Differences in situation efficacy indicators at the elite basketball players that play on different positions in the team

The aim of our study was to determine the differences in situational efficacy for basketball players, in relation to their team positions: between guards and forwards/centres, and between the players on the four major positions in the team. The final sample of subjects (74 basketball players) is selected from the initial sample of 107 subjects, selected from nine men's senior basketball teams that played in A-1 Croatian men's basketball league championship in 2006/2007. Results confirmed the hypothesis that there is a significant difference between different groups of players: point/shooting guards, comparing with forwards/centres; players that play on four positions: point guard, shooting guard, small forward, power forward/centre. Guards have shown greater efficiency and utilization of the three-point shots, while centres are better in two-point shots. Guards have a greater number of assists, successful and unsuccessful three-point shots, while centres are better in the offensive and defensive rebounds, as same as in successful and unsuccessful two-point shots. No statistically significant differences were found among the players on the guard positions (point guard and shooting guard), while only one statistically significant difference is found among the players on the position forward/centre (small forward and power forward/centre).     

Differences in conative characteristics and perceived group cohesion of the basketball players playing in different positions in the team

Identification of differences in individual conative characteristics and in perceived group cohesion of the basketball players playing in different positions in the team could provide guidelines for a better selection of basketball players and better coaching work. The aim of our study was to determine the differences in relation to the positions of guards and forwards/centres, and the four major positions in the team. The final sample of subjects (74 basketball players) is selected from the initial sample of 107 subjects, selected from nine men's senior basketball teams that played in A-1 Croatian men's basketball league championship in 2006/2007. The results showed no statistically significant difference between basketball players who play in different positions in the team, neither in relation to two basic positions in the team (guards as opposed to forwards/centres), nor in relation to the four positions in the team (point guard, shooting guard, small forward, power forward/centre).     

System of the performance evaluation criteria weighted per positions in the basketball game

Based upon the expertise performed by ten basketball professional relative importance coefficients with regard to positions in the game were determined for nineteen performance evaluation criteria. High degree of interobservers agreement was obtained concerning all positions (from 0.91 to 0.98). In concordance with the obtained results the particular play positions were explicitly described, as well as similarities and differences between them were determined from the aspect of the single criteria importance. The following criteria had an above average importance for the: Position 1--levels of defensive pressure, transition defense efficiency, the ball control, passing skills, dribble penetration, outside shots, and transition offence efficiency; Position 2--level of defensive pressure, transition defense efficiency, outside shots, dribble penetration, offence without the ball, and transition offence efficiency; Position 3--transition defense efficiency, outside shots, dribble penetration, offense without the ball, free throws, and transition offence efficiency; Position 4--defensive and offensive rebounding efficiency, inside shots, dribble penetration, efficiency of screening, and free throws; Position 5--defensive and offensive rebounding efficiency, inside shots, dribble penetration, efficiency of screening, drawing fouls and three-point plays, and free throws. The research results could be usefully applied by the basketball practitioners to selecting and following-up players, the teching-learning process directing and improving, the training process programming and the transformational effects controlling.     

The problem of shot selection in basketball

In basketball, every time the offense produces a shot opportunity the player with the ball must decide whether the shot is worth taking. In this article, I explore the question of when a team should shoot and when they should pass up the shot by considering a simple theoretical model of the shot selection process, in which the quality of shot opportunities generated by the offense is assumed to fall randomly within a uniform distribution. Within this model I derive an answer to the question “how likely must the shot be to go in before the player should take it?” and I show that this lower cutoff for shot quality depends crucially on the number of shot opportunities remaining (say, before the shot clock expires), with larger demanding that only higher-quality shots should be taken. The function is also derived in the presence of a finite turnover rate and used to predict the shooting rate of an optimal-shooting team as a function of time. The theoretical prediction for the optimal shooting rate is compared to data from the National Basketball Association (NBA). The comparison highlights some limitations of the theoretical model, while also suggesting that NBA teams may be overly reluctant to shoot the ball early in the shot clock.     

Physical demands on young elite European female basketball players with special reference to speed, agility, explosive strength, and take-off power

The aim of the study was to determine and analyze the level of certain motor abilities (acceleration and agility, the explosive strength of arms, and take-off power) of young elite European female basketball players. We also wanted to establish whether there were any differences between 3 groups of female basketball players who differed in terms of their playing performance. The sample of subjects consists of 65 female basketball players aged 14.49 (± 0.61) years who were divided into 3 groups (divisions A, B, and C of the European Championships). We compare the groups by using 8 motor tests. p Values <0.05 were considered statistically significant. The results show that the division C players achieved below-average results in all tests and thus differ from the players from divisions A and B whose test results were relatively homogeneous. The division C players differ from those from divisions A and B mainly in the 6 × 5-m sprint dribble (discriminant ratio coefficients [DRC] = 0.435), medicine ball throw (DRC = 0.375), and 20-m sprint (DRC = 0.203). Discriminatory power in the 6 × 5-m sprint dribble and 20-m sprint tests is preserved even after eliminating the effect of body height. We assume that, besides the deficit in body height and training status, this is also 1 of the key reasons for these players' lower playing efficiency compared to those from divisions A and B. We hope the findings of this study will enable the generation of model values, which can assist basketball coaches for this age category in basketball clubs, high schools, national teams, and basketball camps.     

Comparison of selected physical fitness and performance variables between NCAA Division I and II football players

The purpose of this study was to compare selected physical fitness and performance variables between National Collegiate Athletic Association (NCAA) Division I and II football players. The subjects included offensive and defensive starters, excluding kickers and punters from 26 NCAA Division I and 23 Division II teams. Offensive players were grouped and compared by the following positions: quarterback, running back, wide receiver, tight end, and line. Defensive players were grouped and compared by the following positions: line, linebackers, and backs. Division I players were better in 58 of 117 comparisons (p < or = 0.01). Division II players were not found to be better in any of the variables studied.     

Set of criteria for the actual quality evaluation of the elite basketball players

The paper comprises a proposition of nineteen criteria for the actual quality (situation-related efficiency/performance) evaluation in the elite basketball players (seven criteria for the efficiency on defence and twelve for the efficiency on offence) regarding all the playing positions. Coaches and other practitioners connected to the domain of basketball could utilize this set of criteria for the individual and team aspects of the performance follow-up and assessment in players throughout their sports career, from the cadettes' to the senior selections. Proposed set of criteria is the pressumption for the exact scientific and expert approach to the basketball performance (situation-related efficiency) evaluation and prediction--criterion variable. Weighting factors (coefficients of significance) for each criterion in relation to the playing positions should be determined on the next stage of developing a system of the performance evaluation criteria.     

Lead Us Not into Tanktation: A Simulation Modelling Approach to Gain Insights into Incentives for Sporting Teams to Tank

Annual draft systems are the principal method used by teams in major sporting leagues to recruit amateur players. These draft systems frequently take one of three forms: a lottery style draft, a weighted draft, or a reverse-order draft. Reverse-order drafts can create incentives for teams to deliberately under-perform, or tank, due to the perceived gain from obtaining quality players at higher draft picks. This paper uses a dynamic simulation model that captures the key components of a win-maximising sporting league, including the amateur player draft, draft choice error, player productivity, and between-team competition, to explore how competitive balance and incentives to under-perform vary according to league characteristics. We find reverse-order drafts can lead to some teams cycling between success and failure and to other teams being stuck in mid-ranking positions for extended periods of time. We also find that an incentive for teams to tank exists, but that this incentive decreases (i) as uncertainty in the ability to determine quality players in the draft increases, (ii) as the number of teams in the league reduces, (iii) as team size decreases, and (iv) as the number of teams adopting a tanking strategy increases. Simulation models can be used to explore complex stochastic dynamic systems such as sports leagues, where managers face difficult decisions regarding the structure of their league and the desire to maintain competitive balance.     

Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores

As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank‐ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of coevolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly‐used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6‐bisphosphate aldolase protein families as models. Calculations used unthresholded coevolution scores from which column‐specific properties such as sequence entropy and random noise were subtracted; “central” positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise coevolution scores: instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints—detectable by divergent algorithms—that occur at key protein locations. Finally, we discuss the fact that multiple patterns coexist in evolutionary data that, together, give rise to emergent protein functions. Proteins 2015; 83:2293–2306. © 2015 Wiley Periodicals, Inc.     

Basketball ability testing and category for players with mental retardation: 8-month training effect

Although sport for athletes with mental retardation (MR) is achieving an important role, the literature concerning basketball tests and training is still poor. The aims of this study were to verify whether the basketball test battery could be an appropriate modality to classify the players in the Promotion (Pro) category, to assess basketball abilities before (PRE) and after (POST) an 8-month training in players with MR in relation to Competitive (Comp) and Pro categories, to analyze the variation of specific basketball abilities based on subjects' MR diagnosis. Forty-one male basketball players with MR (17 Comp and 24 Pro; age range 18-45 years; MR: 15% mild, 54% moderate, 29% severe, and 2% profound) were assessed PRE and POST training through the basketball test battery, which assessed 4 ability levels of increasing difficulty (from I to IV), each one characterized by the analysis of fundamental areas (ball handling, reception, passing, and shooting). Level I was significantly changed after the intervention period regardless of the Category, whereas shooting was affected by the interaction between Category and Intervention. The results showed significant differences between categories in the scores of individual global, level I, level II, level III, and in all fundamental areas. Individual global score in both categories significantly increased. The players of Comp significantly improved in level III, in ball handling, reception, passing, and shooting scores. The players of Pro improved significantly in level II, in ball handling, reception, and passing scores. Individual global, ability levels I-III, and fundamental area scores were negatively correlated to the MR level indicating that the players with a lower MR obtained higher ability scores. In conclusion, it was found that the basketball test battery could be useful for improving and monitoring training in both Comp and Pro players.     

Body composition and physical fitness of female volleyball and basketball players of the Japan inter-high school championship teams

This study evaluated the body composition (underwater weighing) and cardiorespiratory function (VO(2)max and O(2)debt max measured by the treadmill exercise test) in 12 members of the women's volleyball team (mean age 17.4 years) and 11 members of the women's basketball team (mean age 17.6 years) that won the championship in the Japan Inter-high School Meeting. We also examined differences in the physical abilities between the members of the top teams of different events. The following results were obtained. (1) The mean values of the height and body weight were 168.7+/-5.89 cm and 59.7+/-5.73 kg in the volleyball players and 166.5+/-7.87 cm and 58.8+/-6.85 kg in the basketball players. (2) The mean %Fat was 18.4+/-3.29% in the volleyball players and 15.7+/-5.05% in the basketball players, and was similar to the reported values in elite adult players. (3) The mean VO(2)max was 2.78+/-0.32 L x min(-1) (46.5+/-2.90 ml x kg(-1) x min(-1)) in the volleyball players and 3.32+/-0.31 L x min(-1) (56.7+/-4.17 ml x kg(-1) x min(-1)) in the basketball players, and was similar to the reported values in elite adult players. (4) The mean O(2)debt max was 6.18+/-1.15 L (103.2+/-12.40 ml x kg(-1)) in the volleyball players and 7.92+/-1.80 L (134.3+/-23.24 ml x kg(-1)) in the basketball players. These values were 2.6 times and 3.3 times as high as the average values in high school students in general. (5) No significant difference was observed in any measured item of the physique, skinfold thickness, or body composition between the volleyball players and basketball players. (6) The VO(2)max and O(2)debt max were 22% and 28% higher in the basketball players than in the volleyball players.From these results, the female volleyball players and basketball players evaluated in this study had the physical abilities needed to win the championship in the Japan Inter-high School Meets, i.e. a large FFM and excellent aerobic and anaerobic work capacities. Also, basketball appears to require higher aerobic and anaerobic work capacities than volleyball.     

A systematic survey of centrality measures for protein-protein interaction networks

Background

Numerous centrality measures have been introduced to identify “central” nodes in large networks. The availability of a wide range of measures for ranking influential nodes leaves the user to decide which measure may best suit the analysis of a given network. The choice of a suitable measure is furthermore complicated by the impact of the network topology on ranking influential nodes by centrality measures. To approach this problem systematically, we examined the centrality profile of nodes of yeast protein-protein interaction networks (PPINs) in order to detect which centrality measure is succeeding in predicting influential proteins. We studied how different topological network features are reflected in a large set of commonly used centrality measures.

Results

We used yeast PPINs to compare 27 common of centrality measures. The measures characterize and assort influential nodes of the networks. We applied principal component analysis (PCA) and hierarchical clustering and found that the most informative measures depend on the network’s topology. Interestingly, some measures had a high level of contribution in comparison to others in all PPINs, namely Latora closeness, Decay, Lin, Freeman closeness, Diffusion, Residual closeness and Average distance centralities.

Conclusions

The choice of a suitable set of centrality measures is crucial for inferring important functional properties of a network. We concluded that undertaking data reduction using unsupervised machine learning methods helps to choose appropriate variables (centrality measures). Hence, we proposed identifying the contribution proportions of the centrality measures with PCA as a prerequisite step of network analysis before inferring functional consequences, e.g., essentiality of a node.

     

The influence of basic body and hand anthropometry on the results of different throwing tests in young handball and basketball players

The aim of this study was to investigate the relationships between basic body and specific hand anthropometric parameters with some specific and non-specific throw test results in young male handball and basketball players. The subjects included 34 handball and 38 basketball players of the 10-11 years old age group, 39 handball and 22 basketball players of the 12-13 years old age group and 39 handball players of the 14-15 years old age group. Body height and body mass, arms' span, height with outstretched hands and sitting height were the basic anthropometric parameters to be measured. For hand anthropometry, 15 specific hand parameters were measured using the method presented by Visnapuu & Jürim?e (2007). Stepwise multiple regression analysis indicated that medicine ball throw results in the youngest age group are highly dependent on the body height (handball players) and body mass (basketball players). In the middle age group, the most important parameter from the hand anthropometry is TL (handball) or height with outstretched hands (basketball). In the oldest group of handball players, the medicine ball throw results were dependent on the P2 from hand anthropometry and sitting height. Quite different anthropometric parameters appeared to influence the handball or basketball throw results. In the youngest age group, most important were body height (handball) or LFL (basketball). In the middle age group, the most important was height with outstretched hands and in the oldest handball players LFL and sitting height. Handball or basketball pass on speed depended on the combination of body mass and FS5 and body height with height with outstretched hands (even 61.40%, R2 x 100) in the oldest age group. The results of passing the handball or basketball on precision were dependent on body height and P3 or P1 among basketball players in the youngest group. In the middle age group the combination of FS3 and body mass and LFL and height with outstretched hands were the most influential. Anthropometric parameters influence on the passing of the ball on speed or precision is lower in handball players compared with basketball players. Our conclusion is that the basic anthropometric parameters are slightly more important than hand anthropometry that influenced different throw tests results in young handball and basketball players.     

Generalized walks-based centrality measures for complex biological networks

A strategy for zooming in and out the topological environment of a node in a complex network is developed. This approach is applied here to generalize the subgraph centrality of nodes in complex networks. In this case the zooming in strategy is based on the use of some known matrix functions which allow focusing locally on the environment of a node. When a zooming out strategy is applied new matrix functions are introduced, which give a more global picture of the topological surrounds of a node. These indices permit a modulation of the scales at which the environment of a node influences its centrality. We apply them to the study of 10 protein-protein interaction (PPI) networks. We illustrate the similarities and differences between the generalized subgraph centrality indices as well as among them and some classical centrality measures. We show here that the use of centrality indices based on the zooming in strategy identifies a larger number of essential proteins in the yeast PPI network than any of the other centrality measures studied.     

Body size and composition of National Football League players

The purpose of this study was to present a profile of body size and composition of National Football League (NFL) players prior to the start of the regular season. Fifty-three members of the Indianapolis Colts professional football team were measured for height, body mass, and percentage body fat using the BOD POD air-displacement plethysmography system during summer camp of the 2003 football season. These data were categorized by position for comparison with previous studies of NFL football players. The relationships observed were as follows (= represents nonsignificant; > represents p < or = 0.05): Height: Offensive Line = Defensive Line = Quarterbacks/Kickers/Punters = Tight Ends > Linebackers > Running Backs = Wide Receivers = Defensive Backs. Body Mass: Offensive Line = Defensive Line > Tight Ends = Linebackers > Running Backs = Quarterbacks/ Kickers/Punters > Wide Receivers = Defensive Backs. Percentage Body Fat: Offensive Line > Defensive Line > Quarterbacks/ Kickers/Punters = Linebackers = Tight Ends > Running Backs = Wide Receivers = Defensive Backs. Comparisons to teams in the 1970s indicate that body mass has increased only for offensive and defensive linemen; however, height and body fat among player positions have not dramatically changed. Furthermore, the body mass index is not an accurate measure or representation of body fat or obesity in NFL players. These data provide a basic template for size profiles and differences among various positions and allow comparisons with other studies for changes in the NFL over the past 3 decades.     

Investigation of readiness and perceived workload in junior female basketball players during a congested match schedule

This study aimed to: a) investigate the differences in workload and readiness between two junior female national basketball teams competing at different European Championships (EC); b) compare workload, readiness and match performance for players with longer and shorter playing times, and; c) examine the relationship between workload, readiness and match performance variables. Under-18 (U18) (n = 10, height = 179.9 ± 6.6 cm, body mass = 70.2 ± 5.1 kg) and under-20 (U20) female national basketball teams (n = 11, height = 178.4 ± 8.8 cm, body mass = 73.0 ± 9.7 kg) were monitored during congested match schedules encompassing 7 matches within 9 days. Daily workload was determined via the session rating of perceived exertion (sRPE workload); readiness was measured by heart-rate variability (HRV) and well-being (WB); and match performance was assessed using the efficiency statistic and playing time. Analysis of workload and readiness during the EC showed no statistically significant between-team differences in any variables except WB for the U18 team, which was lower on Day 8 compared to the U20 team (p = 0.03; effect size [ES] = large). Players accumulating longer playing time showed a higher sRPE workload (p = 0.01, ES = moderate) and efficiency statistic (p = 0.04, ES = moderate) while no readiness variable differed significantly (p > 0.05) compared to players with shorter playing time. Trivial-to-small correlations were observed between workload, readiness and match performance variables. The study shows that junior female basketball players were able to cope with a congested schedule of 7 matches in 9 days irrespective of the competition context or individual differences in workload. Finally, combining objective and subjective methods to assess workload and readiness is recommended due to the weak relationships observed between these methods.     

Towards a Methodology for Validation of Centrality Measures in Complex Networks

Background

Living systems are associated with Social networks — networks made up of nodes, some of which may be more important in various aspects as compared to others. While different quantitative measures labeled as “centralities” have previously been used in the network analysis community to find out influential nodes in a network, it is debatable how valid the centrality measures actually are. In other words, the research question that remains unanswered is: how exactly do these measures perform in the real world? So, as an example, if a centrality of a particular node identifies it to be important, is the node actually important?

Purpose

The goal of this paper is not just to perform a traditional social network analysis but rather to evaluate different centrality measures by conducting an empirical study analyzing exactly how do network centralities correlate with data from published multidisciplinary network data sets.

Method

We take standard published network data sets while using a random network to establish a baseline. These data sets included the Zachary''s Karate Club network, dolphin social network and a neural network of nematode Caenorhabditis elegans. Each of the data sets was analyzed in terms of different centrality measures and compared with existing knowledge from associated published articles to review the role of each centrality measure in the determination of influential nodes.

Results

Our empirical analysis demonstrates that in the chosen network data sets, nodes which had a high Closeness Centrality also had a high Eccentricity Centrality. Likewise high Degree Centrality also correlated closely with a high Eigenvector Centrality. Whereas Betweenness Centrality varied according to network topology and did not demonstrate any noticeable pattern. In terms of identification of key nodes, we discovered that as compared with other centrality measures, Eigenvector and Eccentricity Centralities were better able to identify important nodes.     

Profiling in basketball: physical and physiological characteristics of elite players

The purpose of this study was to describe structural and functional characteristics of elite Serbian basketball players and to evaluate whether players in different positional roles have different physical and physiological profiles. Five men's basketball teams participated in the study and competed in the professional First National League. Physiological measurements were taken of 60 players during the final week of their preparatory training for competition. According to positional roles, players were categorized as guards (n = 20), forwards (n = 20), and centers (n = 20). Guards were older (p < 0.01) and more experienced (p < 0.01) as compared with both forwards and centers. Centers were taller and heavier than guards and forwards (p < 0.01), whereas forwards had significantly higher height and weight than guards (p < 0.01). Centers had more body fat (p < 0.01) as compared with forwards and guards. Also, centers had significantly lower estimated VO(2)max values (p < 0.01) compared with forwards and guards. In addition, the highest heart rate frequencies during the last minute of the shuttle run test were lower in guards (p < 0.01) as compared with forwards and centers. Vertical jump power was significantly higher in centers (p < 0.01) as compared with guards. The results of the present study demonstrate that a strong relationship exists between body composition, aerobic fitness, anaerobic power, and positional roles in elite basketball.