Researchers and practitioners have highlighted the necessity to monitor jump strategy metrics and the commonly reported outcome measures during the countermovement jump (CMJ) and drop jump (DJ) tests. However, there is a risk of confusion for practitioners, given the vast range of metrics that now seem to be on offer via analysis software when collecting data from force platforms. As such, practitioners may benefit from a framework that can help guide metric selection for commonly used jump tests, which is the primary purpose of this article. To contextualize the proposed framework, we have provided 2 examples for how this could work: one for the CMJ and one for the DJ, noting that these tests are commonly used by practitioners during routine testing across a range of sport performance and clinical settings.

The countermovement jump (CMJ) is one of the most used performance assessments in strength and conditioning. Although numerous studies discuss the usability of different metrics in this test, this is often performed within the context of a specific aim. However, to our knowledge, no information currently exists providing practitioners with some over-arching recommendations on which metrics to choose when the purpose of using the test differs. This article discusses how the metrics selected to monitor during CMJ testing may differ when aiming to use it as a proxy for athletic performance, as part of neuromuscular fatigue monitoring, or as part of a test battery for return to performance in injured athletes.

This infographic outlines a three-step process to determine the efficacy of selected jump metrics and the ability to use them in practice.

In this session from the NSCA’s 2018 TSAC Conference, Josh Hagen explains the importance of having an understanding metrics and how to implement monitoring for tactical athletes to influence training for optimal performance.

This article presents a contemporary, evidence-based, and practical framework that reduces the many strength and speed-strength metrics into five distinct qualities.

Monitoring training load is essential for determining if athletes are adapting positively or negatively to their training program. This article goes over the various measurement metrics and includes recommendations to monitor training load for football athletes.

This excerpt briefly discusses different assessments of internal and external load measures.

Accentuated eccentric loading (AEL) can be combined with lower-body power-based movements to acutely enhance them; however, currently, there are limited recommendations for this training method. AEL can enhance force and power metrics during its utilization with lower-body power based exercises. When using AEL, exercises should consist of jump squats and countermovement jumps with loading methods consisting of weight releasors or dumbbell hand release. Elastic bands can be used; however, more research is needed in this area. External loads ranging from 10–30% of body mass can be used. Future research needs to investigate increased eccentric and concentric loads when using AEL with power based movements.

Maximal force can be expressed across a range of conditions influenced by the external load and the time available to express force. As a result, several distinct and specific strength qualities exist. Conversely, some expressions of maximal force are similar and can be categorized as a single quality. Therefore, strength assessment systems must be sophisticated enough to isolate and measure each quality while minimizing redundant information. This article presents a contemporary, evidence-based and practical framework that reduces the many strength and speed-strength metrics into 5 distinct qualities. Alongside this, we present case examples of the application of strength diagnosis.

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