There is interest in the accuracy and inter‐unit reliability of position‐tracking systems to monitor players. Research into this technology, although relatively recent, has grown exponentially in the last years, and it is difficult to find professional team sport that does not use Global Positioning System (GPS) technology at least. The aim of this study is to know the accuracy of both GPS‐based and Ultra Wide Band (UWB)‐based systems on a soccer field and their inter‐ and intra‐unit reliability. A secondary aim is to compare them for practical applications in sport science. Following institutional ethical approval and familiarization, 10 healthy and well‐trained former soccer players (20 ± 1.6 years, 1.76 ± 0.08 cm, and 69.5 ± 9.8 kg) performed three course tests: (i) linear course, (ii) circular course, and (iii) a zig–zag course, all using UWB and GPS technologies. The average speed and distance covered were compared with timing gates and the real distance as references. The UWB technology showed better accuracy (bias: 0.57–5.85%), test–retest reliability (%TEM: 1.19), and inter‐unit reliability (bias: 0.18) in determining distance covered than the GPS technology (bias: 0.69–6.05%; %TEM: 1.47; bias: 0.25) overall. Also, UWB showed better results (bias: 0.09; ICC: 0.979; bias: 0.01) for mean velocity measurement than GPS (bias: 0.18; ICC: 0.951; bias: 0.03).

The availability of critical information about training and competition is fundamental on performance. Principal components analysis (PCA) is widely used in sports as a multivariate technique to manage big data from different technological assessments. This systematic review aimed to explore the methods reported and statistical criteria used in team’s sports science and to propose a criteria standard to report PCA in further applications. A systematic electronic search was developed through four electronic databases and a total of 45 studies were included in the review for final analysis. Inclusion criteria: (i) of the studies we looked at, 22.22% performed factorability processes with different retention criteria (r > 0.4–0.7); (ii) 21 studies confirmed sample adequacy using Kaiser-Meyer-Olkim (KMO > 5–8) and 22 reported Bartlett’s sphericity; (iii) factor retention was considered if eigenvalues >1–1.5 (n = 29); (iv) 23 studies reported loading retention (>0.4–0.7); and (v) used VariMax as the rotation method (48.9%). A lack of consistency and serious voids in reporting of essential methodological information was found. Twenty-one items were selected to provide a standard quality criterion to report methods sections when using PCA. These evidence-based criteria will lead to a better understanding and applicability of the results and future study replications.

The purpose of this study was to assess the accuracy of positional data and the inter-unit reliability of an ultra-wide-band (UWB) tracking system. Four well-trained males performed five courses designed for the analysis of x- and y-coordinate accuracy analysis, specifically related to the positional distance variation between the UWB data and the fixed reference lines of a basketball court. This was achieved using geographic information system (GIS) mapping software that calculated, for each interval and participant, the distance from the main axis of displacement and from the opposite side of the court each 0.5 s (x and y coordinate). The accuracy of the results was satisfactory, with a mean absolute error of all estimations for the x-position of 5.2 ± 3.1 cm and for the y-position of 5.8 ± 2.3 cm. Regarding inter-unit reliability, the intra-class correlation coefficient (ICC) value was high for the x-coordinate (0.65) and very high for the y-coordinate (0.85). The main findings of the study were: (i) The accuracy of UWB tracking systems can be considered suitable for practical applications in sport analyses; (ii) position estimations are very precise and acceptable for tactical analyses; (iii) the error of the position estimations does not change significantly across different courses; and (iv) the use of different devices does not significantly affect the measurement error.

Accelerometry is a recent method used to quantify workload in team sports. A rapidly increasing number of studies supports the practical implementation of accelerometry monitoring to regulate and optimize training schemes. Therefore, the purposes of this study were: (1) to reflect the current state of knowledge about accelerometry as a method of workload monitoring in invasion team sports according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, and (2) to conclude recommendations for application and scientific investigations. The Web of Science, PubMed and Scopus databases were searched for relevant published studies according to the following keywords: “accelerometry” or “accelerometer” or “microtechnology” or “inertial devices”, and “load” or “workload”, and “sport”. Of the 1383 studies initially identified, 118 were selected for a full review. The main results indicate that the most frequent findings were (i) devices’ body location: scapulae; (b) devices brand: Catapult Sports; (iii) variables: PlayerLoad^TM and its variations; (iv) sports: rugby, Australian football, soccer and basketball; (v) sex: male; (vi) competition level: professional and elite; and (vii) context: separate training or competition. A great number of variables and devices from various companies make the comparability between findings difficult; unification is required. Although the most common location is at scapulae because of its optimal signal reception for time-motion analysis, new methods for multi-location skills and locomotion assessment without losing tracking accuracy should be developed.

Since the accelerating development of technology applied to team sports and its subsequent high amount of information available, the need for data mining leads to the use of data reduction techniques such as Principal Component Analysis (PCA). This systematic review aims to identify determinant variables in soccer, basketball and rugby using exploratory factor analysis for, training design, performance analysis and talent identification. Three electronic databases (PubMed, Web of Science, SPORTDiscus) were systematically searched and 34 studies were finally included in the qualitative synthesis. Through PCA, data sets were reduced by 75.07%, and 3.9 ± 2.53 factors were retained that explained 80 ± 0.14% of the total variance. All team sports should be analyzed or trained based on the high level of aerobic capacity combined with adequate levels of power and strength to perform repeated high-intensity actions in a very short time, which differ between team sports. Accelerations and decelerations are mainly significant in soccer, jumps and landings are crucial in basketball, and impacts are primarily identified in rugby. Besides, from these team sports, primary information about different technical/tactical variables was extracted such as (a) soccer: occupied space, ball controls, passes, and shots; (b) basketball: throws, rebounds, and turnovers; or (c) rugby: possession game pace and team formation. Regarding talent identification, both anthropometrics and some physical capacity measures are relevant in soccer and basketball. Although overall, since these variables have been identified in different investigations, further studies should perform PCA on data sets that involve variables from different dimensions (technical, tactical, conditional).

The aims of this study were to: (1) identify the representative external load profile of match‐play in Spanish professional soccer players by principal components analysis (PCA), and (2) analyse the effect of match location (home vs away), match outcome (win vs draw vs loss) and length of the microcycle (5 vs 6 vs 7 vs 8 vs 9 days) on the external load profile. Data were collected during one season consisting of 42 matches in LaLiga 123 and 11 external load variables were selected after the PCA. TD, total distance covered; DIS_0–6: distance from 0 to 6 km/h; DIS_21–24: distance from 21 to 24 km/h; HSRD: high‐speed running distance above 21 km/h; HSRA: total of high‐speed running actions above 21 km/h; V _MAX: maximum speed in km/h; Sprints: total of actions above 24 km/h; ACC: total of accelerations; ACC_G‐avg: average accelerometer G‐force; ACC_MAX: maximum acceleration (m/s2); DEC_MAX: maximum deceleration (m/s²). Match location had an impact on HSRD (p < 0.01; ES = 0.05), DIS_0–6 (p < 0.01; ES = 0.05), and ACC_MAX (p < 0.01; ES = 0.05). Match outcome had a relation to TD (p < 0.01; ES = 0.05), DIS_0–6 (p < 0.01; ES = 0.05) and HSRD (p < 0.01; ES = 0.05). Length of the microcycle had an impact on TD (p < 0.01; ES = 0.05), DIS_0–6 (p < 0.01; ES = 0.11), ACC (p < 0.01; ES = 0.04) and V_MAX (p < 0.01; ES = 0.04). This study provides coaches a selection of variables for match‐play analysis, which could represent two‐thirds of external load profile. Then, professionals should consider that these contextual variables could have an impact on the external load profile.