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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 aim of the review was to identify the spatial tactical variables used to assess the use of space in team sports using positional data. In addition, we examined computational methods, performed a critical assessment and suggested future considerations. We considered four electronic databases. A total of 3973 documents were initially retrieved and only 15 articles suggested original spatial variables or different computation methods. Spatial team sport tactical variables can be classified into 3 principal types: occupied space, total field coverage by several players; exploration space, the mean location (+/- standard deviations in X- and Y-directions) of the player/team during the entire game; and dominant/influence space, the region the players can reach before any other players. Most of the studies, i.e., 55%, did not include goalkeepers (GKs) and total playing space to assess occupied space, however, several proposed new variables that considered that all playing space could be "played" (i.e. effective free-space, normalized surface area). Only a collective exploration space variable has been suggested: the major range of the geometrical centre (GC). This suggestion could be applied to assess collective exploration space variables at a sub-system level. The measurement of the dominant/influence space has been based on the Voronoi region (i.e. distance d criteria), but several studies also based their computation on the time (t). In addition, several weighted dominant areas have been suggested. In conclusion, the use of spatial collective tactical variables considering the principal structural traits of each team sport (e.g. players of both teams, the location of the space with respect to the goal, and the total playing space) is recommended

Ultra-wide band (UWB) based local positioning systems (LPS) are based on devices and a portable antenna set. The optimal installation height of the antennae is crucial to ensure data accuracy. Collective variables are metrics that consider at least two pairs of coordinates, which may lead to lower precision than an individual one. Therefore, the aim of this study was to compare the influence of antenna height with collective metrics using a UWB (i.e., IMU; WIMU PRO™, RealTrack Systems, Almeria, Spain) based LPS. Data acquisition was carried out in a basketball court measuring 28 × 15 m. Five devices were used; one of which was carried by a healthy and well-trained athlete (age: 38 years, mass: 76.34 kg, height 1.70 m), while each of the remaining four was positioned on a tripod in one of the four corners of the court. Four kinds of variables were extracted: (1) static distances, (2) dynamic distances, (3) static areas and (4) dynamic areas in all antenna installation modes of 0.15, 1.30 and 2.00 m. The results showed that the antenna of 1.30 m provided better accuracy for all measures (% difference range from −0.94 to 1.17%) followed by the antenna of 2.00 m (% difference range from −2.50 to 2.15%), with the antenna of 0.15 m providing the worst accuracy level (% difference range from −1.05 to 3.28%). Overall, the measurements of distance metrics showed greater accuracy than area metrics (distance % difference range from −0.85 to 2.81% and area % difference range from −2.50 to 3.28). In conclusion, the height of the antennae in basketball courts should be similar to the height at which the devices are attached to a player’s upper back. However, as the precision is sensitive to the magnitude of the measure, further studies should assess the effects of the relative height of antennae in team sports with greater playing spaces.

Background: Consistent evidence suggests that exercise improves cognition and decision making, with preliminary evidence suggesting that brain-derived neurotrophic factors (BDNFs) may mediate these effects on high-intensity interval activities, such as in football playing. We conducted a systematic review of studies on football players or football task interventions that evaluated the causality of exercise or its relationship with changes in the basal BDNF level. Methods: The search was conducted in PubMed, SPORTDiscus, Cochrane, and FECYT (Web of Sciences, CCC, DIIDW, KJD, MEDLINE, RSCI, and SCIELO) according to the guidelines for performing systematic reviews in the sport sciences field. Results: From the 44 studies initially identified, seven studies were fully reviewed, and their outcome measures were extracted and analysed. In the scientific study of football, the studies published thus far have explored the relationship of serum BDNF levels and other cognitive function factors with the genetic expression of polymorphisms, the anthropometric and fitness conditions, the acute exercise effect of the match, and the typical actions of the match such as heading. Conclusions: The heterogeneity of designs and variables evaluated in studies related to BDNF exercise or interaction and football playing does not allow us to conclusively determine that there is a relationship with the cause or effect of genetic, anthropometric, or conditional factors that derive from an increase in BDNF due to actions during the playing of football.

The purpose of this study was to analyze the external and internal load of Costa Rican handball referees according to sex and game periods. Nine referees (6 men and 3 women) were monitored during U19 handball matches, using an ultra-wide band local positioning system (UWB) and WIMUPro™ inertial units (IMU). The results showed a total distance of 4566.54±494.02 m (46.95% at 0-6 km/h, 32.97% at 6-12 km/h, 18.11% at 12-18 km/h and 1.96% >18 km/h). 1298.34±151.42 m/s2 accelerations and 1297.73±152.09 m/s2 decelerations were performed. Maximal speed was 19.63±1.85 km/h and average speed was 4.80±0.34 km/h. Player LoadRT was 50.53±9.39 UA. Maximal and average heart rate was 170.59±18.20 bpm 143.06±16.94 bpm respectively. 60% of the efforts were <80% of maximum heart rate. Total energy expenditure was 372.34±67.80 kcal. No significant differences were found in physiological variables between sexes, although men covered greater distance at 0-6 km/h. In the second periods the total distance (m/min), distance at 6-12 km/h, 12-18 km/h (m/min) and >18 km/h, average speed, impacts at 3-5g and >5g, Player LoadRT, and energy expenditure decreased. In conclusion, sex does not seem to affect the external or internal load, while the game period influenced on the external load, El propósito de este estudio fue analizar la carga externa e interna de árbitros costarricenses de balonmano según sexo y periodos de juego. Nueve árbitros (6 hombres y 3 mujeres) fueron monitoreados durante partidos de balonmano Sub-19, utilizando un sistema de posicionamiento local de banda ultra ancha (UWB) y unidades inerciales WIMUPro™(IMU). Los resultados mostraron una distancia total de 4566.54±494.02 m (46,95% a 0-6 km/h, 32,97% a 6-12 km/, 18,11% a 12-18 km/h y 1,96% a >18 km/h. Se realizaron 1298.34±151.42 m/s2 aceleraciones y 1297.73±152.09 m/s2 desaceleraciones. La velocidad máxima fue 19.63±1.85 km/h y la velocidad promedio fue 4.80±0.34 km/h. Player LoadRT fue 50.53±9.39 UA. La frecuencia cardíaca máxima y promedio fueron 170.59±18.20 lpm y 143.06±16.94 lpm respectivamente. El 60% de los esfuerzos fueron <80% de la frecuencia cardíaca máxima. El gasto energético total fue 372.34±67.80 kcal. No hubo diferencias significativas en variables fisiológicas entre sexos, aunque los hombres recorrieron mayor distancia a 0-6 km/h. En los segundos periodos la distancia total (m/min), distancia a 6-12 km/h, 12-18 km/h (m/min) y >18 km/h, velocidad media, impactos a 3-5 g y > 5g, Player LoadRT y gasto energético disminuyeron. En conclusión, el sexo no parece afectar la carga externa o interna, mientras que el periodo de juego sí influyó en la carga externa.

An association between accelerometer workload and injury risk has been found previously. However, any research has assessed the absorption dynamics of external workload through the measurement in different anatomical locations simultaneously. A cross-sectional study was designed to: (i) to describe the multi-joint external workload profile of youth soccer players, (ii) to identify between-participant differences related to anatomical locations, (iii) to analyze the workload dynamics at different speeds at joints and body segments, (iv) to characterize the multi-joint individual workload and the within-participant difference in each body segment. Twenty-one U-18 male players, that were part of a Youth Spanish First Division soccer team, performed an incremental running treadmill test and wore four WIMU PROTM inertial devices in lower limb (ankle-knee) and spine (lower-upper back) locations to register cumulative tri-axial accelerometry-based workload (PlayerLoad, PLRT). The main results have shown that the highest PLRT was detected at the lower limb, especially at the ankle. Different dynamics of accelerometer workload have been found between lower and upper limb, being them between ankle-knee at 12-km/h and lower-upper back at 9.5-km/h (p<.05). Between-participants’ differences were shown at all joints, finding the highest differences at the upper back (p<.01; d=2.17). Finally, the body segment knee-lower back reported the highest differences (%diff=34.25-to-67.28; d=2.20-to-4.77). In conclusion, a great between-participants external workload variability was found at joints and body segments, being recommended for an individualized assessment and specific training protocols., Una asociación entre la carga acelerometría y el riesgo de lesión ha sido encontrada previamente. Sin embargo, no existen investigaciones que evalúen la dinámica de absorción de carga externa a través de diferentes ubicaciones anatómicas simultáneamente. Un estudio transversal fue diseñado para: (i) describir el perfil multi-ubicación de carga externa en jugadores jóvenes de fútbol, (ii) identificar diferencias entre sujetos relacionadas con las ubicaciones anatómicas, (iii) analizar la dinámica de carga a diferentes velocidades en diferentes ubicaciones anatómicas y segmentos corporales, (iv) caracterizar el perfil multi-ubicación individual y las diferencias intra-sujeto en cada segmento corporal. 21 jugadores masculinos U-18 que pertenecían a un equipo de fútbol de Primera División Nacional Juvenil realizaron un test incremental en tapiz rodante portando cuatro dispositivos inerciales WIMU PROTM en diferentes ubicaciones del tren inferior (rodilla-tobillo) y columna (espalda alta y baja) para registrar la carga acelerométrica tri-axial acumulada (PlayerLoad, PLRT). Los principales resultados muestran que el mayor PLRT fue detectando en el tren inferior, especialmente en el tobillo. Diferentes dinámicas de carga acelerométrica han sido encontrados entre el tren inferior y el tren superior, siendo estas diferencias entre tobillo-rodilla a 12 km/h y entre espalda alta-baja a 9.5 km/h (p<.05). Diferencias inter-sujeto fueron encontradas en todas las ubicaciones, encontrando las mayores diferencias en la espalda alta (p<.01; d=2.17). Finalmente, el segmento corporal rodilla-espalda baja reportó las mayores diferencias (%diff=34.25-to-67.28; d=2.20-to-4.77). En conclusión, una alta variabilidad inter-sujeto en la carga externa registrada fue encontrada en todas las ubicaciones y segmentos corporales, siendo recomendable su individualización y entrenamiento específico.

Principal Component Analysis (PCA) has not been used to assess the principal component (PC) of players´ external training loads (TL) in futsal. In addition, no previous study has analyzed the PC of players´ external TL depending on the half of the match in futsal. Thus, this study aimed to assess the PC of players´ external TL considering an entire official futsal match distinguishing by halves (1st and 2nd halves). Two teams of twelve amateur futsal players (Spanish 3rd division) participated in the final match of the futsal cup and external TL was quantified using eight antennas ultra-wideband technology. Through PCA statistical analysis, 10 variables formed the 10 PC. Specifically, three PC for the entire match, four for the 1st half, and three for the 2nd half were extracted. Considering the match as a whole, three PC explained the players´ external TL formed by eight variables: distance covered (m/min), distance covered at high speed running (m/min), distance covered at explosive speed (m/min), total accelerations (n/min), total decelerations between 2-1 m/s/s (n/min), distance covered at 24-50 km/h (m/min), total impacts between 8-100g (n/min) and Jumps performed (n/min). The PC variables differed between halves: a) in the 1st half 74.5% was explained by four PC composed of 8 variables in total, and b) in the 2nd half 67.6% was explained by three PC. The results suggest that the use of only one PC could potentially lead to an underestimation of the external TL demands in futsal matches. It seems that a combination of 3-4 PC from a total of 8 to 10 variables are required to explain senior amateur futsal official games. In addition, the match half should be considered to assess the external TL in team sports., El análisis de componentes principales (ACP) no se ha utilizado para conocer los componentes principales (CP) de las cargas de entrenamiento (CE) de los jugadores en fútbol sala. Además, no se han publicado estudios que analicen los CP de la CE de los jugadores en función del período de juego en fútbol sala. Por lo tanto, este estudio tuvo como objetivo evaluar los CP de la CE de los jugadores considerando un partido de fútbol sala oficial diferenciando por períodos. Dos equipos de doce jugadores amateurs de fútbol sala (3a división española) participaron en una final de la copa de fútbol sala. A través del análisis estadístico de CP, 10 variables formaron los 10 CP. Concretamente, se extrajeron 3 CP para el partido en su totalidad, 4 para el primer período y 3 para el segundo período. Considerando el partido como un todo, 3 CP formados por 8 variables explicaron la CE de los jugadores: Distancia cubierta (m / min), carrera a alta velocidad (m / min), distancia recorrida a velocidad explosiva (m / min), número de aceleraciones totales (n / min), número de desaceleraciones de 2 a 1 m/s (n / min), distancia cubierta de 24 a 50 km/h (m / min), impactos 8-100g (n / min) y saltos (n / min). Las variables de los CP diferían entre períodos: a) en el primer período, 4 CP explicaron el 74.5% de la CE de los jugadores, mientras que b) en el segundo período, 3 CP explicaron el 67.6%. Los resultados sugirieron que el uso de un solo CP podría conducir a una subestimación de las demandas de CE en los partidos de fútbol sala. Parece que se requiere una combinación de 3-4 CP formados por un total de 8 variables para explicar los partidos oficiales de fútbol sala amateur. Además, se debe considerar el ACP por períodos para evaluar el CE en los deportes de equipo.