The purpose of this study was to assess the measurement accuracy of the most commonly used tracking technologies in professional team sports (i.e., semi-automatic multiple-camera video technology (VID), radar-based local positioning system (LPS), and global positioning system (GPS)). The position, speed, acceleration and distance measures of each technology were compared against simultaneously recorded measures of a reference system (VICON motion capture system) and quantified by means of the root mean square error RMSE. Fourteen male soccer players (age: 17.4±0.4 years, height: 178.6±4.2 cm, body mass: 70.2±6.2 kg) playing for the U19 Bundesliga team FC Augsburg participated in the study. The test battery comprised a sport-specific course, shuttle runs, and small sided games on an outdoor soccer field. The validity of fundamental spatiotemporal tracking data differed significantly between all tested technologies. In particular, LPS showed higher validity for measuring an athlete’s position (23±7 cm) than both VID (56±16 cm) and GPS (96±49 cm). Considering errors of instantaneous speed measures, GPS (0.28±0.07 m⋅s-1) and LPS (0.25±0.06 m⋅s-1) achieved significantly lower error values than VID (0.41±0.08 m⋅s-1). Equivalent accuracy differences were found for instant acceleration values (GPS: 0.67±0.21 m⋅s-2, LPS: 0.68±0.14 m⋅s-2, VID: 0.91±0.19 m⋅s-2). During small-sided games, lowest deviations from reference measures have been found in the total distance category, with errors ranging from 2.2% (GPS) to 2.7% (VID) and 4.0% (LPS). All technologies had in common that the magnitude of the error increased as the speed of the tracking object increased. Especially in performance indicators that might have a high impact on practical decisions, such as distance covered with high speed, we found >40% deviations from the reference system for each of the technologies. Overall, our results revealed significant between-system differences in the validity of tracking data, implying that any comparison of results using different tracking technologies should be done with caution.

The present study aimed to validate and compare the football-specific measurement accuracy of two optical tracking systems engineered by TRACAB. The "Gen4" system consists of two multi-camera units (a stereo pair) in two locations either side of the halfway line, whereas the distributed "Gen5" system combines two stereo pairs on each side of the field as well as two monocular systems behind the goal areas. Data were collected from 20 male football players in two different exercises (a football sport-specific running course and smallsided games) in a professional football stadium. For evaluating the accuracy of the systems, measures were compared against simultaneously recorded measures of a reference system (VICON motion capture system). Statistical analysis uses RMSE for kinematic variables (position, speed and acceleration) and the difference in percentages for performance indicators (e.g. distance covered, peak speed) per run compared to the reference system. Frames in which players were obviously not tracked were excluded. Gen5 had marginally better accuracy (0.08 m RMSE) for position measurements than Gen4 (0.09 m RMSE) compared to the reference. Accuracy difference in instantaneous speed (Gen4: 0.09 m�s-1 RMSE; Gen5: 0.08 m�s-1 RMSE) and acceleration (Gen4: 0.26 m�s-2 RMSE; Gen5: 0.21 m�s-2 RMSE) measurements were significant, but also trivial in terms of the effect size. For total distance travelled, both Gen4 (0.42 ± 0.60%) and Gen5 (0.27 ± 0.35%) showed only trivial deviations compared to the reference. Gen4 showed moderate differences in the low-speed distance travelled category (-19.41 ± 13.24%) and small differences in the high-speed distance travelled category (8.94 ± 9.49%). Differences in peak speed, acceleration and deceleration were trivial (<0.5%) for both Gen4 and Gen5. These findings suggest that Gen5's distributed camera architecture has minor benefits over Gen4's single-view camera architecture in terms of accuracy. We assume that the main benefit of the Gen5 towards Gen4 lies in increased robustness of the tracking when it comes to optical overlapping of players. Since differences towards the reference system were very low, both TRACAB's tracking systems can be considered as valid technologies for football-specific performance analyses in the settings tested as long as players are tracked correctly.

This study explores whether positioning systems are a viable alternative to timing gates when it comes to measuring sprint times in ice hockey. We compared the results of a single-beam timing gate (Brower Timing) with the results of the Iceberg optical positioning system (Optical) and two radio-based positioning systems provided by InMotio (Radio 1) and Kinexon (Radio 2). The testing protocol consisted of two 40 m linear sprints, where we measured sprint times for a 11 m subsection (Linear Sprint 11), and a shuttle run (Shuttle Total), including five 14 m sprints. The exercises were performed by six top-level U19 field players in regular ice hockey equipment on ice. We quantified the difference between measured sprint times e.g., by Mean Absolute Error (MAE) (s) and Intra Class Correlation (ICC). The usefulness of positioning systems was evaluated by using a Coefficient of Usefulness (CU), which was defined as the quotient of the Smallest Worthwhile Change (SWC) divided by the Typical Error (both in s). Results showed that radio-based systems had a higher accuracy compared to the optical system. This concerned Linear Sprint 11 (MAEOptical = 0.16, MAERadio1 = 0.01, MAERadio2 = 0.01, ICCOptical = 0.38, ICCRadio1 = 0.98, ICCRadio2 = 0.99) as well as Shuttle Total (MAEOptical = 0.07, MAERadio1 = 0.02, MAERadio2 = 0.02, ICCOptical = 0.99; ICCRadio1 = 1.0, ICCRadio2 = 1.0). In Shuttle Total, all systems were able to measure a SWC of 0.10 s with a probability of >99% in a single trial (CUOptical = 4.6, CURadio1 = 6.5, CURadio2 = 5.1). In Linear Sprint 11 an SWC of 0.01 s might have been masked or erroneously detected where there were none due to measurement noise (CUOptical = 0.6, CURadio1 = 1.0, CURadio2 = 1.0). Similar results were found for the turning subsection of the shuttle run (CUOptical = 0.6, CURadio1 = 0.5, CURadio2 = 0.5). All systems were able to detect an SWC higher than 0.04 s with a probability of at least 75%. We conclude that the tested positioning systems may in fact offer a workable alternative to timing gates for measuring sprints times in ice hockey over long distances like shuttle runs. Limitations occur when testing changes/differences in performance over very short distances like an 11 m sprint, or when intermediate times are taken immediately after considerable changes of direction or speed.

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