Classification of cricket shots is a recent field of study that has seen some growth. The addition of Human Pose Estimation (HPE) has the potential to advance the study of cricket shot classification. This paper investigates which of the available and widely use HPE frameworks are most suitable for for the domain of cricket and introduces a hand annotated verification dataset in order to test this. The findings indicate that any increase in precision will come at a steep computational cost but a middle ground can be found depending on the use-case.