Systematic Observation of Corner Kick Strategies in Portuguese Football Players

Set pieces are important for the success of football teams, with the corner kick being one of the most game defining events. The aim of this research was twofold: (1) to analyze the corner kicks of a senior football amateur team, and (2) to compare the corner kicks of successful and unsuccessful teams (of the 2020/21 sporting season). In total, 500 corners were observed using a bespoke notational analysis tool, using a specific observational instrument tool (8 criteria; 25 categories). Out of the 500 corner kicks, 6% resulted in a goal. A greater number of direct corners using inswing trajectories were performed (n = 54%). Corners were delivered to central and front post areas most frequently (n = 79%). Five attackers were most predominantly used for offensive corners (n = 58%), but defenders won the ball more frequently (n = 44%). Attempts at goal occurred following a corner most commonly from outside of the box (n = 7%). Goals were scored most frequently with the foot (n = 16%) and head (n = 15%). Successful teams are more effective at reaching the attackers and score more goals directly from corners. Unsuccessful teams deliver more corner kicks out of play, the first touch is more frequently from the opposition defenders, and fewe goals are scored from corner kicks. The study provides an insight into the determining factors and patterns that influence corner kicks and success in football matches. This information should be used by coaches to prepare teams for both offensive and defensive corner kicks to increase team success and match outcomes.

Shot Characteristics Based on Match Period in Elite Table Tennis Matches

This study aimed to compare the shot characteristics amongst different match periods in table tennis matches. For the shot characteristics of position, type, placement and efficacy, 13 men’s singles matches comprising 72 sets from a round of 16 to the final in the 2019 World Table Tennis Championships were selected for notational analysis. Kruskal–Wallis and Mann–Whitney tests were conducted to quantify the differences in various categories of each variable amongst the initial, intermediate and ending match periods. There are no significant differences in each distribution between initial and intermediate periods. From intermediate to ending periods, significant decreases were found in chop type (p < 0.01) and middle long placement (p < 0.01), whereas a significant increase was found in backhand half placement (p < 0.05). By comparing the initial and ending periods, significant decreases were found in middle backhand turn position (p < 0.05), middle long placement (p < 0.01), chop (p < 0.01), and poor shots (p < 0.05). Therefore, shot characteristics in table tennis matches are match period related, and the main differences existed between the beginning and the ending period. From initial to ending period, the frequency of applying the middle long placements is decreasing. At the end of every set, the players adopted a safe stroke position, performed offensive stroke types and deployed flexible stroke placement. Results suggested that coaches can establish different scenarios on the basis of varying match periods for players’ training.

A Random Forest approach to identify metrics that best predict match outcome and player ranking in the esport Rocket League

Notational analysis is a popular tool for understanding what constitutes optimal performance in traditional sports. However, this approach has been seldom used in esports. The popular esport “Rocket League” is an ideal candidate for notational analysis due to the availability of an online repository containing data from millions of matches. The purpose of this study was to use Random Forest models to identify in-match metrics that predicted match outcome (performance indicators or “PIs”) and/or in-game player rank (rank indicators or “RIs”). We evaluated match data from 21,588 Rocket League matches involving players from four different ranks. Upon identifying goal difference (GD) as a suitable outcome measure for Rocket League match performance, Random Forest models were used alongside accompanying variable importance methods to identify metrics that were PIs or RIs. We found shots taken, shots conceded, saves made, and time spent goalside of the ball to be the most important PIs, and time spent at supersonic speed, time spent on the ground, shots conceded and time spent goalside of the ball to be the most important RIs. This work is the first to use Random Forest learning algorithms to highlight the most critical PIs and RIs in a prominent esport.

How football team composition constrains emergent individual and collective tactical behaviours: Effects of player roles in creating different landscapes for shared affordances in small-sided and conditioned games

The aim of the present study was to examine how team composition of players with different roles constrains individual and collective tactical behaviours, and ball possession effectiveness, during competitive 3 vs 3 small-sided and conditioned games (SSCGs) in youth soccer players. Fifteen male players (under 15 yrs, mean age 13.2 ± 1.03 years, mean years of practice: 4.2 ± 1.10 years) from the same club participated in this study. For analysis purposes, on advice from the coaching staff, participants were categorised according to their main team performance role, resulting in sub-samples of 5 defenders (centre-backs = 2 and full- backs = 3), 7 midfielders (central midfielders = 3 and wide midfielders = 4) and 3 attackers (forwards). In order to assess participant tactical behaviours, a notational analysis system was created with four categories: i) team behaviours, ii) individual players’ offensive actions, iii) individual players’ defensive actions, and iv), ball possession effectiveness. Analysis of players’ offensive actions revealed that the team composed only of midfielders revealed a higher frequency of diagonal and vertical passes in relation to the attackers’ team. In offensive individual actions, the attackers’ team revealed more dribbles in relation to the teams of defenders and midfielders. Analysis of ball possession effectiveness revealed that the team of defenders achieved higher values of shots on goal compared to the team of midfielders. These findings exemplified how playing role constrains the emergence of different collective behaviours and individual actions in 3 vs 3 SSCGs.

Effects of Congested Fixture on Men’s Volleyball Load Demands: Interactions with Sets Played

The purpose of this study was to compare the external load, internal load, and technical efficacy between the first and the second matches (M1 and M2) occurring in congested fixtures (two matches in two days) using the number of sets as a moderating factor. An observational analytic research design was adopted. Data from official volleyball matches were collected during the first competitive period of the championship, comprising 14 competitive games within 10 weeks. Ten male elite volleyball athletes (age: 21.7 ± 4.19 years of age; experience: 6.2 ± 3.8 years; body mass: 85.7 ± 8.69 kg; height: 192.4 ± 6.25 cm; BMI: 23.1 ± 1.40 kg/m2) participated in this study. Players were monitored for external load (number of jumps and height of jumps) and internal load (using the rate of perceived exertion—RPE). Additionally, notational analysis collected information about attack efficacy and receptions made during matches. The mixed ANOVA revealed no significant interaction between time (M1 vs. M2) and number of sets for number of jumps per minute (p = 0.235; ηp2 = 0.114), mean jump height (p = 0.076; ηp2 = 0.193), RPE (p = 0.261; ηp2 = 0.106), attack efficacy (p = 0.346; ηp2 = 0.085), Positive reception (p = 0.980; ηp2 = 0.002) and Perfect reception (p = 0.762; ηp2 = 0.022). In conclusion, congested fixtures do not seem to affect the performance of volleyball players negatively.

A Random Forest approach to identify metrics that best predict match outcome and player ranking in the esport Rocket League

Notational analysis is a popular tool for understanding what constitutes optimal performance in traditional sports. However, this approach has been seldom used in esports. The popular esport “Rocket League” is an ideal candidate for notational analysis due to the availability of an online repository containing data from millions of matches. The purpose of this study was to use Random Forest models to identify in-match metrics that predicted match outcome (performance indicators or “PIs”) and/or in-game player rank (rank indicators or “RIs”). We evaluated match data from 21,588 Rocket League matches involving players from four different ranks. Upon identifying goal difference (GD) as a suitable outcome measure for Rocket League match performance, Random Forest models were used alongside accompanying variable importance methods to identify metrics that were PIs or RIs. We found shots taken, shots conceded, saves made, and time spent goalside of the ball to be the most important PIs, and time spent at supersonic speed, time spent on the ground, shots conceded and time spent goalside of the ball to be the most important RIs. This work is the first to use Random Forest learning algorithms to highlight the most critical PIs and RIs in a prominent esport.

Modelling team performance in soccer using tactical features derived from position tracking data

Decision-makers in soccer routinely assess the tactical behaviour of a team and its opponents both during and after the game to optimize performance. Currently, this assessment is typically driven by notational analysis and observation. Therefore, potential high-impact decisions are often made based on limited or even biased information. With the current study, we aimed to quantitatively assess tactical performance by abstracting a set of spatiotemporal features from the general offensive principles of play in soccer using position tracking data, and to train a machine learning classifier to predict match outcome based on these features computed over the full game as well as only parts of the game. Based on the results of these analyses, we describe a proof of concept of a decision support system for coaches and managers. In an analysis of 302 professional Dutch Eredivisie matches, we were able to train a Linear Discriminant Analysis model to predict match outcome with fair to good (74.1%) accuracy with features computed over the full match, and 67.9% accuracy with features computed over only 1/4th of the match. We therefore conclude that using only position tracking data, we can provide valuable feedback to coaches about how their team is executing the various principles of play, and how these principles are contributing to overall performance.

Analysis of the differences in serve effectiveness between Billie Jean King Cup (former Fed Cup) and Davis Cup doubles tennis matches

The doubles game has considerable relevance in professional tennis, especially in team competitions such as the Billie Jean King Cup (former Fed Cup) (BJKC) and the Davis Cup (DC). However, there are very few studies that have carried out quantitative notational analysis to provide information on the specific features of this tennis modality. The goal of this study was to analyse the differences in serve direction and effectiveness of male and female teams in matches played at BJKC and DC ties. A total of 29,207 serves; 7,578 of BJKC and 21,628 of DC matches were analysed. The data was obtained through the Hawk-Eye system. The results showed that with the first serve, both BJKC and DC teams tried to move the receiver by serving to zones W (wide) and T to take the initiative of the point, while with the second serve teams took lower risks and mainly served to zone B (body). In general, in DC matches the effectiveness of the serve was greater than in BJKC ones. The first serve effectiveness in DC matches was found to be higher in each direction, while the differences in the effectiveness of the second serve was only found in the zone C (body) of the advantage service box. This information can be particularly relevant for coaches to design the doubles training sessions and the strategic planning of doubles matches on reliable and quantitative information.

Notational analysis in female grand slam tennis competitions

Grand Slam tennis tournaments are played on different surfaces. The aims of the present study were to analyse the technical differences in the Grand Slam tournaments (Australian Open or AO, Roland Garros or RG, Wimbledon or W, and the United States Open or US), as well as to establish differences between winning and losing players. A total of 580 sets in 248 matches played in Grand Slams between 2017 and 2018 were analysed. To observe differences between the tournaments, a one-way analysis of variance (Kruskal Wallis) with the Bonferroni post-hoc test was performed. Univariate (Wilcoxon test) analysis of data was carried out to show the differences between the winning and losing performances of sets. Players who had more aces, points won on the 1st serve, winning shots and net points won more matches in the AO, W and US than in the RG (p<.05). However, in RG, players won more receiving points (43.56% of the points played) with chances to break the opponents’ service game. The results also showed that the winning players were superior in both service and receiving, and the most influential variables on the outcome of the match were percentage of receiving points won, break points won, and percentage of points won on the first serve. Such knowledge may have implications in the design of appropriate game strategies and specific training sessions to improve performance in professional women’s tennis.