Increasing demands for food and energy require a step change in the effectiveness, speed and flexibility of crop breeding. The aim of this study was therefore to assess the potential of genome-wide association studies (GWASs) and genomic selection (i.e., phenotype prediction from a genome-wide set of markers) to guide fundamental plant science and accelerate breeding in the energy grass Miscanthus. We generated over 100,000 single-nucleotide variants (SNVs) by sequencing restriction-site associated DNA (RAD) tags in 138 M. sinensis genotypes and related SNVs to phenotypic data for 17 traits measured in a field trial. Confounding by population structure and relatedness was severe in naïve GWAS analyses, but mixed-linear models robustly controlled for these effects and allowed us to detect multiple associations that reached genome-wide significance after Bonferroni corrections. Genome-wide prediction accuracies tended to be moderate to high (average = 0.57) but varied dramatically across traits (range = 0.05-0.95). As expected, predictive abilities (1) were correlated with broad-sense heritabilities (r > 0.57, P < 0.018); (2) increased linearly with the size of the mapping population, but reached a plateau when the number of markers used for prediction exceeded 10,000-20,000; and (3) tended to decline, but remain significant, when cross-validations were performed across subpopulations. Our results suggest that the immediate implementation of genomic selection in Miscanthus breeding programs may be feasible.