How to get predicted and observed risk estimates from riskRegression::FGR() subdistribution competing risk model object?

Question

I want to extract observed and predicted estimates from time to event riskRegression::FGR() competing risk model object.

Below is some simulated data:

library(simstudy)
library(data.table)
library(survival)
library(riskRegression)
library(cmprsk)
library(prodlim)

#Generate time to event data
d1 <- defData(varname = "x1", formula = .5, dist = "binary")
d1 <- defData(d1, "x2", .5, dist = "binary")
head(dtSurv)
f <- "(time==censor)*0 + (time==event_1)*1 + (time==event_2)*2 + (time==event_3)*3"
cdef <- defDataAdd(varname = "time", 
                   formula = "pmin(censor, event_1, event_2, event_3)", dist = "nonrandom")
cdef <- defDataAdd(varname = "time", 
                   formula = "pmin(censor, event_1, event_2, event_3)", dist = "nonrandom")
cdef <- defDataAdd(cdef, varname = "event", 
                   formula = f, 
                   dist = "nonrandom")
dtSurv_final <- addCompRisk(dtSurv, 
                            events = c("event_1", "event_2", "event_3", "censor"), 
                            timeName = "time", censorName = "censor")
head(dtSurv_final)

#Fit subdistribution model
crr<-riskRegression::FGR(Hist(time, event)~ x1+x2 ,data=dtSurv_final, cause=1)
crr.object<-riskRegression::Score(list(model1=crr),
          Hist(time,event)~1,data=dtSurv_final, cause=1, times=30, plots="cal")
#Store model output 
(cal<-crr.object[["Calibration"]]$plotframe %>% as.data.frame())

I tried extracting the observed and predicted risks from cal but have been unable to do so.