Effect of quality of opposition on game performance indicators in elite male volleyball

2021 ◽  
pp. 174795412110137
Author(s):  
Sotirios Drikos ◽  
Karolina Barzouka ◽  
Dimitrios G Balasas ◽  
Konstantinos Sotiropoulos
Keyword(s):  
Cluster Analysis ◽  
Logistic Regression ◽  
Performance Indicators ◽  
Interactive Process ◽  
Performance Factors ◽  
Binomial Logistic Regression ◽  
Skill Performance ◽  
Game Performance

Performance in a volleyball match is the result of a dynamic and interactive process between two teams. The current study aimed to investigate the influence of the quality of opposition on skill performance indicators. A total of 550 teams’ performances (N = 550) from 275 sets of men’s European Championship 2019 was recorded and the effectiveness of 12 parameters from 5 basic volleyball skills was analyzed. A two-step cluster analysis was performed to divide 24 teams into three quality groups (upper, middle, lower) and 6 types of match status were created according to the quality of the opponents. Binomial logistic regression showed that for each type of match, the key performance factors that discriminate win and loss are differentiated, while the efficacy of attack win is associated with the success almost with all contexts studied. Other significant parameters were serve aces for matches between upper-quality teams, opponent’s errors for matches between teams of different quality and avoidance of blocked attacks for balanced matches. The findings emphasize the need for coaches to plan strategies that allow players with special serving abilities to risk for an ace, to enhance the side-out skills of their team and to work detailed on attack coverage systems.

scholarly journals Identifying Basketball Performance Indicators in Regular Season and Playoff Games

2013 ◽  
Vol 36 (1) ◽  
pp. 161-168 ◽  
Author(s):  
Javier García ◽  
Sergio J. Ibáñez ◽  
Raúl Martinez De Santos ◽  
Nuno Leite ◽  
Jaime Sampaio
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Performance Indicators ◽  
Training Programs ◽  
Practical Applications ◽  
Basketball Game ◽  
Point Field ◽  
Game Performance ◽  
Conditioning Programs

The aim of the present study was to identify basketball game performance indicators which best discriminate winners and losers in regular season and playoffs. The sample used was composed by 323 games of ACB Spanish Basketball League from the regular season (n=306) and from the playoffs (n=17). A previous cluster analysis allowed splitting the sample in balanced (equal or below 12 points), unbalanced (between 13 and 28 points) and very unbalanced games (above 28 points). A discriminant analysis was used to identify the performance indicators either in regular season and playoff games. In regular season games, the winning teams dominated in assists, defensive rebounds, successful 2 and 3-point field-goals. However, in playoff games the winning teams’ superiority was only in defensive rebounding. In practical applications, these results may help the coaches to accurately design training programs to reflect the importance of having different offensive set plays and also have specific conditioning programs to prepare for defensive rebounding.

The Quality of a Surgeon Defined by Internal Medicine and Family Practice Physicians: A Closed-Ended Survey with Importance Scale

2007 ◽  
Vol 73 (5) ◽  
pp. 481-483
Author(s):  
Eldo E. Frezza ◽  
Mitchell S. Wachtel
Keyword(s):  
Internal Medicine ◽  
Logistic Regression ◽  
Family Practice ◽  
Binomial Logistic Regression ◽  
Family Practice Physicians ◽  
To Receive ◽  
Selection Of

An anonymously completed, closed-ended questionnaire with an importance scale was sent to physicians to assess which qualities were important in their selection of a surgeon. Differences in proportions of rankings that were designated “extremely important” were assessed by binomial logistic regression was used. Null hypotheses were rejected if P < 0.05. Forty-two of 61 questionnaires were returned for analysis. Differences between dependability and other characteristics were statistically significant (G = 35.62, P = 0.001). The only characteristics that were statistically significantly less likely to receive a ranking of “extremely important” were facility appearance, subspecialty fellowship, and graduation from a good residency. All other differences could have been explained by chance ( P > 0.05). Surgeons’ character, equipment, and staffing of the facility were ranked extremely important, whereas training of the surgeon or the appearance of the facility was not.

Computable metrics of personal performance in software development teams

2019 ◽  
Author(s):  
Andriy Lishchytovych ◽  
Volodymyr Pavlenko
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Product Quality ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Project Manager ◽  
Development Life Cycle ◽  
Software Product ◽  
Software Development Life Cycle

The present article describes setup, configuration and usage of the key performance indicators (KPIs) of members of project teams involved into the software development life cycle. Key performance indicators are described for the full software development life cycle and imply the deep integration with both task tracking systems and project code management systems, as well as a software product quality testing system. To illustrate, we used the extremely popular products - Atlassian Jira (tracking development tasks and bugs tracking system) and git (code management system). The calculation of key performance indicators is given for a team of three developers, two testing engineers responsible for product quality, one designer, one system administrator, one product manager (responsible for setting business requirements) and one project manager. For the key members of the team, it is suggested to use one integral key performance indicator per the role / team member, which reflects the quality of the fulfillment of the corresponding role of the tasks. The model of performance indicators is inverse positive - the initial value of each of the indicators is zero and increases in the case of certain deviations from the standard performance of official duties inherent in a particular role. The calculation of the proposed key performance indicators can be fully automated (in particular, using Atlassian Jira and Atlassian Bitbucket (git) or any other systems, like Redmine, GitLab or TestLink), which eliminates the human factor and, after the automation, does not require any additional effort to calculate. Using such a tool as the key performance indicators allows project managers to completely eliminate bias, reduce the emotional component and provide objective data for the project manager. The described key performance indicators can be used to reduce the time required to resolve conflicts in the team, increase productivity and improve the quality of the software product.

Principals’ Policy Preferences concerning Accountability: Implications for Key Competencies, Performance Indicators, and Professional Development

1995 ◽  
Vol 5 (5) ◽  
pp. 448-481 ◽  
Author(s):  
R. J. S. Mac Macpherson ◽  
Margaret Taplin
Keyword(s):  
Professional Development ◽  
Performance Indicators ◽  
Policy Preferences ◽  
Development Programs ◽  
Stakeholder Groups ◽  
Key Competencies ◽  
Professional Development Programs ◽  
Accountability Practices ◽  
State Schools

In this paper, we examine the policy preferences of Tasmania's principals concerning accountability criteria and processes, compare their views to other stakeholder groups, and identify issues that warrant attention in principals’ professional development programs. We show that there are many criteria and processes related to the quality of learning, teaching, and leadership that are valued by all stakeholder groups, including principals. We conclude that Tasmanian state schools probably need to review and develop their accountability policies, and that the professional development will need to prepare leaders for specific forms of performance and generate key competencies if more educative forms of accountability practices are to be realised in practice.

scholarly journals Galileo L10 Satellites: Orbit, Clock and Signal-in-Space Performance Analysis

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1695
Author(s):  
Constantin-Octavian Andrei ◽  
Sonja Lahtinen ◽  
Markku Poutanen ◽  
Hannu Koivula ◽  
Jan Johansson
Keyword(s):  
Performance Indicators ◽  
Satellite System ◽  
Short Term ◽  
Orbital Inclination ◽  
Navigation Data ◽  
Periodic Signals ◽  
Global Navigation Satellite ◽  
Minor Correction ◽  
Very High

The tenth launch (L10) of the European Global Navigation Satellite System Galileo filled in all orbital slots in the constellation. The launch carried four Galileo satellites and took place in July 2018. The satellites were declared operational in February 2019. In this study, we report on the performance of the Galileo L10 satellites in terms of orbital inclination and repeat period parameters, broadcast satellite clocks and signal in space (SiS) performance indicators. We used all available broadcast navigation data from the IGS consolidated navigation files. These satellites have not been reported in the previous studies. First, the orbital inclination (56.7±0.15°) and repeat period (50680.7±0.22 s) for all four satellites are within the nominal values. The data analysis reveals also 13.5-, 27-, 177- and 354-days periodic signals. Second, the broadcast satellite clocks show different correction magnitude due to different trends in the bias component. One clock switch and several other minor correction jumps have occurred since the satellites were declared operational. Short-term discontinuities are within ±1 ps/s, whereas clock accuracy values are constantly below 0.20 m (root-mean-square—rms). Finally, the SiS performance has been very high in terms of availability and accuracy. Monthly SiS availability has been constantly above the target value of 87% and much higher in 2020 as compared to 2019. Monthly SiS accuracy has been below 0.20 m (95th percentile) and below 0.40 m (99th percentile). The performance figures depend on the content and quality of the consolidated navigation files as well as the precise reference products. Nevertheless, these levels of accuracy are well below the 7 m threshold (95th percentile) specified in the Galileo service definition document.

scholarly journals COVID-19-Related Changes in Perceived Household Food Waste in the United States: A Cross-Sectional Descriptive Study

2021 ◽  
Vol 18 (3) ◽  
pp. 1104
Author(s):  
Kelly Cosgrove ◽  
Maricarmen Vizcaino ◽  
Christopher Wharton
Keyword(s):  
Logistic Regression ◽  
Food Waste ◽  
The United States ◽  
Food Groups ◽  
Related Factors ◽  
Cross Sectional ◽  
Household Level ◽  
Binomial Logistic Regression ◽  
Household Food ◽  
Fresh Vegetables

Food waste contributes to adverse environmental and economic outcomes, and substantial food waste occurs at the household level in the US. This study explored perceived household food waste changes during the COVID-19 pandemic and related factors. A total of 946 survey responses from primary household food purchasers were analyzed. Demographic, COVID-19-related household change, and household food waste data were collected in October 2020. Wilcoxon signed-rank was used to assess differences in perceived food waste. A hierarchical binomial logistic regression analysis was conducted to examine whether COVID-19-related lifestyle disruptions and food-related behavior changes increased the likelihood of household food waste. A binomial logistic regression was conducted to explore the contribution of different food groups to the likelihood of increased food waste. Perceived food waste, assessed as the estimated percent of food wasted, decreased significantly during the pandemic (z = −7.47, p < 0.001). Food stockpiling was identified as a predictor of increased overall food waste during the pandemic, and wasting fresh vegetables and frozen foods increased the odds of increased food waste. The results indicate the need to provide education and resources related to food stockpiling and the management of specific food groups during periods of disruption to reduce food waste.

scholarly journals Application of Logistic Regression to Determine The Quality of Foreign Tourists to Indonesia

2021 ◽  
Vol 1863 (1) ◽  
pp. 012029
Author(s):  
Neli Agustina ◽  
Chaterina D. Puspita ◽  
Dini Arifatin ◽  
Ricky Yordani
Keyword(s):  
Logistic Regression

scholarly journals Study on the relationship of depression, anxiety, lifestyle and eating habits with the severity of reflux esophagitis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rongxin Wang ◽  
Jing Wang ◽  
Shuiqing Hu
Keyword(s):  
Quality Of Life ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Reflux Esophagitis ◽  
Eating Habits ◽  
Positive Correlation ◽  
Relationship Of ◽  
The Relationship

Abstract Background The etiology of reflux esophagitis (RE) is multi-factorial. This study analyzed the relationship of depression, anxiety, lifestyle and eating habits with RE and its severity and further explored the impact of anxiety and depression on patients’ symptoms and quality of life. Methods From September 2016 to February 2018, a total of 689 subjects at Xuanwu Hospital Capital Medical University participated in this survey. They were divided into the RE group (patients diagnosed with RE on gastroscopy, n = 361) and the control group (healthy individuals without heartburn, regurgitation and other gastrointestinal symptoms, n = 328). The survey included general demographic information, lifestyle habits, eating habits, comorbidities, current medications, the gastroesophageal reflux disease (GERD) questionnaire (GerdQ), the Patient Health Questionnaire-9 depression scale and the General Anxiety Disorder-7 anxiety scale. Results The mean age and sex ratio of the two groups were similar. Multivariate logistic regression analysis identified the following factors as related to the onset of RE (p < 0.05): low education level; drinking strong tea; preferences for sweets, noodles and acidic foods; sleeping on a low pillow; overeating; a short interval between dinner and sleep; anxiety; depression; constipation; history of hypertension; and use of oral calcium channel blockers. Ordinal logistic regression analysis revealed a positive correlation between sleeping on a low pillow and RE severity (p = 0.025). Depression had a positive correlation with the severity of symptoms (rs = 0.375, p < 0.001) and patients’ quality of life (rs = 0.306, p < 0.001), whereas anxiety showed no such association. Conclusions Many lifestyle factors and eating habits were correlated with the onset of RE. Notably, sleeping on a low pillow was positively correlated with RE severity, and depression was positively related to the severity of symptoms and patients’ quality of life.

scholarly journals Ordinal outcome analysis improves the detection of between-hospital differences in outcome

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
I. E. Ceyisakar ◽  
N. van Leeuwen ◽  
Diederik W. J. Dippel ◽  
Ewout W. Steyerberg ◽  
H. F. Lingsma
Keyword(s):  
Logistic Regression ◽  
Quality Of Care ◽  
Outcome Measures ◽  
Statistical Power ◽  
Ordinal Scale ◽  
Efficiency Gain ◽  
Number Of Patients ◽  
Dichotomous Outcomes ◽  
Ordinal Outcome

Abstract Background There is a growing interest in assessment of the quality of hospital care, based on outcome measures. Many quality of care comparisons rely on binary outcomes, for example mortality rates. Due to low numbers, the observed differences in outcome are partly subject to chance. We aimed to quantify the gain in efficiency by ordinal instead of binary outcome analyses for hospital comparisons. We analyzed patients with traumatic brain injury (TBI) and stroke as examples. Methods We sampled patients from two trials. We simulated ordinal and dichotomous outcomes based on the modified Rankin Scale (stroke) and Glasgow Outcome Scale (TBI) in scenarios with and without true differences between hospitals in outcome. The potential efficiency gain of ordinal outcomes, analyzed with ordinal logistic regression, compared to dichotomous outcomes, analyzed with binary logistic regression was expressed as the possible reduction in sample size while keeping the same statistical power to detect outliers. Results In the IMPACT study (9578 patients in 265 hospitals, mean number of patients per hospital = 36), the analysis of the ordinal scale rather than the dichotomized scale (‘unfavorable outcome’), allowed for up to 32% less patients in the analysis without a loss of power. In the PRACTISE trial (1657 patients in 12 hospitals, mean number of patients per hospital = 138), ordinal analysis allowed for 13% less patients. Compared to mortality, ordinal outcome analyses allowed for up to 37 to 63% less patients. Conclusions Ordinal analyses provide the statistical power of substantially larger studies which have been analyzed with dichotomization of endpoints. We advise to exploit ordinal outcome measures for hospital comparisons, in order to increase efficiency in quality of care measurements. Trial registration We do not report the results of a health care intervention.

Systematic Literature Review on Smart Mobility: A Framework for Future “Quantitative” Developments

2021 ◽  
pp. 088541222199424
Author(s):  
Mauro Francini ◽  
Lucia Chieffallo ◽  
Annunziata Palermo ◽  
Maria Francesca Viapiana
Keyword(s):  
Cluster Analysis ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Performance Indicators ◽  
State Of The Art ◽  
Measurement Model ◽  
Broader Impacts ◽  
Research Goal ◽  
Smart Mobility ◽  
Definition Of

This work aims to reorganize theoretical and empirical research on smart mobility through the systematic literature review approach. The research goal is to reach an extended and shared definition of smart mobility using the cluster analysis. The article provides a summary of the state of the art that can have broader impacts in determining new angles for approaching research. In particular, the results will be a reference for future quantitative developments for the authors who are working on the construction of a territorial measurement model of the smartness degree, helping them in identifying performance indicators consistent with the definition proposed.

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