Purpose: To quantify and compare external and internal game workloads according to contextual factors (game outcome, game location, and score-line). Methods: Starting semiprofessional, male basketball players were monitored during 19 games. External (PlayerLoad™ and inertial movement analysis variables) and internal (summated-heart-rate-zones and rating of perceived exertion [RPE]) workload variables were collected for all games. Linear mixed-effect models and effect sizes were used to compare workload variables based on each of the contextual variables assessed. Results: The number of jumps, absolute and relative (in min−1) high-intensity accelerations and decelerations, and relative changes-of-direction were higher during losses, whereas session RPE was higher during wins. PlayerLoad™ the number of absolute and relative jumps, high-intensity accelerations, absolute and relative total decelerations, total changes-of-direction, summated-heart-rate-zones, session RPE, and RPE were higher during away games, whereas the number of relative high-intensity jumps was higher during home games. PlayerLoad™, the number of high-intensity accelerations, total accelerations, absolute and relative decelerations, absolute and relative changes-of-direction, summated-heart-rate-zones, sRPE, and RPE were higher during balanced games, whereas the relative number of total and high-intensity jumps were higher during unbalanced games. Conclusions: Due to increased intensity, starting players may need additional recovery following losses. Given the increased external and internal workload volumes encountered during away games and balanced games, practitioners should closely monitor playing times during games. Monitoring playing times may help identify when players require additional recovery or reduced training volumes to avoid maladaptive responses across the in-season.