The application of acceleration and deceleration data as a measure of an athlete’s physical performance is common practice in team sports. Acceleration and deceleration are monitored with athlete tracking technologies during training and games to quantify training load, prevent injury and enhance performance. However, inconsistencies exist throughout the literature in the reported methodological procedures used to quantify acceleration and deceleration. The object of this review was to systematically map and provide a summary of the methodological procedures being used on acceleration and deceleration data obtained from athlete tracking technologies in team sports and describe the applications of the data. Systematic searches of multiple databases were undertaken. To be included, studies must have investigated full body acceleration and/or deceleration data of athlete tracking technologies. The search identified 276 eligible studies. Most studies (60%) did not provide information on how the data was derived and what sequence of steps were taken to clean the data. Acceleration and deceleration data were commonly applied to quantify and describe movement demands using effort metrics. This scoping review identified research gaps in the methodological procedures and deriving and cleaning techniques that warrant future research focussing on their effect on acceleration and deceleration data.

This study examined the impact of various smoothing techniques on acceleration data obtained from a Global Navigation Satellite System (GNSS) device during accelerating and decelerating movements, resembling those commonly observed in team sports. Eight participants performed six different accelerating and decelerating movements at different intensities and starting speeds for a total of 46 trials each. The movements were collected concurrently at 10 Hz using a GNSS device (Vector S7, Catapult Sports) at 100 Hz using a motion analysis system (Vicon). Acceleration data were smoothed using (I) a fourth-order Butterworth filter (cut-off frequencies ranging from raw to 4.9 Hz), (II) exponential smoothing (smoothing constant ranging from 0.1 to 0.9), and (III) moving average (sliding window ranging from 0.2 s to 2.0 s). To determine the ability of a GNSS to quantify acceleration, a variety of measurement indices of validity were obtained for each movement and each smoothing technique. The fourth-order Butterworth filter with a cut-off frequency of 2 Hz (mean bias 0.00 m·s−2, 95% LoA ± 1.55 m·s−2, RMSE 0.79 m·s−2) showed the strongest relationship with the Vicon data. These results indicate that this smoothing technique is more accurate than those currently used and accepted on GNSS devices in the sports science community.

This study aimed to measure the differences in commonly used summary acceleration metrics during elite Australian football games under three different data processing protocols (raw, custom-processed, manufacturer-processed). Estimates of distance, speed and acceleration were collected with a 10-Hz GNSS tracking technology device from fourteen matches of 38 elite Australian football players from one team. Raw and manufacturer-processed data were exported from respective proprietary software and two common summary acceleration metrics (number of efforts and distance within medium/high-intensity zone) were calculated for the three processing methods. To estimate the effect of the three different data processing methods on the summary metrics, linear mixed models were used. The main findings demonstrated that there were substantial differences between the three processing methods; the manufacturer-processed acceleration data had the lowest reported distance (up to 184 times lower) and efforts (up to 89 times lower), followed by the custom-processed distance (up to 3.3 times lower) and efforts (up to 4.3 times lower), where raw data had the highest reported distance and efforts. The results indicated that different processing methods changed the metric output and in turn alters the quantification of the demands of a sport (volume, intensity and frequency of the metrics). Coaches, practitioners and researchers need to understand that various processing methods alter the summary metrics of acceleration data. By being informed about how these metrics are affected by processing methods, they can better interpret the data available and effectively tailor their training programs to match the demands of competition.

This study identified and profiled the types of player actions of Australian football players executed during high acceleration and/or deceleration efforts and identified how the duration exceeding the acceleration or deceleration threshold influenced the identified executed player actions. The commencing speed of the acceleration and deceleration efforts were also assessed. Acceleration and deceleration efforts of 22 Australian football players monitored with a 10-Hz GNSS device across two matches were analysed. Synchronised video footage of the matches was used to identify the player actions executed during acceleration and deceleration efforts. Linear mixed models were conducted to examine the relationship between commencing speed, player action, and duration exceeding the effort threshold. ‘Linear movement’ and ‘jump’ were the most frequently executed player actions for high accelerations and ‘stop’ and ‘being tackled’ for high decelerations. Significant differences were observed in commencing speed between player actions for the high deceleration efforts. Furthermore, it was found that a higher commencing speed was associated with an increased duration exceeding the deceleration threshold. These findings will help practitioners and researchers with selecting minimum-duration criteria for acceleration and deceleration efforts and provide an understanding of the types of player actions executed during these efforts.

This study assessed the concurrent validity and between-device reliability of the Catapult Vector S8 GNSS device for measuring distance, speed, acceleration and banded distance metrics. Twelve male sub-elite team sport athletes completed a testing protocol consisting of linear sprints, change of direction drills and a modified small-sided game. Validity was evaluated against criterion reference systems, a VICON motion capture system for most trials and a Stalker ATS radar for 50 m sprints, evaluated using root mean square error (RMSE) and mean bias. Between-device reliability was assessed using interclass correlation coefficients (ICC) and typical error (TE%). The Vector S8 demonstrated good validity with minimal errors for instantaneous distance (RMSE: 0.03 ± 0.01 m), speed (RMSE: 0.14 ± 0.05 m·s ⁻¹ ) and acceleration (RMSE: 0.29 ± 0.14 m·s ⁻² ). No overall bias was detected for instantaneous distance and speed, and the bias for acceleration (−0.016) was minimal. Accumulated distance showed a small underestimation across trials (mean bias −1.42%), with consistently low RMSE values (0.26–3.06 m), indicating high measurement precision. The 50 m sprint results showed similar validity, with minimal RMSE for instantaneous speed (0.14 ± 0.15 m·s ⁻¹ ) and acceleration (0.22 ± 0.22 m·s ⁻² ). Between device reliability demonstrated excellent agreement across all measured variables (ICC ≥ 0.95) with good precision (TE as CV < 3.13%). No significant systematic bias was observed between devices for any variable (p > 0.05). This is the first study to validate the Catapult Vector S8 GNSS device, demonstrating that it is valid and reliable for measuring distance, speed and acceleration during sport-specific movements.

This study assessed the concurrent validity and between-device reliability of the Catapult Vector S8 GNSS device for measuring distance, speed, acceleration and banded distance metrics. Twelve male sub-elite team sport athletes completed a testing protocol consisting of linear sprints, change of direction drills and a modified small-sided game. Validity was evaluated against criterion reference systems, a VICON motion capture system for most trials and a Stalker ATS radar for 50 m sprints, evaluated using root mean square error (RMSE) and mean bias. Between-device reliability was assessed using interclass correlation coefficients (ICC) and typical error (TE%). The Vector S8 demonstrated good validity with minimal errors for instantaneous distance (RMSE: 0.03 ± 0.01 m), speed (RMSE: 0.14 ± 0.05 m⸱s ^-1 ) and acceleration (RMSE: 0.29 ± 0.14 m⸱s ^-2 ). No overall bias was detected for instantaneous distance and speed, and the bias for acceleration (-0.016) was minimal. Accumulated distance showed a small underestimation across trials (mean bias -1.42%), with consistently low RMSE values (0.26-3.06 m), indicating high measurement precision. The 50 m sprint results showed similar validity, with minimal RMSE for instantaneous speed (0.14 ± 0.15 m⸱s ^-1 ) and acceleration (0.22 ± 0.22 m⸱s ^-2 ). Between device reliability demonstrated excellent agreement across all measured variables (ICC ≥ 0.90) with good precision (TE as CV 0.05). This is the first study to validate the Catapult Vector S8 GNSS device, demonstrating that it is valid and reliable for measuring distance, speed and acceleration during sport-specific movements.