More than a Metric: How Training Load is Used in Elite Sport for Athlete Management.

Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is usually undertaken with a view to improve player performance and/or manage injury risk. To target these outcomes, practitioners attempt to optimise load at different stages throughout the training process, like adjusting individual sessions, planning day-to-day, periodising the season, and managing athletes with a long-term view. With greater investment in training load monitoring comes greater expectations, as stakeholders count on practitioners to transform data into informed, meaningful decisions. In this editorial we highlight how training load monitoring has many potential applications and cannot be simply reduced to one metric and/or calculation. With experience across a variety of sporting backgrounds, this editorial details the challenges and contextual factors that must be considered when interpreting such data. It further demonstrates the need for those working with athletes to develop strong communication channels with all stakeholders in the decision-making process. Importantly, this editorial highlights the complexity associated with using training load for managing injury risk and explores the potential for framing training load with a performance and training progression mindset.

Assessment of linear sprinting performance: a theoretical paradigm.

The purpose of this manuscript is to describe a theoretical paradigm from which to more accurately assess linear sprinting performance. More importantly, the model describes how to interpret test results in order to pinpoint weaknesses in linear sprinting performance and design subsequent training programs. A retrospective, quasi-experimental cross sectional analysis was performed using 86 Division I female soccer and lacrosse players. Linear sprinting performance was assessed using infrared sensors at 9.14, 18.28, 27.42, and 36.58 meter distances. Cumulative (9.14, 18.28, 27.42, and 36.58 meter) and individual (1(st), 2(nd), 3(rd), and 4(th) 9.14 meter) split times were used to illustrate the theoretical paradigm. Sub-groups were identified from the sample and labelled as above average (faster), average, and below average (slower). Statistical analysis showed each sub-group was significantly different from each other (fast < average < slow). From each sub-group select individuals were identified by having a 36.58 meter time within 0.05 seconds of each other (n = 11, 13, and 7, respectively). Three phases of the sprint test were suggested to exist and called initial acceleration (0-9.14 m), middle acceleration (9.14-27.42 m), and metabolic-stiffness transition (27.42-36.58 m). A new model for assessing and interpreting linear sprinting performance was developed. Implementation of this paradigm should assist sport performance professionals identify weaknesses, minimize training errors, and maximize training adaptations. Key PointsAssessment of linear sprinting should include splits for a greater understanding of performance.Individual split times can be used to identify specific areas of weakness.Appropriate training strategies can be developed and used to improve the identified weaknesses.