Pre-exercise Screening System (Exercise and Sports Science Australia). Players also gave verbal and written informed consent and were familiarized with study procedures, including completion of the Agility 5-0-5 Test. Each player then completed three 20-m linear sprints with 2 minutes of passive
Maria C. Madueno, Vincent J. Dalbo, Joshua H. Guy, Kate E. Giamarelos, Tania Spiteri, and Aaron T. Scanlan
Jon L. Oliver and Robert W. Meyers
The purpose of the current study was to assess the reliability of a new protocol that examines different components of agility using commercially available timing gates.
Seventeen physically active males completed four trials of a new protocol, which consisted of a number of 10-m sprints. Sprints were completed in a straight line or with a change of direction after 5 m. The change of direction was either planned or reactive, with participants reacting to a visual light stimulus.
There was no systematic bias in any of the measures, although random variation was reduced in the straight acceleration and planned agility when considering only the fnal pair of trials, with mean coefficients of variation (CV) of 1.6% (95%CI, 1.2% to 2.4%) and 1.1% (0.8% to 1.7%), respectively. Reliability of reactive agility remained consistent throughout with mean CVs of approximately 3%. Analyses revealed a high degree of common variance between acceleration times and both planned (r 2 = .93) and reactive (r 2 = .83) agility, as well as between the two agility protocols (r 2 = .87).
Both planned and reactive agility could be measured reliably. Protocol design and use of a light stimulus in the reactive test emphasize physical abilities comparable with other test measures. Therefore, inclusion of a reactive light stimulus does not appear to require any additional perceptual qualities.
Iván Peña-González, Alba Roldan, Carlos Toledo, Tomás Urbán, and Raúl Reina
classification system. Hence, this study evaluated the content validity of the new classification system for CP football through a COD test (ie, modified agility test [MAT]) and explored the validity and reliability of a new dribbling test to correctly classify international CP football players. We hypothesized
Matthew Ellis, Mark Noon, Tony Myers, and Neil Clarke
accelerations) or fatigue resistance during a soccer simulation match with young soccer players (18  y) 9 despite improving reactive agility in elite youth soccer players (14  y). 10 High doses of caffeine have also been reported to increase the susceptibility to negative side effects (increased heart
Manuel Santiago Martin, Fernando Pareja Blanco, and Eduardo Saez De Villarreal
the following 3 different strength training methods: (1) combined dry-land and in-water-specific strength training; (2) in-water-specific strength; and (3) dry-land plyometric training on strength and WP-specific performance parameters (ie, in-water boost, swim sprint, agility, and throwing
Greg Henry, Brian Dawson, Brendan Lay, and Warren Young
To study the validity of a video-based reactive agility test in Australian footballers.
15 higher performance, 15 lower performance, and 12 nonfootballers completed a light-based reactive agility test (LRAT), a video-based reactive agility test (VRAT), and a planned test (PLAN).
With skill groups pooled, agility time in PLAN (1346 ± 66 ms) was significantly faster (P = .001) than both reactive tests (VRAT = 1550 ± 102 ms; LRAT = 1572 ± 97 ms). In addition, decision time was significantly faster (P = .001; d = 0.8) in LRAT (278 ± 36 ms) than VRAT (311 ± 47 ms). The correlation in agility time between the two reactive tests (r = .75) was higher than between the planned and reactive tests (r = .41–.68). Higher performance players had faster agility and movement times on VRAT (agility, 130 ± 24 ms, d = 1.27, P = .004; movement, 69 ± 73 ms, d = 0.88, P = .1) and LRAT (agility, 95 ± 86 ms, d = 0.99, P = .08; movement, 79 ± 74 ms; d = 0.9; P = .08) than the nonfootballers. In addition, higher (55 ± 39 ms, d = 0.87, P = .05) and lower (40 ± 57 ms, d = 0.74, P = .18) performance groups exhibited somewhat faster agility time than nonfootballers on PLAN. Furthermore, higher performance players were somewhat faster than lower performance for agility time on the VRAT (63 ± 85 ms, d = 0.82, P = .16) and decision time on the LRAT (20 ± 39 ms, d = 0.66, P = .21), but there was little difference in PLAN agility time between these groups (15 ± 150 ms, d = 0.24, P = .8).
Differences in decision-making speed indicate that the sport-specific nature of the VRAT is not duplicated by a light-based stimulus. In addition, the VRAT is somewhat better able to discriminate different groups of Australian footballers than the LRAT. Collectively, this indicates that a video-based test is a more valid assessment tool for examining agility in Australian footballers.
Ryan Holding, Rudi Meir, and Shi Zhou
The purpose of this study was to examine whether a video-based warm-up could provide an acute performance benefit to response time for athletes in a sport-specific agility task. In addition, 2 learning strategies, explicit and implicit, were compared for their effectiveness in facilitating an improvement in sport-specific agility. Thirty representative male junior rugby union players (age 14–16 y, mean age 14.6 ± 1.09 y) were placed in 3 experimental groups (explicit, implicit, and control) and completed 2 intervention sessions. Testing sessions included preintervention testing, completion of the video-based warm-up intervention, and postintervention testing. A 3D motion-analysis system was used to assess response time in the testing battery. The athletes’ response times on the pre- to postintervention tests were compared to determine the effectiveness of the video-based warm-up. A 2-way general linear model with repeated-measures analysis indicated that both the explicit (P = .030, d = 0.28) and implicit (P = .049, d = 0.33) groups significantly improved their response time by the intervention compared with the control group (P = .367, d = 0.08). The mean postintervention response time for the explicit group improved by 19.1% (from 0.246 s pre to 0.199 s post), and the implicit group improved by 15.7% (from 0.268 s to 0.226 s). Findings suggest that a video-based warm-up may provide an acute benefit to sport-specific agility performance for junior athletes.
Anne Delextrat, Bernard Grosgeorge, and Francois Bieuzen
To investigate the reliability and determinants of performance in a new test of planned agility in elite junior basketball players.
Seventeen female (15.1 ± 0.4 y, 176.9 ± 11.2 cm, 65.7 ± 10.9 kg) and 42 male (14.9 ± 0.4 y, 193.7 ± 8.1 cm, 79.0 ± 12.0 kg) elite junior basketball players performed 5 fitness tests presented in a random order, including a 20-m sprint, a planned-agility test, a triple bilateral horizontal countermovement jump, and 2 triple unilateral horizontal countermovement jumps (with each leg separately). The novelty of the planned-agility test is that it included both offensive and defensive movements. The determinants of planned agility were assessed by a stepwise-regression analysis, and the reliability of the new test was evaluated by the intraclass correlation coefficient and the typical error of measurement.
The main results show good reliability of the new test of planned agility. In addition, the determinants of planned-agility performance were different between genders, with sprint performance explaining 74.8% of the variance for girls, while unilateral jump performance and body mass were the most important for boys, accounting for 24.0% and 8.9% of the variance, respectively, in planned agility.
These results highlight a gender effect on the determinants of planned-agility performance in young elite basketball players and suggest that straight-line sprint and unilateral horizontal tests must be implemented to test elite junior players.
Robert G. Lockie, Matthew D. Jeffriess, Tye S. McGann, Samuel J. Callaghan, and Adrian B. Schultz
Research indicates that planned and reactive agility are different athletic skills. These skills have not been adequately assessed in male basketball players.
To define whether 10-m-sprint performance and planned and reactive agility measured by the Y-shaped agility test can discriminate between semiprofessional and amateur basketball players.
Ten semiprofessional and 10 amateur basketball players completed 10-m sprints and planned- and reactive-agility tests. The Y-shaped agility test involved subjects sprinting 5 m through a trigger timing gate, followed by a 45° cut and 5-m sprint to the left or right through a target gate. In the planned condition, subjects knew the cut direction. For reactive trials, subjects visually scanned to find the illuminated gate. A 1-way analysis of variance (P < .05) determined between-groups differences. Data were pooled (N = 20) for a correlation analysis (P < .05).
The reactive tests differentiated between the groups; semiprofessional players were 6% faster for the reactive left (P = .036) and right (P = .029) cuts. The strongest correlations were between the 10-m sprints and planned-agility tests (r = .590–.860). The reactive left cut did not correlate with the planned tests. The reactive right cut moderately correlated with the 10-m sprint and planned right cut (r = .487–.485).
The results reemphasized that planned and reactive agility are separate physical qualities. Reactive agility discriminated between the semiprofessional and amateur basketball players; planned agility did not. To distinguish between male basketball players of different ability levels, agility tests should include a perceptual and decision-making component.
Michael J. Davies, Warren Young, Damian Farrow, and Andrew Bahnert
To compare the agility demands of 4 small-sided games (SSGs) and evaluate the variability in demands for elite Australian Football (AF).
Fourteen male elite Australian Football League (AFL) players (mean ± SD; 21.7 ± 3.1 y, 189.6 ± 9.0 cm, 88.7 ± 10.0 kg, 39.4 ± 57.1 games) completed 4 SSGs of 3 × 45-s bouts each with modified designs. Video notational analysis, GPS at 5 Hz, and triaxial accelerometer data expressed the external player loads within games. Three comparisons were made using a paired t test (P < .05), and magnitudes of differences were reported with effect size (ES) statistics.
Reduced area per player (increased density) produced a small increase in total agility maneuvers (SSG1, 7.2 ± 1.3; SSG2, 8.8 ± 4.1), while a large 2D player load was accumulated (P < .05, ES = 1.22). A reduction in players produced a moderate (ES = 0.60) total number of agility maneuvers (SSG 3, 11.3 ± 6.1; SSG 2, 8.3 ± 3.6); however, a greater variability was found. The implementation of a 2-handed-tag rule resulted in a somewhat trivial decline (P > .05, ES = 0.16) in agility events compared with normal AFL tackling rules (SSG 2, 8.3 ± 3.6; SSG 4, 7.8 ± 2.6).
SSG characteristics can influence agility-training demand, which can vary considerably for individuals. Coaches should carefully consider SSG design to maximize the potential to develop agility for all players.