Linear mixed models? MANOVA? I'm confused...

I’m a newbie in statistics and R, so I hope that my question isn’t too banal for you.

I’m going to carry out an experiment in order to verify whether cortisol and Hemoglobin levels are different when soccer players fail a penalty kick, compared with when they score a goal.

Each player pulls 5 penalty kicks. Here is an example for three subjects:

(R code)
subj<-c(1,1,1,2,2,2,3,3,3,4,4,4) err <-c("goal","fail","goal" ,"goal","goal","goal", "fail", "goal", "goal", "goal", "goal", "fail") hemo<-c (.12,.23,.23,.43,.12,.13,.61,.23,.13,.34,.56,.11) cort<-c (220,130,210,130,150,130,630,230,230,340,560,110)
data<-data.frame(subj, err,hemo, cort)

I don't know which statistics I have to use... I'm a bit confused. Any advice? Thanks in advance