  Team Recommendation has always been a challenging aspect in team sports. Such
systems aim to recommend a player combination best suited against the
opposition players, resulting in an optimal outcome. In this paper, we propose
a semi-supervised statistical approach to build a team recommendation system
for cricket by modelling players into embeddings. To build these embeddings, we
design a qualitative and quantitative rating system which considers the
strength of opposition also for evaluating player performance. The embeddings
obtained, describes the strengths and weaknesses of the players based on past
performances of the player. We also embark on a critical aspect of team
composition, which includes the number of batsmen and bowlers in the team. The
team composition changes over time, depending on different factors which are
tough to predict, so we take this input from the user and use the player
embeddings to decide the best possible team combination with the given team
composition.
