Deep sequencing of ribosome footprints, also known as ribosome profiling (Ribo-seq), enables the quantification of mRNA translation and a comprehensive view of the translatome landscape. Here, we report an optimised Ribo-seq protocol and analysis pipeline for the model green alga, Chlamydomonas reinhardtiii (Chlamydomonas). Compared to the previously published data sets, the ribosome-protected fragments generated by our protocol showed improved mapping rates to the main open reading frames, reduced bias mapping to the gene coding regions and high 3-nt footprint periodicity. Using this optimised protocol, we employed Ribo-seq alongside RNA-seq to compute translation efficiency and identify genes with differential translation during the diurnal cycle. Interestingly, we found that the translation efficiency of many core cell cycle genes was significantly enhanced in cells at the early synthesis/mitosis (S/M) stage. This result suggests that translational regulation plays a role in cell cycle regulation in C. reinhardtii. Furthermore, the high periodicity of ribosome footprints allowed us to identify potential C. reinhardtii upstream open reading frames (uORFs). Further analysis revealed that some of these uORFs are differentially regulated and may play a role in diurnal regulation. In summary, we used an optimised Ribo-seq protocol to generate a high-quality Ribo-seq data set that constitutes a valuable resource for Chlamydomonas genomics. The ribosome profile data is linked to the Chlamydomonas reference genome and accessible to the scientific community.