##   duration power   pwr
## 1      337 314.3 5.238
## 2      333 325.1 5.419
## 3      166 345.1 5.752
## 4      220 354.1 5.902
## 5      286 379.1 6.319
## 6       85 450.1 7.502

mean(d$Watts)

## [1] 259.6

以上を踏まえて、JBCF南魚沼のコースを来年ターゲットにするとしたら @ E1レベル

トータル1時間半 つなぎは200W以上で、

• 5分 @ 5.5W/kg 2本
• 3分　@ 6W/kg 3本
• 1分半 @ 7.5W/kg 死ぬまで

などがよろしいか