Ranking Of Players Research Articles

A Study on the Factors Influencing Rank Prediction in PlayerUnknown’s Battlegrounds

This study analyzes the key factors influencing player rank prediction in PlayerUnknown’s Battlegrounds (PUBG), using machine learning models to evaluate in-game performance. By examining variables such as “walkDistance”, “boosts”, and “weaponsAcquired”, the study identifies these as critical predictors, with “walkDistance” emerging as the most significant across all match types. Utilizing models including random forest (RF), gradient descent (GD), extreme gradient boosting (XGBoost), and feedforward neural network (FNN), the analysis reveals performance variation by match type: XGBoost achieves the highest accuracy in solo matches (88.07%), GD performs best in duo matches (84.75%), and RF records the highest accuracy in squad matches (78.21%). These findings provide valuable insights for game developers in balancing gameplay and offer personalized strategic recommendations for players. Future research may enhance predictive performance by incorporating additional variables and exploring alternative models applicable to PUBG and similar battle royale games.

NBA Player Data Statistics and Predictions Based on Spark

Entering the 21st century, the sports field has begun to rely on advanced data to establish fine-grained athlete evaluation metrics, such as the impact of an athlete’s presence on the team and performance in critical moments. These metrics are included in statistics and analysis. This experiment analyzes player datasets from NBA games, processing and statistically analyzing data indicators such as player rankings, changes brought by player age and career length, and changes in the proportion of three-point shots. The rating score proposed in this study is used as a measurement indicator to predict Luka Doncic’s performance since entering the league. The model’s performance is evaluated by calculating the root mean square error between the predicted and actual data. Analyzing and predicting player game data is crucial for evaluating player performance, formulating tactics, and management strategies. It not only helps management and coaching teams make more informed draft and trade decisions but also reveals similarities and differences among players through techniques such as cluster analysis, guiding personalized training and tactics.

Same Same but Different: Why Both Sport-Specific Cutting Tasks and Generic Change-of-Direction Tasks Might Need to Be Considered to Prevent ACL Injury

OBJECTIVES: To compare knee abduction moment (KAM) magnitudes between a generic 180° pivot turn (modified 505 change-of-direction test [m505]) and a handball-specific sidestep cut, to assess ranking consistency, and to examine the resultant ground reaction force (GRF) and its frontal plane moment arm to the knee to comprehend their contributions to KAM. STUDY DESIGN: Observational laboratory study. METHODS: High-level female handball players (n = 45) performed the m505 and the handball-specific sidestep cut. The resultant GRF and its frontal plane moment arm to the knee as well as KAM were obtained and subsequently compared between tasks. Rank correlation coefficients were employed to assess if the variables of both tasks were related. RESULTS: Peak KAM was similar for the m505 and the sidestep cut (median [range], 1.79 [0.95-3.53] Nm/kg vs 1.64 [0.34-3.60] Nm/kg; rb = .25; P = .14). The ranking of the players’ peak KAM differed substantially ( rs = .26; P = .084), suggesting that different tasks could classify the same player with different injury risk. The m505 generated lower resultant GRFs (24 ± 4 N/kg, 95% CI [23, 24] vs 33 ± 9 N/kg, 95% CI [31, 35]; d = 1.30; P<.001) but longer frontal plane moment arms (7.8 ± 1.8 cm, 95% CI [7.3, 8.4] vs 5.4 ± 1.5 cm, 95% CI [5.0, 5.8]; d = 1.36; P<.001) compared to those generated by the sidestep cut. CONCLUSION: A difference in individual anterior cruciate ligament injury risk assessment depending on movement type was revealed. While KAM magnitudes were similar across direction-change tasks, player rankings differed. The contributions of resultant GRF and frontal plane moment arms to peak KAM varied between tasks, underscoring the importance of task-specific and individualized injury prevention. JOSPT Open 2025;3(2):1-9. Epub 4 December 2024. doi:10.2519/josptopen.2024.0076

Разработка предметных графов знаний на основе семантического аннотирования табличных данных

The article outlines an approach and software tool for the automated enrichment of domain-oriented knowledge graphs with new facts derived from semantically annotated tabular data. For semantic annotation of table columns, a combination of three heuristic methods is proposed, leveraging named entity recognition in cells, lexical matching, and feature grouping. This approach is implemented as a dedicated handler within the Talisman software platform. An example and experimental evaluation of the approach during the semantic annotation of columns are provided using a test set of tabular data across six thematic categories: "organization employees," "open vacancies," "car model market," "famous scientists," "book sales," and "tennis player rankings." Evaluation metrics included precision, recall, and F-measure, with final results across all six categories as follows: precision - 79%, recall- 63%, F-measure - 70%. These results highlight the potential of the developed approach for enriching domain-oriented knowledge graphs with new facts from semantically annotated tabular data. The limitations of the proposed approach are also discussedfrom semantically annotated tabular data. The paper also provides a number of limitations of the proposed approach.

Evaluating aerial duel ability of football players using height-adjusted Elo rating model

ABSTRACT Football players’ aerial duel ability has been typically evaluated based on the “aerial duel success rate (success/attempt)”. However, sole reliance on this indicator implies excluding other factors like the opponent’s aerial duel ability and height. This makes the evaluation of a player’s true ability difficult. The Elo rating system is an alternative method that addresses such exclusion. This study analysed a player’s aerial duel ability more accurately using an Elo model adjusted by height. All players from all matches in the K League 1 over the 3 seasons were analysed. The player rankings for aerial duel ability calculated using the Elo rating system showed significant differences compared to the rankings based on aerial duel success rates used in previous studies e.g. the player ranked 1st in Elo was 3rd in aerial duel success rate, the 2nd and the 3rd players remained 21st and 54th. These results serve as valuable information for analysing players’ abilities and understanding team tactics in the applied field. These will also be crucial for player evaluation while scouting.

The relative age effect among Chinese junior men's tennis players and its impact on sports performance.

The relative age effect (RAE) has been the subject of many studies, but no relevant literature has discussed the phenomenon of RAE in Chinese tennis. Numerous studies have demonstrated that RAE significantly contributes to brain drain and other occurrences that create inequity. This paper analyzes the birth dates and year-end rankings of all male players (N = 2697) who participated in China's junior tennis tournaments (U12, U14, U16) between 2014 and 2019 and who were selected for China's National Junior Team in 2019 and 2020; the paper classifies the birth dates into quarters and semesters. One of the research objectives of this study is to analyze whether RAE exists in Chinese junior men's tennis and whether RAE exerts an effect on athletes' performance. Differences between the observed and expected birthdate distributions were tested using chi-square statistics, and subsequent calculations were tested using odds ratios. The study found that RAE was present in all Chinese junior male tennis sports groups (p<0.001). The percentages of athletes born in the first half of the year were 56.4% (U12), 60.4% (U14), and 60.4% (U16), and the percentages of those born in the first quarter were 34.1% (U12), 36.4% (U14), and 37.1% (U16). Athletes with birth dates closer to the beginning of the year had a higher probability of achieving excellent athletic performance as a result of RAE, whereas those who were born near the end of the year had a more difficult time achieving strong athletic performance.

Evaluating Hockey Players Using Andersen and Petersen's Super-Efficiency Model: Who is the Best Czech Hockey Player in the NHL?

Abstract Introduction. The aim of this article is to measure and assess the efficiency of Czech hockey players in the NHL, to create a ranking, and to reveal the best Czech hockey players in the NHL. Material and methods. The methodology is based on data envelopment analysis (DEA), namely a basic input-oriented model with constant returns to scale and an advanced Andersen and Petersen's model. Using the Andersen and Petersen's model, a ranking of the best Czech forwards, defenders, and goalkeepers was created based on the super-efficiency scores. DEA models worked with several variables and allowed for greater objectivity to be incorporated into the rankings. The input variable chosen was the number of seasons played. The output variables included the number of games played, the number of minutes played, the number of goals, the number of assists, save percentage, and the number of Stanley Cups won. Results. The research named Jaromír Jágr, Jan Rutta, and Pavel Francouz as the best Czech forward, defender and goalkeeper in the NHL in terms of technical efficiency. Conclusions. The ranking of hockey players based on super-efficiency scores revealed, among other things, that hockey players with a high number of seasons, games played or goals scored are not necessarily technically efficient.

Relationships between selected indices of postural stability and sports performance in elite badminton players: Pilot study.

The main aim of this study was to determine the relationships between postural stability and the place in the ranking of badminton players. The study examined 10 elite players from Polish national badminton team. The scope of the study included basic somatic characteristics, such as body height, body weight, BMI, and training experience. A Microgate GYKO inertial sensor system was used to assess the postural stability of athletes. Using Spearman's rank correlation, cause-and-effect relationships between the place in the sports ranking and the analyzed variables characterizing postural stability were recognized. Depending on the distribution and homogeneity of variance, the significance of differences in variables that characterize postural stability between players of different sports skill levels (two groups) was calculated. The Student's t-test or Mann-Whitney's U-test was used for this purpose. In general, the athletes with higher positions on the ranking list presented a higher level of postural stability in both tests, which is also confirmed by the normalized values. However, for all variables of postural stability, no statistically significant correlations with sports ranking were observed. Higher values of Spearman's rank correlation coefficients were found for the test performed in the one-foot standing test compared to the two-foot test. The results obtained indicate that particular attention in badminton training should be paid to the development of the level of postural stability in order to improve sports performance.

Expertise, gender, and equilibrium play

Mixed‐strategy Nash equilibrium is the cornerstone of our understanding of strategic situations that require decision makers to be unpredictable. Using data from nearly half a million serves over 3000 tennis matches, and data on player rankings from the ATP and WTA, we examine whether the behavior of professional tennis players is consistent with equilibrium. We find that win rates conform remarkably closely to the theory for men, but conform somewhat less neatly for women. We show that the behavior in the field of more highly ranked (i.e., better) players conforms more closely to theory. We show that the statistical tests used in the prior related literature are not valid for large samples like ours; we develop a novel statistical test that is valid and show, via Monte Carlo simulations, that it is more powerful against the alternative that receivers follows a nonequilibrium mixture.

Pre-season body composition has minimal influence on in-season match availability, and match performance in female Australian Football League (AFLW) players.

This study examined the relationship between pre-season body composition, in-season match performance, and match availability in female players competing in the Australian Football League Women's (AFLW) competition. With the outlawing of body composition assessments as part of pre-draft player evaluations in the AFLW, this study seeks to examine whether this is justified. Twenty-two (n = 22) players had body composition assessed with dual-energy x-ray absorptiometry at the beginning of the 2021 AFLW pre-season (whole-body and regional fat mass and lean soft-tissue mass [LSTM]). In-season match availability and match performance data (Coaches Score [CS], Champion Data Player Rank, average disposals, disposal and kicking efficiency) were collected throughout the 2021 competition. Pearson correlations were performed to assess if associations existed between body composition and in-season match performance and availability. A median split was performed to divide players into higher and lower performing groups for match performance variables. Two-sample independent t-tests were then used to assess differences between groups. No body composition characteristics could differentiate between in-season match availability groups (100% availability vs. <100% availability) or higher and lower performing groups for all match performance variables. Total leg LSTM asymmetry shared a moderate negative association with CS. Body composition may not be important for determining in-season match availability and performance in female AFLW players. Thus, the repercussions following the removal of pre-draft body composition assessments across the league may not be as significant as is currently perceived. Other physiological, biomechanical, or performance qualities are more variable and may mask the effect of body composition in these players. AFLW practitioners should prioritize the development of other important attributes, such as aerobic fitness, muscular strength and power, and technical skill.

Action2Score: An Embedding Approach to Score Player Action

Multiplayer Online Battle Arena (MOBA) is one of the most successful game genres. MOBA games such as League of Legends have competitive environments where players race for their rank. In most MOBA games, a player's rank is determined by the match result (win or lose). It seems natural because of the nature of team play, but in some sense, it is unfair because the players who put a lot of effort lose their rank just in case of loss and some players even get free-ride on teammates' efforts in case of a win. To reduce the side-effects of the team-based ranking system and evaluate a player's performance impartially, we propose a novel embedding model that converts a player's actions into quantitative scores based on the actions' respective contribution to the team's victory. Our model is built using a sequence-based deep learning model with a novel loss function working on the team match. We showed that our model can evaluate a player's individual performance fairly and analyze the contributions of the player's respective actions.

Football player ranking generated by multivariate methods

The objective was to build a ranking of football players based on multivariate methods. The players evaluated were the winners of FIFA; UEFA; Ballon D'Or; FIFPro; World Soccer; Golden Ball World Cup and King of América awards. A total of 95 players were evaluated based on the variables: games played, wins, draws, losses, goals scored, yellow/red cards, awards, dream team, title in national leagues/ continental championships in a football club, title in world cups/ continental championship in a national team, Olympics gold medal. We performed the multivariate clustering and principal components analyses. The grouping technique resulted in three groups: regionally renowned players (Group 1), renowned players for their extraordinary performance (Group 2), and globally renowned players (Group 3). The players in Group 2, except for Maradona, reached the highest indexes. The leaders of the ranking were Messi, Cristiano Ronaldo, Xavi, Pelé, and Iniesta.

Using the PageRank Algorithm to Rank Football Players in a Game

There are many methods to rank football players based on their performance in a game or series of games. However, since most methods are subjective, this paper proposes the PageRank algorithm as an objective method to rank players in a football team, where players can be considered as the nodes, and the passes made between them as the edges of a graph. To achieve this, we consider weighting functions, which are based on parameters which consider the number and quality of passes as well as the actions of individual players in the game. In this paper, the game chosen for implementing the rankings is the 2018 World Cup Final between France and Croatia. The weighting functions are then combined in multiple ways to create different models, which hare implemented in Python to compute the rankings. The models are compared with the official rankings of players during the game with the help of the Kendall's Tau Correlation Coefficient in order to find the distance between the two ranking vectors. While the results may not be highly accurate for the models tested in this paper, a number of additional factors influencing player performance, which official rankings account for, can be considered through more weighting functions. This would lead to more accurate results, thus making the PageRank algorithm a promising and objective tool for ranking football players in a game.

Iterative algorithm for discrete structure recovery

We propose a general modeling and algorithmic framework for discrete structure recovery that can be applied to a wide range of problems. Under this framework, we are able to study the recovery of clustering labels, ranks of players, signs of regression coefficients, cyclic shifts and even group elements from a unified perspective. A simple iterative algorithm is proposed for discrete structure recovery, which generalizes methods including Lloyd’s algorithm and the power method. A linear convergence result for the proposed algorithm is established in this paper under appropriate abstract conditions on stochastic errors and initialization. We illustrate our general theory by applying it on several representative problems: (1) clustering in Gaussian mixture model, (2) approximate ranking, (3) sign recovery in compressed sensing, (4) multireference alignment and (5) group synchronization, and show that minimax rate is achieved in each case.

Preliminary Research on Physical Performance in Junior Tennis Players U16

Physical performance regarding the rankings of U16 junior tennis players is not precisely understood. The purpose of this preliminary research was to check if the top-ranked players had better results in the evaluation of physical tests than the lower-ranked ones. Therefore, the scope was to determine if the national ranking is related to the physical characteristics. The physical tests used were approved by the Romanian Tennis Federation. The following research methodology has been used: protocol methodology, the recording of data in research methodology, test in research methodology, and the statistical methodology. The tennis players followed their usual physical training for three months and at the end of this period, they were tested. Twenty-two tennis players, eleven girls, and eleven boys, between 14 and 16 years old, were part of this preliminary research. The following measures were conducted: 5-10 m sprint, 30 m sprint test, 6 x 20 m sprints, long jump, repeated lateral jumps performed on both legs over the gym bench, one-handed medicine ball throw with, overhead medicine ball throw test, lateral steps test, Hexagon test, agility test, and push-ups test. Results The group of tennis players was followed during 12 weeks of their usual training. The variables were expressed in mean and standard deviation. The purpose was to check if there is any correlation between the ranking and the morphological parameters. Pearson correlation has been used. The normality of the variance and covariance was certified with Shapiro-Wilks Normality Test. Conclusion After comparing the results, it was shown that the players from the group with better ranking positions, had superior results in the evaluation tests.

Forecasting Tennis Match Results Using the Bradley-Terry Model

Forecasting has been playing an important role in different fields of life, i.e., in decision-making activities of management, to predict uncertain events within an organization, in weather forecasting, in flood forecasting, etc. Stakeholders involved in betting market take advantage of tennis forecasting directly or indirectly. Winning probability calculated using forecasting models helps the bettors in deciding whether to place a bet or not. Keeping in view the importance of tennis forecasting, the Bradley-Terry model is used to model men’s professional tennis for predicting match outcomes in tennis matches of men’s singles. Model coefficients are estimated using data from January 2019 to September 2020 of 3439 matches. Ratings for each player are calculated using model coefficients. Player rankings are then calculated using these ratings. Comparison of model rankings with ATP rankings has shown satisfactory results. Winning probability for each player is calculated using model coefficients and ratings. These probability predictions are evaluated against four measures of performance. The results reveal that surface on which a game is played on contributes significantly towards a player’s performance. Due to this impact of the surface, our model has produced superior player rankings for certain players who had been ranked very low in official ATP rankings. According to most of the performance measures, the model has shown good results for clay court data which are closely followed by hard court data. To calculate return on investment, model results are compared with the bookmakers’ average odds and best available odds. It has been found that return on investment for a fitted model is highest in the case of clay court data in comparison to bookmaker’s average odds and best odds.

Disproving the Sophomore Slump Using Data Envelopment Analysis

The “sophomore slump” is a widely accepted phenomenon in modern sport culture, commonly conceptualized as a decline in performance during a player’s second year of competition following an outstanding first season. This study empirically verified the absence of sophomore slump through a two-stage network data envelopment analysis and Malmquist productivity index analysis of 616 English Premier League players from the 2014–2015 to 2018–2019 seasons. The relative rankings of individual second-year players were compared with their rankings in the previous season, and second-year and non-second-year player groups were also compared. No evidence was found to indicate the existence of a sophomore slump. In addition, Tobit regression analysis was conducted to analyze the effects of environmental variables such as yellow cards, red cards, and fouls. This study is meaningful because it analyzes “efficiency,” which has a strategic and financial impact not only on individual players but also on team managers and scouts.

Disproving the Sophomore Slump Using Data Envelopment Analysis—Focusing on English Premier League’s 2014/2015 to 2018/2019 Seasons

Abstract: The “sophomore slump” is a widely accepted phenomenon in modern sport culture, commonly conceptualized as a decline in performance during a player’s second year of competition following an outstanding first season. This study empirically verified the absence of sophomore slump through a two-stage network data envelopment analysis and Malmquist productivity index analysis of 616 English Premier League players from the 2014–2015 to 2018–2019 seasons. The relative rankings of individual second-year players were compared with their rankings in the previous season, and second-year and non-second-year player groups were also compared. No evidence was found to indicate the existence of a sophomore slump. In addition, Tobit regression analysis was conducted to analyze the effects of environmental variables such as yellow cards, red cards, and fouls. This study is meaningful because it analyzes “efficiency,” which has a strategic and financial impact not only on individual players but also on team managers and scouts.

A Multidisciplinary Investigation into the Talent Development Processes in an English Premiership Rugby Union Academy: A Preliminary Study through an Ecological Lens.

(1) Background: The progression of youth rugby union (RU) players towards senior professional levels can be the result of various different constraints. The aim of this study was to examine characteristics that differentiated playing positions and player rankings in an English Premiership RU academy. (2) Methods: Thirty players (mean age = 18.5 ± 2.8 years) were divided by playing positions (forwards = 18, backs = 12) and ranked (one to thirty) by coaches based on their potential to achieve senior professional status. Players were analysed across 32 characteristics from eight overreaching factors based on task, environmental, and performer constraints. MANOVA and ANOVA were used to calculate differences among variables in players’ positions (i.e., forwards vs. backs) and ranks (i.e., top 10 vs. bottom 10), with a Welch’s t-test applied to identify individual differences amongst groups and effect sizes calculated. (3) Results: Large effect sizes were found between groups for socioeconomic, sport activity, anthropometric, physical, and psychological factors. Moreover, environmental and performer constraints differentiated playing positions, whereas task and environmental constraints discriminated player ranks. (4) Conclusion: Present findings showed that playing positions and player ranks can be distinguished according to specific constraints.

Video Sequence Analysis for On-Table Tennis Player Ranking and Analysis

With the rapidly developing of the scientific research in the field of sports, big data analytics and information science are used to carry out technical and tactical statistical analysis of competition or training videos. The table tennis is a skill oriented sport. The technique and tactics in table tennis are the core factors to win the game. With the endlessly emerging innovative playing techniques and tactics, the players have their own competition styles. According to the competition events among athletes, the athletes’ competition relationship network is constructed and the players’ ranking is established. The ranking can be used to help table tennis players improve daily training and understand their ability. In this paper, the table tennis players’ ranking is established their competition videos and their prestige scores in the table tennis players’ competition relationship network.