The tactical role of return height in tennis rallies has been largely overlooked in existing research, which tends to focus on placement or overall outcomes. This study addresses this gap by developing a machine learning based decision model to optimize return height in prolonged rallies. Using data from seven matches of the 2024 Australian Open Men’s Singles Champion, 7,200 shot-level records were extracted and analyzed. Three algorithms—support vector machine (SVM), artificial neural network (ANN), and random forest (RF)—were applied to predict optimal return heights, with RF achieving the highest accuracy (84.5%) and F1-score (94.0%). Furthermore, a personalized model incorporating K-means clustering improved accuracy to 81.2% for specific player styles. Feature importance and sensitivity analysis confirmed that return height is a key tactical determinant. This study contributes a data-driven framework for analyzing return strategy in tennis and provides practical implications for coaching, player training, and real-time tactical support.

Although both unresisted sprint training (UST) and resisted sprint training (RST) are widely used in rugby and other team sports, evidence comparing their specific effects on neuromuscular adaptations and strength-related measures is still limited. This study aimed to analyze the effects of two sprint training programs-UST and RST, using 50% of body mass-on secondary outcome measures and force-time characteristics obtained from the squat one-repetition maximum (squat 1RM-strength), associated strength deficits (SDef from 40% to 90% 1RM), isometric squat, Nordic hamstring exercise (NHE), and jump performance in youth rugby players. Thirty-five under-19 male rugby players (age: 17.3 ± 0.9y) volunteered to participate in the study. Players completed the following assessments: (1)UST during a 30-m sprint; (2)isometric squat and squat 1RM-strength; and (3)hamstring eccentric strength via the NHE and countermovement jump tests. Only the UST group showed moderate improvements in 30-m sprint speed (ES = -0.77, 95% CI, -1.43 to 0.07, P < .05). In the isometric squat, both groups demonstrated small-to-moderate increases in force at 200 milliseconds (ES = -0.83 to -0.64, P < .05). In the NHE, the RST group showed large increases in torque and average force across both legs (P < .001, ES = -1.73 to -1.28). Similarly, in the UST group, large increases were observed in NHE average force across both legs (P ≤ .008, ES = -0.99 to -0.92), while NHE impulse was moderately reduced only in the right leg (ES = 0.71, 95% CI, 0.06 to 1.33, P = .031). Our findings indicate that both UST and RST can be effectively implemented during short in-season periods to maintain sprint performance and strength-related capacities in youth rugby players, especially when time for resistance training is limited or cannot be prioritized. Coaches may therefore select either method according to the specific context, time constraints, and player needs.

Adjusting the design of small-sided games and selecting the appropriate format can significantly enhance training outcomes and player development in soccer. The aim of the study was to compare the effects of intermittent small-sided games (ISSG) and continuous small-sided games (CSSG) on athletic performance metrics in male soccer players. This pilot study was conducted using a parallel group pre-test and post-test design, with 16 male youth soccer players randomly assigned to two groups: the ISSG group (n = 8, Mean age = 16.50 ± 0.53 years) and the CSSG group (n = 8, Mean age = 16.63 ± 0.52 years), ensuring a balance in pre-test performance and playing positions. The ISSG protocol began with 4 min sets in week one, progressively increasing to 7 min by week four, with 2 min rest intervals. The CSSG protocol involved continuous play, starting at 16 min and progressing to 28 min over the same period. Players underwent pre- and post-tests, with a 4-week training period. Performance metrics assessed included body composition, a 30 m sprint test, agility, horizontal jump, aerobic and anaerobic capacity, and static balance. Training intensity was monitored using the CR-10 Borg Rating of Perceived Exertion scale throughout the training period. Both groups exhibited improvements in horizontal jump, agility, aerobic and anaerobic power, and static balance, with no significant between-group differences. Sprint performance did not significantly improve in either group. The CSSG group reported higher RPE values and experienced a reduction in body mass index. Our findings demonstrate that both ISSG and CSSG resulted in similar improvements in athletic performance metrics in male youth soccer players. Coaches and practitioners can choose the most appropriate training method based on specific objectives, session duration, and player fatigue levels, thereby optimizing training outcomes.

ABSTRACT The analysis of technical-tactical performance in women’s football has begun to develop exhaustively in recent years, and it must be further identified in the years to come. The objective of this study was to develop and train a segmentation algorithm capable of classifying pass-type event data based on technical-tactical indicators, and to interpret the trends and playing styles of national teams in the FIFA Women’s World Cup 2023 through the clustering and data visualisation techniques. A cross-sectional descriptive design was used to collect 227,393 observations from the 64 matches played in the FIFA Women’s World Cup 2023. The passes were segmented into 5 groups using a K-means algorithm and interpreted using a multivariate descriptive decision tree analysis. The results were visualised through frequency distributions and specific graphics displaying the start and end coordinates of passes on the field. The findings revealed differences in the types of passes executed by the top- and lower-performing teams in the tournament, facilitating the identification of collective play patterns and styles through visual tools. This procedure could be valuable in football for evaluating the performance of one’s own team and opponents, as well as for gaining insights into the playing style of a specific player.

ABSTRACT The popularity of futsal is growing worldwide, leading to a greater professionalization of the sport and requiring coaches to have a deeper knowledge of its competitive demands. Advanced tracking systems allow for monitoring the physical demands associated with external load, which may aid coaches in understanding critical aspects to maximize sports performance. The present systematic review aims to identify the competitive demands of futsal in terms of external load measured via tracking systems. A search was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines in Web of Science, Scopus (Elsevier), and PubMed databases up to November 2023. Of the 318 citations, 12 met the inclusion criteria. High-intensity actions are important for futsal performance. The main external loading variables that assess efforts in elite futsal are total distance, distance covered per minute, high-intensity running, accelerations, and decelerations. It is essential to analyze the external load variables relative to time. In addition, and for a deeper understanding, the analysis of the physical demands should be further explored according to specific player positions (defenders, wingers, or pivots). Futsal performance seems to be determined by the player's ability to repeat multiple high-intensity actions in very short periods.

In fast ball sports, such as tennis, when spatiotemporal constraints are high, players have to anticipate the opponent action. Not much is known about how players acquire and improve this ability. The aim of this study was to use an implicit training protocol (no information was given to participants) based on the knowledge of one particular opponent to analyse how experts could improve their anticipation ability. Professional tennis players were tested and trained in a protocol consisted of watching videos with temporal occlusions before the opponent stroke and guessing the direction of the stroke. Three groups took part in the experiment: one with a specific training with the same opponent as in pre- and post-tests; one with a various training with players other than the one used in pre- and post-tests (to control that the improvement is link with the knowledge of one specific opponent and not to an adaptation to the task) and one control group without practice. Only the group trained with the same opponent increased its response accuracy. Our results suggest that anticipation can be improved in professional tennis players with a very specific training providing information about the opponent.

The rise of social media has provided a rich source of real-time data for analyzing player performance and tactics in professional sports, particularly tennis. This study harnesses social media data mining techniques to analyze tennis-related discussions on Twitter, focusing on identifying biomechanical patterns and tactical strategies during major tournaments. We propose a hybrid model combining Bidirectional Encoder Representations from Transformers (BERT) for generating contextual embeddings and Bidirectional Long Short-Term Memory (Bi-LSTM) for analyzing the sequential nature of tweets. The data collection spans tweets discussing key tournaments, including the Australian Open, French Open, Wimbledon, and US Open. It focuses on specific player movements such as footwork, speed, endurance, and tactical decisions like serve placement, net play, and shot selection. Our methodology includes preprocessing the data, tokenizing the text, and applying sentiment analysis to capture public perception of player performance. The model achieves an accuracy of 88.5% and an F1-score of 87.95%, outperforming comparative models such as BERT with CNN and GloVe with LSTM. The analysis highlights key player-specific tactics, including Rafael Nadal’s baseline dominance and Novak Djokovic’s defensive play, as well as tournament-specific strategies, such as serve-and-volley at Wimbledon and baseline control at the French Open. Furthermore, sentiment analysis reveals positive public perception toward player performance, with key emotions such as excitement and admiration frequently expressed during intense match moments. This study demonstrates the effectiveness of applying advanced NLP techniques to social media data for sports analytics. The insights generated can inform players, coaches, and analysts in enhancing performance strategies and understanding public reactions. Using social media data, our approach provides a scalable framework for analyzing tactical shifts and player performance in other sports contexts.

This study aimed to carry out a systematic review of existing research on physiological, physical and anthropometric parameters in padel. After searching through PubMed, Scopus, Google Scholar, and Web of Science, 33 articles were analyzed, covering physiological, physical, and anthropometric parameters. Physiologically, heart rate varies by sex and play level; men amateurs show a lower maximum heart rate compared to semi-professionals and professionals (154.75 vs 169.72 vs 188.6 beats per minute). Women players maintain consistent maximum heart rate across levels (∼178 beats per minute). Lactate levels during competition indicate effort within the aerobic transition zone, peaking at 2.40 millimole per liter in women and 3.38 millimole per liter in men. Regarding maximal oxygen consumption, padel players exhibit levels around 76.3%, increasing to 95.1% during peak exertion. Biochemical and hematological parameters vary by sex, with men players typically having higher basal levels, while competition reduces certain elements like copper and zinc. Physically, men players exhibit superior jump height, strength, and maximum speeds around 2.09 kilometers per hour, with significant lateral movements. The average distance covered per match is 3000 meters, with higher-level players traveling less. Anthropometrically, men players are taller with a mesomorphic-endomorphic profile, while women players have an endomorphic-mesomorphic somatotype. The study highlights the need for tailored training based on specific player characteristics and calls for further research to better individualize physical preparation in padel.

One of the reasons for the renewed interest in sports star trading cards is is a collection of things you love. For example, personal favorite team, personal favorite players, some people may be a memory of youth, and some people are a kind of walking with time now. Blind boxes, where collectors purchase a pack without knowing which cards they will receive, have become a popular marketing strategy to add an element of surprise and excitement to the buying experience. This unpredictability can create a sense of anticipation and increase the perceived value of the cards inside. Additionally, auctions of specific player cards can create a sense of competition among collectors, driving up prices and adding a thrill of the chase to the purchasing process. By analyzing the effectiveness of these marketing strategies, we can gain insights into what drives collectors to make purchases and how to best engage with them. Understanding these consumer behaviors can help companies in the sports star trading card market tailor their marketing efforts to maximize sales and increase collector engagement.

This study aims to overcome this issue by objectively determining the best positions of the soccer players through the application of the Profile Matching technique. The process consists of five steps: GAP values are first determined by comparing each player's unique traits to predetermined benchmarks. Next, compute the primary and secondary standards, establish weighted scores by utilizing the GAP values, compute the GAP values by contrasting specific player attributes with predetermined benchmarks, compute the overall scores, and order players according to their performance. A weighted combination of mental, physical, and skill criteria (30, 40%, and 30%, respectively) determines the final positions. The results demonstrate how effectively this rigorous technique scores the participants. This process offers a logical and objective approach to player selection, enhancing the precision and effectiveness of decision-making in soccer team management.

Athletes in the National Basketball Association (NBA) are subjected to high levels of mechanical stress increasing their risk of injury. The purpose of this study was to see how certain lower extremity injuries affect in-game performance in relation to each NBA athlete's demographics. The hypothesis was that NBA players' post-injury performance would differ depending on their demographics and the type of injury sustained. Descriptive epidemiology study of NBA injury list designations from the 2010/2011 season to the 2018/2019 season. About 255 lower leg injuries that met the inclusion criteria were selected from the injury lists spanning from the 2010/2011 season to the 2018/2019 season. These included ligamentous knee injuries, knee sprains, knee strains, knee hyperextensions, patellar injuries, ankle injuries, and Achilles injuries. The change in performance was determined by comparing mean game scores before and after injury with single-tailed, heteroscedastic t-testing and 95% confidence intervals for mean values. An overall statistically significant decrease in mean game score from 9.82 to 8.75 was seen in all included players (p = 0.01). Only athletes taller than the mean height (199.85 cm; p = 0.01) and heavier than the mean weight (101.63 kg;p = 0.02) showed a significant decline in performance. Ankle and knee injuries both resulted in a significant loss in game score (p = 0.04), with ankle injuries resulting in a greater average decline (-1.76 post-injury) than knee injuries (-1.34 post-injury). These findings suggest that treatment regimens should reflect the type of injury and demographics of the specific NBA player injured. Further research is warranted to determine if treatment may be more efficacious when streamlined based on player size and injury type.

We study the (a, b)-monochromatic transversal game that is a combinatorial Maker–Breaker game where Alice and Bob alternately colour a vertices in red and b vertices in blue of a hypergraph, respectively. Either player is enabled to start the game. Alice tries to construct a hyperedge transversal, and Bob tries to prevent this. The winner is Alice if she obtains a red hyperedge transversal; otherwise, Bob wins the game if he obtains a monochromatic blue hyperedge. Maker–Breaker games were determined to be PSPACE-complete. In this work, we analyze the game played on clique-hypergraphs of powers of cycles, and we show strategies that, depending on the choice of the parameters, allow a specific player to win the game.

The research purpose : (1) The factors affecting the satisfaction of mobile devices and desktop players of MMORPG games in China are discussed. (2) Investigate the relative importance of the satisfaction of MMORPG players on mobile devices and desktop computer in China. (3) According to the research results, make a guide for MMORPG players in the choice of platform, and give relative suggestions, so that players can choose their own game platform more quickly. Using this quantitative research, mainly MMORPG players in Hunan Province, including players from other provinces. By publishing questionnaire links in related forums, social media platforms and related official topics, 1,258 valid questionnaires were collected after cleaning, and the methods of reliability analysis, validity analysis, variance analysis and regression analysis were used in the study. It is found that: (1) Game quality, social rating, narrative structure and game experience will have a positive impact on player satisfaction. (2) China MMORPG desktop computer players are more satisfied than mobile devices players. (3) Suggestions are made that future research should further explore the differences between specific game types and specific player groups, so as to better meet the needs of different users and better guide gamers.

This article investigate the cooperative differential game (CDG) for continuous-time linear Itô stochastic systems with markovian jumps (SSMJ) to obtain the Pareto solutions. Different from most existing works studying nonzero-sum games, this article studies the CDG on the quadratic infinite horizon for the Itô-type SSMJ with unknown system matrix and transition probability. A novel <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$</tex-math> </inline-formula> -learning online algorithm is developed, which consists of that (i) the optimal control problem is equivalent to solving a stochastic algebraic Riccatic equation (ARE); (ii) the joint cost function is approximated by a critic neural network (NN) and Pareto efficient is approximated by two actor NNs. The rigorous stability analysis shows that the system state for SSMJ and the NN weight errors are uniformly ultimately bounded (UUB). Finally, the theory analysis is validated by a numerical example with detailed discussions. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In practical applications, many systems are often affected by the change of external environment or the failure of internal components, which leads to the random jump of system parameters. Markovian jump system can effectively describe the above problems. And when the system model is disturbed by the internal parameters, the system control input and external environment, the random errors of state measurement, and other random factors, the deterministic model can no longer accurately describe the controlled system. Therefore, the SSMJ can describe practical problems more accurately. By cooperation, in general, the cost one specific player incurs is not uniquely determined anymore. If all players decide, for example, to use their control variables to reduce the cost of player 1 as much as possible, a different minimum is attained for player 1 compared with that in the case where all players agree collectively to help a different player in minimizing his cost. So, depending on how the players choose to ‘divide’ their control efforts, a player incurs different ‘minima’. Therefore, we will design an online learning algorithm to obtain pareto solutions with different weights. On the other hand, in practice, it is difficult to obtain an accurate system model. In order to solve this problem, a novel scheme is designed by using <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$</tex-math> </inline-formula> -learning technology, which does not need system matrix.

Basketball players should train at intensities similar to those recorded in competition, but are the intensities really similar? This study aimed to quantify and compare the internal and external intensities assimilated by professional basketball players, both in training and in competition, according to context and the specific player position. Players from the same team in the Spanish ACB competition were monitored for three weeks. The sample recorded intensities in 5 vs. 5 game situations in both training (n = 221) and competition (n = 32). The intensities, as dependent variables, were classified into kinematic external workload demands (distances, high-intensity displacements, accelerations, decelerations, the acceleration:deceleration ratio, jumps, and landings), neuromuscular external workload demands (impacts and player load), and internal workload demands (heart rate). They were measured using inertial measurement devices and pulsometers. The playing positions, as independent variables, were grouped into guard, forward, and center. According to the context, the results reported a significant mismatch of all training intensities, except jumps, with respect to competition; these intensities were lower in training. According to the playing position, inside players recorded more jumps and landings per minute than point guards and outside players in training. In turn, inside players recorded a higher average heart rate per minute than outside players in this same context. There were no significant differences in intensity according to the playing position in the competition. Considering the context–position interaction, no differences were observed in the intensities. Adjusting and optimizing training intensities to those recorded in competition is necessary.

We examine two diametrically opposite levels of action on a basketball court to address incorrect concepts about both. When a free throw is taken, all action stops. The fouled player steps unopposed to the free throw line to shoot at the open basket. A specific player may have flaws in technique, but consistent improvement across many games for many players at first consideration seems unlikely. A plot of yearly free throw shooting accuracy from 1987 through 2022 tells a different story. At the opposite end of the basketball activity spectrum is the three-point shot. Since 1987 when the top division of US college basketball created the opportunity to score three points for shots taken outside of an arc, we see much effort being taken to shoot increasing numbers of three-point shots, given the obvious advantage of scoring three points instead of two. Of course, a team with accurate three-point shooters should exploit that option. Late in a game when a team is behind, again, the three-point shot should be exploited. However, we ask if it is good practice as a rule for teams to become infatuated with shooting that shot. We will display significant flaws with that strategy.

Costello II, JP, Wagner, JD, Dahl, VA, Cohen, JL, Reuter, AM, and Kaplan, LD. Effects of COVID-19 on rate of injury and position-specific injury during the 2020 National Football League season. J Strength Cond Res 38(1): 97-104, 2024-Because of the COVID-19 pandemic, the National Football League (NFL) made changes to its operations for the 2020 season. We hypothesize an increase in the rate of injuries during the 2020 season. Publicly available data were reviewed to identify NFL injuries from the 2015-2020 seasons. Player position, description of injury, date of injury, and injury setting were recorded. p ≤ 0.05 was considered statistically significant. For the 2020 season, compared with the 2015-2019 seasons, there was an increased risk of injury during the regular season overall relative risk (RR) = 1.308 ( p < 0.05), week (W)1 RR = 7.33 ( p < 0.05), W1-6 RR = 1.964 ( p < 0.05), W7-12 RR = 1.8909 ( p < 0.05), and during the postseason overall RR = 1.1444 ( p < 0.05), calculated using analysis of variance. There was an overall increased risk of abdominal or core injuries RR = 1.248 ( p < 0.05), groin or hip injuries RR = 2.534 ( p < 0.05), and hamstring injuries RR = 3.644 ( p < 0.05). There was an increased risk of hamstring injuries in cornerbacks RR = 3.219 ( p < 0.05) and running backs RR = 1.1394 ( p < 0.05), hip or groin injuries in guards RR = 1.105 ( p < 0.05), Achilles tendon injuries in safeties RR = 1.6976 ( p < 0.05), quadriceps injuries in running backs RR = 1.6191 ( p < 0.05), and arm injuries in defensive tackles RR = 1.221 ( p < 0.05). There was an increase in the overall rate of injuries in the 2020 NFL season, both in the regular season and postseason, compared with the 2015-2019 seasons. The overall rate of abdominal or core, groin or hip, and hamstring injuries increased. Specific player positions saw unique increases in rates of injuries. These findings may be due to numerous operational changes implemented, such as reduced in-person training and the elimination of the preseason, leading to suboptimal, sports-specific conditioning and increased risk of musculoskeletal injury.

Introduction: Water polo is a physically high-demanding team sport, therefore players’ physical abilities and anthropometric characteristics are important factors to achieve a good level of quality in technical-tactical actions. The aim of this study was to determine the association of the chronological age with the anthropometric characteristics and specific functional swimming capacities in youth U12 male water polo players. Methods: There were 170 youth U12 water polo players who attended the Croatian Water Polo Federation training camps included in this cross-sectional study. Measurements included anthropometric characteristics and specific functional swimming capacities. Results: Players were divided according to their chronological age: Q1 (January- March) – 59 players (34.7%), Q2 (April-June) – 35 players (20.6%), Q3 (July-September) – 46 players (27.1%) and Q4 (October-December) – 30 players (17.6%). Older players born in Q1 presented higher values of body height and weight than their younger peers born in Q4 (Q1 165.96±7.88 cm vs. Q4 159.46±5.44 cm, P=0.001; Q1 60.14±13.99 kg vs. Q4 51.35±7.09 kg, P=0.023), while there were no statistically significant differences in specific functional swimming tests between different age groups. Discussion: Contrary to what was hypothesized, older water polo players presented only better anthropometric characteristics than their younger peers, probably due to the biological maturity influence on functional skills, as well as small range of chronological age differences. Conclusion: Such data might provide an understanding of the general and specific water polo player’s development process, which should be considered by coaches of youth players to improve their skills as a result of developing better training programs.

Automatic ways to generate video summarization is a key technique to manage huge video content nowadays. The aim of video summaries is to provide important information in less time to viewers. There exist some techniques for video summarization in the cricket domain, however, to the best of our knowledge our proposed model is the first one to deal with specific player summaries in cricket videos successfully. In this study, we provide a novel framework and a valuable technique for cricket video summarization and classification. For video summary specific to the player, the proposed technique exploits the fact i.e., presence of Score Caption (SC) in frames. In the first stage, optical character recognition (OCR) is applied to extract text summary from SC to find all frames of the specific player such as the Start Frame (SF) to the Last Frame (LF). In the second stage, various frames of cricket videos are used in the supervised AlexNet classifier for training along with class labels such as positive and negative for binary classification. A pre-trained network is trained for binary classification of those frames which are attained from the first phase exhibiting the performance of a specific player along with some additional scenes. In the third phase, the person identification technique is employed to recognize frames containing the specific player. Then, frames are cropped and SIFT features are extracted from identified person to further cluster these frames using the fuzzy c-means clustering method. The reason behind the third phase is to further optimize the video summaries as the frames attained in the second stage included the partner player’s frame as well. The proposed framework successfully utilizes the cricket videoo dataset. Additionally, the technique is very efficient and useful in broadcasting cricket video highlights of a specific player. The experimental results signify that our proposed method surpasses the previously stated results, improving the overall accuracy of up to 95%.

Abstract: This research estimates the effect of specific player position on salary in Major League Soccer. We expand a mincer-style wage equation with indicators for precise roles as defined by the Football Manager™ simulation. Our salary data covers 1,174 salaries for the 2019 and 2020 seasons. We match this to 17 positions and consider generalist and specialist functions in wage determination. Estimating ordinary least squares and quantile regressions, we find that defensive salary penalties are incurred only by specific peripheral defensive and wing back positions. Premia exist for versatile, attacking midfield players. We show that multi-positional players—those that play in multiple positional zones—earn a premium. The findings bring nuance to any specialist-generalist debate as versatile defensive players incur a penalty whereas versatile attacking midfield players earn a premium. Practically, the results speak to player unions, intermediaries advising players on their developmental needs, and franchises who must optimize salary budgets.