Spermatogenesis is a tightly regulated process to produce male gametes. It involves the sequential and coordinated activation and repression of thousands of genes and proteins. Many of these genes and proteins are testis-specific and are required across multiple cell states, for the successful development of spermatogonial stem cells into mature sperm cells. Understanding the intricate functions and mechanisms at each step of this process requires a multi-dimensional approach that integrates quantitative and qualitative methods. We used single-cell RNA sequencing data, spatial protein profiling, and automated image analysis to generate a high-resolution spatio-temporal map of the human testis. Through transcriptomics analysis, we identified 12 distinct states of germ cells corresponding to subsets of spermatogonia, spermatocytes, and spermatids. By utilizing a large-scale fluorescent-based multiplex immunohistochemistry pipeline, we performed an in-depth characterization of approximately 500 proteins expressed in different germ cells, mapping their exact spatial localization during spermatogenesis. The generated data allowed us to cluster the proteins into expression groups based on common patterns of cell state-specific expression, forming the basis for downstream functional analysis. In total, we identified 18 different protein clusters and demonstrated that the proteins in these groups were linked to germ cell-specific functions such as cell differentiation or cell cycle regulation at different phases of spermatogenesis. Mapping mRNA and protein levels in the germ cell states also allowed studying the correlation between mRNA and protein along spermatogenesis. During spermatogenesis, two distinct phases of inactive transcription have been identified and are known to i) be associated with early meiosis and ii) mRNA production arrest during the cellular transformation of haploid round cells into elongating spermatids. We identified several cases of high positive correlation between mRNA and protein expression in germ cell states, but interestingly, for more than one-third of the investigated proteins, the correlation coefficients were very low. Proteins exhibiting expression at a later cell state compared to their mRNA expression provided new insight into the complex spatio-temporal nature of spermatogenic function and mRNA translation dynamics. In summary, we present a spatio-temporal single-cell type reference map of adult human spermatogenesis. Our automated staining-to-image analysis pipeline reliably extracts quantitative measurements from state-specific germ cells in human testis tissue and can be used to characterize poorly defined proteins not previously described in the context of sperm development. This data also has the potential to contribute to valuable insights into the molecular functions and pathways of proteins previously linked to infertility and disorders of the male gonads.