Resampling train and test data in R
Try using a different seed for each loop. You can do it like this.
my_seeds &lt;- c(1:10) # These are 10 seeds, 1, 2, 3...10. Change to whatever.     
for (i in 1:10){
          set.seed(my_seeds[i])
          ##########################
          ##########################
          boot.sample = sample(n, 1000, replace = TRUE)
          bootSample = dataset[boot.sample, ]
          bootSample
        
          split = sample.split(bootSample$blueWins, SplitRatio= 0.80)
          training = subset(bootSample, split == TRUE,  replace=TRUE)
          test = subset(bootSample, split == FALSE,  replace=TRUE)
          print(training)
    }