The development and application of a framework to guide training load prescription considering scheduling factors in basketball

Basketball teams typically undergo extensive training and competition demands across the season. Accordingly, it is becoming regular practice for basketball coaches and performance staff to implement monitoring programs to quantify external and internal loading in players during the season. As part of monitoring programs, it is essential to consider scheduling factors that may impact player loads across the regular season. In this regard, the impact of scheduling factors, such as game location, opposition ability, and fixture density, on player loads needs to be considered to precisely coordinate training schedules and appropriately manage player recovery in basketball teams. Thus, the aim of this research was to develop an evidence-based framework for use in practice to guide weekly training load prescription considering scheduling factors in basketball through: (i) conducting a systematic review to identify the precise impact of different scheduling factors on player loads in team sports; (ii) developing a framework that guides training load prescription across the regular season while factoring in prominent scheduling factors in basketball; and (iii) comparing the recommendations of the developed framework to training loads naturally prescribed in practice to a semi-professional basketball team. Ultimately, the number of games played in the current, previous, and subsequent weeks, days between games across subsequent weeks, and travel requirements were identified as the predominant scheduling factors to be considered in the TrAining load Recommendations based on weekly Game schEduling in baskeTball (TARGET) framework when planning weekly training loads for basketball players. In the TARGET framework, each scheduling factor is scored separately for each week of the season based on the team schedule. The overall score for each week in the TARGET framework is determined by summing the scores for all scheduling factors in that week to indicate schedule difficulty and guide training load prescription. The TARGET framework was retrospectively applied in practice to assess its utility and the extent to which coaching staff in a semi-professional basketball team may naturally consider scheduling factors when planning weekly team training loads. In this way, the weekly overall score in the TARGET framework was correlated with the weekly team training load prescribed across two regular seasons in a semi-professional, Australian basketball team. Accumulated PlayerLoadTM was measured using microsensors to quantify weekly team training load. The small, positive relationships (season one: r = 0.13; season two: r = 0.11) between weekly overall score in the TARGET framework scores and weekly team training load across two seasons suggest coaching staff of the investigated team tended to increase training load as schedule difficulty increased each week. Contrary to these findings, we expected coaching staff to reduce weekly team training loads as schedule difficulty increased, which suggests scheduling factors may not be adequately considered by some basketball coaching staff in real world contexts when planning team training loads across the regular season. The TARGET framework provides basketball coaches and performance staff with an easy-to-use, efficient, practical tool to inform weekly team training load prescription during the regular season. Furthermore, the ability to consider key scheduling factors in a prospective manner once the game schedule and travel plans are known for basketball teams, enables the TARGET framework to be used proactively to plan weekly training loads across the season