scholarly journals A simple new method for identifying performance characteristics associated with success in elite tennis

2018 ◽  
Vol 14 (1) ◽  
pp. 43-50 ◽  
Author(s):  
Anna Fitzpatrick ◽  
Joseph A Stone ◽  
Simon Choppin ◽  
John Kelley
Keyword(s):  
Performance Analysis ◽  
Statistical Methods ◽  
Rank Order ◽  
Large Datasets ◽  
Performance Characteristics ◽  
New Method ◽  
Considerable Time ◽  
Simple Method ◽  
Suitable Alternative ◽  
Using Data

Performance analysis and identifying performance characteristics associated with success are of great importance to players and coaches in any sport. However, while large amounts of data are available within elite tennis, very few players employ an analyst or attempt to exploit the data to enhance their performance; this is partly attributable to the considerable time and complex techniques required to interpret these large datasets. Using data from the 2016 and 2017 French Open tournaments, we tested the agreement between the results of a simple new method for identifying important performance characteristics (the Percentage of matches in which the Winner Outscored the Loser, PWOL) and the results of two standard statistical methods to establish the validity of the simple method. Spearman’s rank-order correlations between the results of the three methods demonstrated excellent agreement, with all methods identifying the same three performance characteristics ( points won of 0–4 rally length, baseline points won and first serve points won) as strongly associated with success. Consequently, we propose that the PWOL method is valid for identifying performance characteristics associated with success in tennis, and is therefore a suitable alternative to more complex statistical methods, as it is simpler to calculate, interpret and contextualise.

scholarly journals Country of Origin Effects on the Average Annual Values of NHL Player Contracts

2019 ◽  
Vol 7 (2) ◽  
pp. 24
Author(s):  
Aju J. Fenn ◽  
Lucas Gerdes ◽  
Samuel Rothstein
Keyword(s):  
Quantile Regression ◽  
Fixed Effects ◽  
Country Of Origin ◽  
Large Datasets ◽  
National Hockey League ◽  
Dummy Variables ◽  
Country Of Origin Effects ◽  
Performance Statistics ◽  
Career Performance ◽  
Using Data

Using data from 2005 to 2016, this paper examines if players in the National Hockey League (NHL) are being paid a positive differential for their services due to the competition from the Kontinental Hockey League (KHL) and the Swedish Hockey League (SHL). In order to control for performance, we use two different large datasets, (N = 4046) and (N = 1717). In keeping with the existing literature, we use lagged performance statistics and dummy variables to control for the type of NHL contract. The first dataset contains lagged career performance statistics, while the performance statistics are based on the statistics generated during the years under the player’s previous contract. Fixed effects least squares (FELS) and quantile regression results suggest that player production statistics, contract status, and country of origin are significant determinants of NHL player salaries.

scholarly journals Emerging issues in genomic selection

2021 ◽  
Author(s):  
I Misztal ◽  
I Aguilar ◽  
D Lourenco ◽  
L Ma ◽  
J Steibel ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Sparse Matrices ◽  
Large Datasets ◽  
Single Step ◽  
Genomic Information ◽  
Long Term Effects ◽  
Additive Variance ◽  
Recent Developments ◽  
Emerging Issues ◽  
Using Data

Abstract Genomic selection is now practiced successfully across many species. However, many questions remain such as long-term effects, estimations of genomic parameters, robustness of GWAS with small and large datasets, and stability of genomic predictions. This study summarizes presentations from at the 2020 ASAS symposium. The focus of many studies until now is on linkage disequilibrium (LD) between two loci. Ignoring higher level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWAS studies using small genomic datasets frequently find many marker-trait associations whereas studies using much bigger datasets find only a few. Most current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for important effects for traits of interest. Artifacts arising in GWAS with small datasets can be minimized by using data from all animals (whether genotyped or not), realistic models, and methods that account for population structure. Recent developments permit computation of p-values from GBLUP, where models can be arbitrarily complex but restricted to genotyped animals only, and to single-step GBLUP that also uses phenotypes from ungenotyped animals. Stability was an important part of nongenomic evaluations, where genetic predictions were stable in the absence of new data even with low prediction accuracies. Unfortunately, genomic evaluations for such animals change because all animals with genotypes are connected. A top ranked animal can easily drop in the next evaluation, causing a crisis of confidence in genomic evaluations. While correlations between consecutive genomic evaluations are high, outliers can have differences as high as one SD. A solution to fluctuating genomic evaluations is to base selection decisions on groups of animals. While many issues in genomic selection have been solved, many new issues that require additional research continue to surface.

Capturing Protein Droplets: Label-free Visualization and Detection of Protein Liquid-Liquid Phase Separation with an Aggregation-Induced Emission Fluorogen

2021 ◽  
Author(s):  
Yan-Mei Li ◽  
Chu-Qiao Liang ◽  
Lin Wang ◽  
Yun-Yi Luo ◽  
Qian-Qian Li
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Liquid Phase Separation ◽  
New Method ◽  
Label Free ◽  
Simple Method ◽  
Aggregation Induced Emission ◽  
Liquid Liquid Phase Separation

We developed a new method for protein droplet visualization by means of a droplet probe (DroProbe) based on an aggregation-induced emission (AIE) fluorogen. A simple method for viscosity comparison of...

scholarly journals A Model for Selecting a Strategic Information System Using the FITradeoff

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Ana Paula Henriques de Gusmão ◽  
Cristina Pereira Medeiros
Keyword(s):  
Information System ◽  
Information Systems ◽  
Decision Maker ◽  
Additive Model ◽  
New Method ◽  
Strategic Information ◽  
Perceived Need ◽  
Using Data ◽  
Strategic Information System ◽  
Glass Packaging

This paper arose from the perceived need to make a contribution towards assessing a strategic information system by using a new method for eliciting the weights of criteria. This is considered one of the most complex and important stages in multicriteria models. Multicriteria models have been proposed to support decisions in the context of information systems given that problems in this field deal with many conflicting criteria. The new procedure for eliciting the weights of the criteria has the advantage of requiring less effort from the decision-maker and, thus, the risk of inconsistent answers is minimized. Therefore, a model based on this new procedure is proposed and applied using data from a glass packaging factory that needs to select a single information system from a set of systems previously identified as relevant. The results obtained are consistent both with the performance of alternatives and with the additive model used to evaluate the alternatives.

Functional Analysis of Intermittently Reinforced Behaviour: A Case Study

1999 ◽  
Vol 16 (4) ◽  
pp. 219-225 ◽  
Author(s):  
Don Tustin
Keyword(s):  
Functional Analysis ◽  
Problem Solving ◽  
Personality Disorder ◽  
Revealed Preference ◽  
New Method ◽  
Dependent Personality Disorder ◽  
Dependent Personality ◽  
Standard Problem ◽  
Using Data

AbstractFunctional analysis is used to identify potential reinforcers by generating hypotheses about possible functions of a behaviour. Current methods of functional analysis emphasise observations of events, especially consequences, that occur in the immediate environment of the behaviour. While these methods are well suited for assessing behaviour that is reinforced frequently, they are less appropriate for assessing behaviour that is reinforced only intermittently. A new method for conducting functional analysis is presented that is designed to assess intermittently reinforced behaviour. The new method is illustrated using data that were gathered from an extension of a standard problem-solving format. Data are interpreted using the principle of revealed preference that arose from behavioural economics. The revealed preference method is illustrated using information provided by a client with a dependent personality disorder.

scholarly journals Improved Specificity of a New Homogeneous Assay for LDL-Cholesterol in Serum with Abnormal Lipoproteins

2006 ◽  
Vol 52 (5) ◽  
pp. 886-888 ◽  
Author(s):  
Yasumasa Iwasaki ◽  
Hiroyuki Matsuyama ◽  
Nobuo Nakashima
Keyword(s):  
Clinical Practice ◽  
Obstructive Jaundice ◽  
Ldl Cholesterol ◽  
Performance Characteristics ◽  
New Method ◽  
Assay Performance ◽  
Basic Performance ◽  
Homogeneous Method ◽  
Homogeneous Assay ◽  
Improved Performance

Abstract Background: Although a homogeneous assay for serum LDL-cholesterol (LDL-C) has become a routine clinical procedure, problems remain in assay performance characteristics. Methods: We examined the performance of a recently developed automated homogeneous assay (New-Daiichi assay) for serum LDL-C and compared the results with those obtained by the current homogeneous method (Denka-Seiken assay) or by ultracentrifugation as a control. Results: The New-Daiichi assay showed satisfactory basic performance characteristics such as reproducibility, linearity, and stability. There was no interference in the assay by various substances examined. The LDL-C values obtained with this method correlated well with those obtained by ultracentrifugation. In samples from patients with obstructive jaundice, both methods detected cholesterol from abnormal lipoproteins (such as lipoprotein-X and -Y), but the New-Daiichi assay was less reactive and more specific for LDL-C. Conclusion: The new method has improved performance for the accurate measurement of LDL-C in clinical practice.

Investigation of the micropolar lubricant and thermal effects in the slot entry hybrid journal bearings

2017 ◽  
Vol 232 (11) ◽  
pp. 2103-2116 ◽  
Author(s):  
Pankaj Khatak ◽  
HC Garg
Keyword(s):  
Performance Analysis ◽  
Present Article ◽  
Thermal Effects ◽  
Three Dimensional ◽  
Journal Bearings ◽  
Performance Characteristics ◽  
Reliable Performance ◽  
Isothermal Characteristics

The present article studies the combined influence of the micropolar lubricant and thermal effects in the slot entry hybrid journal bearings. Bearing performance characteristics are computed by the concurrent solution of modified Reynolds, three-dimensional micropolar energy, and three-dimensional conduction equations. Thermohydrostatic characteristics of the slot entry hybrid journal bearings have been studied vis-à-vis isothermal characteristics. The results obtained numerically indicate that isoviscous assumption of the lubricant is incorrect and the bearing performance is significantly affected by the increase in temperature. Hence, it is essential to consider the thermal effects for the bearings operating with the micropolar lubricant for reliable performance analysis of the bearings.

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