Development of change of direction ability is important to provide the physical and technical foundation to develop agility (Nimphius et al., 2016a). Therefore, it is important for strength and conditioning coaches, physiotherapists and rehabilitators, to evaluate this quality by selecting appropriate tests to evaluate change of direction ability. However, a lack of clarity regarding the definitions of agility and related qualities many years ago led to the formation of tests with questionable face validity (e.g., a test labelled ‘agility’ without involving a response to visual stimuli). Research over the last decade has improved the clarity in how we can assess agility and change of direction ability. That said, there are many important considerations for practioners to contemplate to effectively evaluate change of direction ability in the field which forms the focus of this blog.
Key Terms
‘Agility’ has been comprehensively defined as ‘a rapid and accurate whole-body movement with change of velocity, direction, or movement pattern in response to a stimulus’ (Jones & Nimphius, 2018). Whilst agility is an essential quality in field and court-based sports, it is important to consider what agility is by considering potential underpinning factors. FIGURE 1 (taken from Dos’Santos & Jones, 2022 & Jones & Dos’Santos, 2023) illustrates that agility is largely dependent on perceptual-cognitive factors that leads to the selection of an action (perception-action coupling). These actions could be instantaneous (i.e., change of direction or vertical jump) or have a timed duration and involve travel (i.e., sprinting, side-shuffling, etc.). For example, a running back looking to break the defensive line (FIGURE 2) may on receiving the ball perform a lateral shuffle motion as a ‘ready position’ to scan for an opening (known as the transitional phase), once an opening presents itself the running back may perform a sharp side-step cutting manoeuvre (an initiation) to evade an opponent and sprint into the gap and gain yards in the play (actualisation phase) (FIGURE 2). Effectively, the final phase decides the success of the play (yards gained), but the preceding phases play an important role to the player in preparation for that final phase (FIGURE 2).
Change of direction ability or speed is defined as ‘the ability to decelerate, reverse or change movement direction and accelerate again’.
Jones et al., 2009
Locomotion and instantaneous actions (FIGURE 1) are dependent on technical and physical factors that are specific to each action. Collectively, in developing ‘agility’ whilst attention should be paid to the development of perceptual-cognitive abilities (e.g., improve the thinking element), the ability to perform instantaneous and locomotion actions efficiently and effectively (e.g., make the athlete move faster – ACTION) is a foremost consideration requiring both technical and physical development to do so. Change of direction (COD) ability or speed is defined as ‘the ability to decelerate, reverse or change movement direction and accelerate again’ (Jones et al., 2009). Furthermore, the ability to maintain velocity during CODs without a clear ”plant” step (i.e., a curvilinear path of movement) or the ability to perform or change mode of travel to and from ‘transitional’ movements (i.e., side shuffle or back pedal) may be termed manoeuvrability (DeWeese & Nimphius, 2016).
Many tests appear in the literature that are purported to assess ‘agility’ or ‘change of direction’. However, it is important to be clear on the abovementioned definitions (TABLE 1 for a summary) to be able to recognise the qualities assessed during a reported test. An assessment of agility must involve some reaction to a stimulus to truly assess the athlete’s ability to respond to a stimulus, select the most appropriate movement patterns and carry out the movement pattern(s) efficiently and effectively. Whereas, if evaluating a change of direction, the actions of the athlete during the test must involve a change of direction with a definitive plant step and performed in a pre-planned manner. The remainder of this current blog will focus on assessing change of direction speed/ ability, due to the issues associated with providing a standardised, reliable sports specific stimulus to assess agility.
Assessments of Change of Direction Speed
There are a variety of tests available to strength and conditioning coaches to evaluate athletes’ COD speed. Well known tests include the 505 (Draper and Lancaster, 1985; Barber et al., 2016), pro-agility (Sierer et al., 2008), L-run / 3 cone drill (Sierer et al., 2008; Gabbett et al 2008), T-test (Munro & Herrington, 2011) and the Illinois test (Vescovi & McGuigan, 2008). A summary of well-known COD speed tests from the literature are presented in TABLE 2 with classifications described above to assist in determining the sub-qualities of COD examined by the test. For an extensive overview of a range of COD speed tests the interested reader should refer to the excellent article by Nimphius et al. (2018). For detailed descriptions of the more common above-mentioned tests see Jones & Nimphius (2018).
Please note many of the tests mentioned in this blog use timing cells to record test completion times. It is beyond the scope of this Blog to discuss the application of timing cells. A brief summary of important considerations is provided in FIGURE 3. Please refer to Lockie (2018) or Jones & Dos’Santos (2023) for further details on using timing cells.
A limitation of many traditional COD speed tests often is the test duration (TABLE 2). A test of COD speed should be of short duration, as the longer the test is, then there is less emphasis on assessing COD ability, but more on anaerobic capacity and sprint ability as more time is spent running between COD actions (Nimphius et al., 2016a). For instance, typical test durations shown in TABLE 2 suggest performance on all these tests may be influenced by metabolic limitations (Vescovi & McGuigan, 2008) and sprint ability (Nimphius et al., 2016a) and less on COD ability. Furthermore, many of the abovementioned tests due to the involvement of transitional movements (i.e., T-test) or a curvilinear path of running (i.e., running around cones during an L-run or Illinois) are suggested to be more appropriate assessments of manoeuvrability rather than an isolated measure of COD ability (Nimphius, 2014; DeWeese & Nimphius, 2016; Nimphius et al., 2018). Therefore, careful consideration of test design is needed to ensure the required quality is being assessed.
The remainder of this Blog will focus on the 505 test (FIGURE 4). The 505 removes much of the task complexity of other tests as with only one turn involved it provides a measure of COD ability with a particular emphasis during the “traditional” 505 on deceleration ability prior to a COD. The tests clearly involve a change of direction as there is a definitive ‘plant’ step at a turn line and does not involve running around cones, which would then effectively make it a test of manoeuvrability. The 505 test avoids the limitation of test duration as the typical completion times last 2-3 seconds (Gabbett et al., 2008; Jones et al., 2009; Nimphius et al., 2016a).
The 505 is not without limitations. For instance, total completion time of a 505 test may not necessarily provide a measure of COD ability. Biomechanical studies have found that the final contact time represents approximately 19.5-20% of completion times of 180° pivot tasks from various approaches (Jones et al., 2016; Graham-Smith et al., 2009; Jones et al., 2017), whereas Kaneko et al. (2019) found that COD time (termed cutting time – last 1 m of approach to first 1 m exit measured using a LAVEG) constituted a third (0.8 ± 0.08 s) of 505 completion times in a group (n = 24) of faster performers (2.45 ± 0.11 s). The latter substantiates the findings of Nimphius et al. (2013) that only 31% of the time during a 505 test is spent turning, with the remainder of the time decelerating and accelerating. Therefore, linear sprinting ability may influence 505 completion times and is perhaps more pronounced during traditional compared to modified 505 tests due to the greater entry velocity developed during the initial 10 m sprint. This view is supported by several studies that have found a relationship between linear sprinting speed and 505 test performance (Gabbett et al., 2008; Jones et al., 2009; Nimphius et al., 2016); despite the recognition that they are different physical qualities (Young et al., 2001). Furthermore, Sayers et al. (2015) using 3D motion analysis to examine COD performance times over distances 0.3, 0.5 and 1 m before and after the turn; measured as the time for the centre of mass to cover each distance before and after the turn; revealed strong relationships between 505 time and 5, 10 and 20 m sprint performance. However, the strength of these correlations reduced when COD ability was measured 0.5 m and 0.3 m before and after the turn. Thus, highlighting that 505-performance time is biased by linear sprinting ability.
Assessing COD ability over shorter approach and exit distances (i.e., less than 1 m before and after the turn) is not an option if using timing cells due to the compromised reliability and accuracy associated with reduced approach and exit distances (Sayers, 2015). An approach to overcome the limitation of linear sprinting speed influencing 505 test performance is to calculate the COD deficit (Nimphius et al., 2013; Nimphius et al., 2016a), whereby a 10 m sprint time is subtracted from the 505 time. The lower the value the greater the COD ability. This concept was initially proposed and investigated in 66 collegiate American football players performing 40-yard sprints with a 10-yard split and pro-agility trials with a split time for the first 10 yards of the test (a single 180° turn) (Nimphius et al., 2013). COD deficit was determined by subtracting the 10-yard sprint split time from the 10-yard split time from the pro-agility test with the resultant time providing an indication of the time taken to negotiate the 180° turn. Significant (p < 0.001) correlations were observed between pro-agility scores (total and split) time and 10-yard sprint performance. However, a low non-significant correlation was observed between COD deficit and 10-yard sprint time (r = 0.19), but significant moderate correlations were observed to pro-agility (r = 0.54) and pro-agility split times (r = 0.61). This data suggests that the COD deficit offers a measure of COD speed independent of linear sprinting speed. Subsequently, Nimphius et al. (2016a) investigated the application of the COD deficit within the 505 tests in 17 cricketers. The authors found that COD deficit correlated to 505 (r = 0.74 – 0.81), but not 10 m sprint time (r = -0.11-0.10), whilst 505 time correlated with sprint time (r = 0.52 – 0.70). Moreover, when Z scores were examined 5 of the 17 subjects were classified differently in terms of COD ability when using 505 or COD deficit. The results support the use of the COD deficit to isolate and quantify an individual’s COD ability, independent from their linear sprinting speed. The COD deficit has been further explored at various change of direction angles (Cuthbert et al., 2019; Nimphius et al, 2016b), transitioning between modes of travel (e.g., sprint to shuffle) (Nimphius et al., 2016b) and been shown to be more able to detect asymmetries in COD ability during a 505-test (Dos’Santos et al., 2018a). Thus, determining COD deficit should be a minimum requirement when assessing COD speed/ ability.
One limitation of the COD deficit is it may actually bias towards ‘linearly’ slower athletes. For instance, the ability to change direction during a 505 test depends on the athlete’s ability to reduce momentum in a few steps prior to the turn, to negotiate the turn and effectively re-accelerate out of the turn. The task is considerably harder with a faster approach whereby the athletes possess greater momentum which must be reduced leading into the turn. Thus, faster athletes and athletes of greater mass experience a much greater ‘braking demand’ during the test. Therefore, it is recommended that momentum is factored into the assessments by quantifying an athlete’s linear momentum. Moreover, another important aspect to consider is whether the athlete applies a ‘pacing strategy’ during tests such as the 505 test. This could be evaluated by comparing the 10 m approach time from a traditional 505 test to that from a linear 10 m sprint time. If the approach time is slower than the 10-m sprint it immediately tells the examiner that the athlete is adopting a ‘pacing strategy (self-regulatory)’ to either, make the test slightly easier and / or to reduce the braking demands / load. A cut off value could be an approach speed which is slower than a linear 10 m sprint time by a margin greater than the typical error, coefficient of variation or standard error of measurement associated with the 10 m linear sprint test (Jones & Dos’Santos, 2023). To conclude, during a traditional 505 test, the initial 10 m approach time should be recorded and the approach momentum (average velocity (10 m/ approach time) × athletes’ mass) determined. The athlete’s momentum can also be determined from a maximal linear sprint, which is useful for versions of the 505 without the longer approach (modified 505).
The pre-planned structure of the 505 test and all the tests outlined in TABLE 2 often leads to questions regarding the ecological validity in relation to match or game performance. For instance, the pro-agility or L-run used in the NFL combine (Sierer et al., 2008) hardly matches the changing patterns of play for all positions on the field in American football. Realistically the abovementioned tests or any other designed to mimic movement patterns in a sport will not achieve an exact replication due to the constantly changing patterns of play on the field. Moreover, often strategies adopted by athletes to negotiate the manoeuvre often leads to breaks in posture and technique from what is achieved during similar manoeuvres during match play in ‘open’ situations (FIGURE 5) and thus, maybe rules should be implemented to negate any undesired movement mechanics in this regard.
Do We Need to Gather More Information?
Assessment of time to completion of any COD task may still provide an oversimplification of an athlete’s COD ability. With available resources such as 3D motion analysis, force platforms, and high-speed cameras could be used to gather information regarding technique or kinetic characteristics of changing direction which could help evaluate COD efficiency or movement quality/ braking strategy on return to play scenarios. The associated costs and practicality (i.e., lab-based equipment) often precludes application of such analyses. Using readily available methods such as high-speed video (> 100 Hz) via smart phones could at least provide additional information of approach (deceleration), execution (‘plant’ step contact) and reacceleration phase characteristics, allowing an evaluation of an athlete’s deceleration and re-acceleration abilities. Whilst 2D analysis to derive centre of mass velocities to determine approach and exit velocities maybe too time consuming for a strength and conditioning coach, delaying feedback to athletes. FIGURE 6 outlines an approach to breakdown a 505 test into approach, execution and re-acceleration phases from video analysis, whereby additional information regarding step characteristics can also be determined. Alternative approaches could involve laser devices (Graham-Smith & Pearson, 2005; Hader et al., 2015; Kaneko et al., 2019). For instance, Hader et al., (2015) used 2 LAVEG speed guns to measure approach (10 m) speed toward and exiting (10 m) from 45° and 90° cuts, whereas others (Graham-Smith & Pearson, 2005; Kaneko et al., 2019) have used a LAVEG laser speed gun to examine the approach and exit velocity characteristics during a 180° COD task. The timing system has been shown to provide acceptable levels of validity and reliability to assess a range of movement characteristics (i.e., peak, and minimum speed, distance at peak speed) during such tasks (Hader et al., 2015) and could also be used to identify time spent braking, changing direction, and re-accelerating in a 505 test (Kaneko et al., 2019). Motorised resistance devices have also been used to quantify such variables during a 505 test (Eriksrud et al., 2022). Thus, may be options to practitioners with available resources.
Test Selection
Test choice and the associated methods must be determined with respect to the purpose of the assessment (e.g., is it to replicate common patterns, assess a specific aspect of athleticism, or to evaluate ‘kinesiophobia’ and physical capacity prior to return to play?) (Jones & Nimphius, 2018). To decide on an appropriate test/ assessment strategy for COD and/ or manoeuvrability, it is important to ensure the “why” of testing is considered (Nimphius et al., 2018). Practitioners should consider the following to make informed decisions regarding test selection
- Consider isolating the COD by reducing the length of the test (e.g., less running content and number of directional changes) or calculating the COD deficit and ensuring a definitive ‘plant’ step is performed to change direction
- Consider calculating approach momentum (velocity × body mass) for contact sports and identify/ judge the braking demand this places on the athlete
- Consider (qualitative) technique analysis of the movement to determine COD efficiency or movement quality/ braking strategy upon return to play scenarios (e.g., the CMAS if using a test that involves side-step cutting).
- Consider whether change in mode of travel or ability to maintain velocity (manoeuvrability) is needed rather than or solely assessing COD ability
Once these points have been considered, the selection of an appropriate test may in part depend on the common movement patterns involved within that sport. That said, tests may be selected purely based on the physical demand the test elicits on an athlete for general athletic quality assessment or return to play evaluation (Nimphius, 2017). For instance, whilst 180° turns are often observed in many different field and court-based sports, they are often the least common compared to other angles of direction change in soccer (Bloomfield et al., 2007; Morgan et al., 2021), netball (Sweeting et al., 2017) and Gaelic football (Talty et al., 2022). Nevertheless, practitioners in such sports may often use a test like the 505-test due to the deceleration/ braking demand involved in the test. It should be recognised that changing direction to differing angles (and different approach velocities) results in marked biomechanical differences (Scheurs et al., 2017; Dos’Santos et al., 2018b; Dos’Santos et al., 2021). Therefore, potentially practitioners may consider assessing performance and/ or technique of athletes performing different directional changes (e.g., a COD profile) given that multiple-directional changes may be performed in their sport (See Jones & Dos’Santos, 2023, for an example).
Presenting and Interpreting Information
Having collected data, the next step is to effectively present information in an easy to view format for athletes and coaches. Data could be compared within a squad as shown in FIGURE 7 or to equivalent normative data from literature or applied practice. FIGURE 7 (left) presents Z (athletes time – mean group time/ standard deviation of the group) scores which are converted to T scores [percentiles] (10 (Z score) + 50) in order to rate the athlete against the group, identifying strengths and weaknesses. The Z scores (left of Figure 6) highlight 5 measures whereby the athlete is faster than the group average by at least 1 standard deviation (the bars in Figure 6 left are green using a simple traffic light system to highlight areas of strength). However, the athlete is 1 standard deviation slower than the group for right change of direction deficit (red bar = +1 standard deviation slower than the group) and around average for left change of direction deficit and right 505 completion time (amber bars = between + 1 to -1 standard deviation around the mean for the group). The T- scores presented to the right of FIGURE 7 effectively shows the same, any point that appears inside the dark red heptagon (average for the group) indicates that the athlete is faster than average for the group, whereas points that fall outside the dark red heptagon indicate an area of weakness (slower than average for the group). Graphical illustrations such as these help highlight strengths and weaknesses in the athlete’s speed and change of direction profile that can be targeted.
A closer look at the data in FIGURE 7 shows that clearly the athlete has good linear sprinting speed over 20 m and thus, is influential in the athlete having good left 505 completion time. However, the athlete is slower than average for change of direction deficits particularly on the right. This clearly indicates that the athlete needs to improve their ability to change direction. Furthermore, noticeable is the differing Z scores between left and right completion times and change of direction deficit. Given that the group means and standard deviations for right and left 505 completion time and COD deficit are similar for the group (top of FIGURE 7). The athlete clearly has discrepancies between right and left completion times and COD deficit – the athlete is not equally efficient at changing direction off the right and left limb. Whilst the data collected, and its presentation clearly shows areas for the athlete to improve. However, at this point in time we can only speculate on the causes for; a) slower than average COD ability and, b) discrepancies between changing direction from left and right. Has the athlete had a previous injury? Is the athlete technically deficient when changing direction? Are there technical differences in turning from the left, or right? Does the athlete have adequate eccentric strength to control the rapid deceleration during the approach? Are there any imbalances regarding muscle strength qualities between limbs? Therefore, collection of additional information such as video analysis of the directional changes, exploring the athlete’s injury history and amalgamating other test results from strength and power testing would help provide a clearer picture to explain these performance trends and provide clearer avenues for intervention.
Summary
Development of COD ability is important to provide the physical and technical foundation to develop agility. Therefore, it is important for strength and conditioning coaches to evaluate this quality by selecting appropriate tests to evaluate COD ability. Test choice and associated methods must be determined with respect to the purpose of the assessment. The following points should be considered before deciding on the test to use to evaluate COD speed and the methods adopted:
- Ensure that the test design clearly involves a directional change, and that this element is isolated from other contributing factors to test performance (e.g., linear running speed). Alternatively, if change in mode of travel or ability to maintain velocity (manoeuvrability) is needed rather than or solely assessing COD ability then this should be factored into the choice of test.
- Factor in the athlete’s momentum (velocity × body mass) in the COD test to identify/ judge the braking demand placed on the athlete
- Consider whether additional information such as (qualitative) technique analysis is needed to determine COD efficiency or movement quality/ braking strategy upon return to play scenarios
This blog is adapted from a book chapter in Jones, P.A., & Dos’Santos, T. (2023). Multidirectional speed in sport: Research to Application. Routledge.
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