# Poisson regression for count data - predictions

This is probably an elementary error in either my understanding or my R implementation: I am trying use a Poisson model to make some predictions. The original data is discrete count data. I would expect the predictions to also be discrete outcomes (e.g. 39, 40, 41). Instead - the predictions include decimals (41.2) - which seems odd for count predictions / the Poisson distribution. What am I doing wrong?

Example:

warpbreaks
breaksmodel<-glm(breaks~wool*tension, warpbreaks, family=poisson)
predict(breaksmodel,warpbreaks,type="response")