The effect of the Video Assistant Referee on referee’s decisions in the Spanish LaLiga

2020 ◽  
pp. 174795412098011
Author(s):  
C Lago-Peñas ◽  
MA Gómez ◽  
R Pollard
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Final Decision ◽  
Association Football ◽  
Before And After ◽  
Speed Up ◽  
Playing Time ◽  
The Impact

Video Assistant Referee (VAR) was officially introduced into Association Football (Soccer) regulations in 2018. The aim of this study was to examine how the implementation of this technology has modified the play in elite soccer. The sample consists of all 760 matches played in the Spanish LaLiga during the seasons before and after the implementation of the VAR system. The following variables were recorded for each match and half: Fouls, Goals, Offsides, Penalties, Playing time, Red cards and Yellow cards. Match statistics were retrieved from the website of “Whoscored” ( www.whoscored.com ). A Mann-Whitney U test and Generalized linear model were used to compare seasons before and after the implementation of VAR. Overall, the findings of the present study showed that the VAR system does not dramatically change the play in elite soccer. Nevertheless: (i) there was a significant decrease in the number of offside after the implementation of VAR; (ii) there was a slight increase in the number of minutes added to the playing time in the first and second half and the full game; and (iii) in most of 70% of all matches, the checks of the match-changing incidents did not lead to review. Moreover, the impact of the VAR system on the game decreases with VAR-only reviews, where the final decision was only based on the communication with the VAR, compared to matches with on-field reviews, where the main referee reviewed the footage on a monitor near the pitch. These findings suggest that to reduce time-wasting and speed up the match, the number of on-field reviews should be reduced.

The influence of the video assistant referee on the Chinese Super League

2020 ◽  
Vol 15 (5-6) ◽  
pp. 662-668
Author(s):  
Bo Han ◽  
Qiu Chen ◽  
Carlos Lago-Peñas ◽  
Changquan Wang ◽  
Tianbiao Liu
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Research Result ◽  
High Tech ◽  
Professional Football ◽  
Auxiliary Equipment ◽  
Home Team ◽  
Playing Time ◽  
The Impact ◽  
Super League

With the development and advancement of technology, various types of high-tech auxiliary equipment have been gradually introduced into football matches to assist referees to officiate the game. The Chinese football Super League (CSL) introduced the video assistant referee (VAR) in the 2018 season. The purpose of this study is to explore the impact of the introduction of VAR on football matches and on referees’ performance. This study compared the data of all 240 games without VAR in the season 2017 and all 240 games with VAR in the season 2018 using Generalized Linear Model (GLM) and means comparison. The following match variables were considered: goals, penalties, red cards, yellow cards, fouls, offsides, playing time in the first half, playing time in the second half and total playing time. The study found that: 1) After the introduction of VAR, the number of offsides and fouls in the Chinese Super League dropped significantly (p < .001); 2) the playing time in the first and second half and the total playing time increased significantly(p < .001); 3) after the introduction of VAR, the home team advantage decreased slightly. The research result can help to better understand the impact of VAR on professional football, especially on the Chinese football Super League, it can also help referees to optimize their refereeing strategy.

A simulation study of impacts of error structure on modeling stock–recruitment data using generalized linear models

2004 ◽  
Vol 61 (1) ◽  
pp. 122-133 ◽  
Author(s):  
Yan Jiao ◽  
Yong Chen ◽  
David Schneider ◽  
Joe Wroblewski
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Linear Models ◽  
Least Squares Method ◽  
Estimation Of Parameters ◽  
Estimation Errors ◽  
Error Structure ◽  
Stock Recruitment ◽  
Data Points ◽  
The Impact

Stock–recruitment (S–R) models are commonly fitted to S–R data with a least-squares method. Errors in modeling are usually assumed to be normal or lognormal, regardless of whether such an assumption is realistic. A Monte Carlo simulation approach was used to evaluate the impact of the assumption of error structure on S–R modeling. The generalized linear model, which can readily deal with different error structures, was used in estimating parameters. This study suggests that the quality of S–R parameter estimation, measured by estimation errors, can be influenced by the realism of error structure assumed in an estimation, the number of S–R data points, and the number of outliers in modeling. A small number of S–R data points and the presence of outliers in S–R data could increase the difficulty in identifying an appropriate error structure in modeling, which might lead to large biases in the S–R param eter estimation. This study shows that generalized linear model methods can help identify an appropriate error distribution in S–R modeling, leading to an improved estimation of parameters even when there are outliers and the number of S–R data points is small. We recommend the generalized linear model be used for quantifying stock–recruitment relationships.

scholarly journals A Bayesian Analysis of the Inversion of the SARS-COV-2 Case Rate in the Countries of the 2020 European Football Championship

2021 ◽  
Author(s):  
Luca Casini ◽  
Marco Roccetti
Keyword(s):  
Bayesian Analysis ◽  
Linear Model ◽  
Generalized Linear Model ◽  
Piecewise Regression ◽  
Increase Rate ◽  
Before And After ◽  
Case Rate ◽  
European Football

While Europe was beginning to deal with the resurgence of COVID-19 due to the Delta variant, the European football championship took place, June 11 - July 11, 2021. We studied the inversion in the decrease/increase rate of new SARS-COV-2 infections in the countries of the tournament, investigating the hypothesis of an association. Using a Bayesian piecewise regression with a Poisson Generalized Linear Model, we looked for a changepoint in the timeseries of the new SARS-COV-2 cases of each country, expecting it to appear not later than two to three weeks after the date of their first match. The two slopes, before and after the changepoint, were used to discuss the reversal from a decreasing to an increasing rate of the infections. For 17 out of 22 countries (77%) the changepoint came on average 14.97 days after their first match [95% CI 12.29 to 17.47]. For all those 17 countries, the changepoint coincides with an inversion from a decreasing to an increasing rate of the infections. Before the changepoint, the new cases were decreasing, halving on average every 18.07 days [95% CI 11.81 to 29.42]. After the changepoint, the cases begin to increase, doubling every 29.10 days [95% CI 14.12 to 49.78]. This inversion in the SARS-COV-2 case rate, happened during the tournament, provides evidence in favor of a relationship

The impact of global positioning systems and plotters on fishing power in the northern prawn fishery, Australia

1998 ◽  
Vol 55 (7) ◽  
pp. 1645-1651 ◽  
Author(s):  
Carolyn M Robins ◽  
You-Gan Wang ◽  
David Die
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Global Positioning Systems ◽  
Commercial Catch ◽  
Positioning Systems ◽  
Catch Data ◽  
Global Positioning ◽  
Management Controls ◽  
The Impact ◽  
Northern Prawn Fishery

The impact of global positioning systems (GPS) and plotter systems on the relative fishing power of the northern prawn fishery fleet on tiger prawns (Penaeus esculentus Haswell, 1879, and P. semisulcatus de Haan, 1850) was investigated from commercial catch data. A generalized linear model was used to account for differences in fishing power between boats and changes in prawn abundance. It was found that boats that used a GPS alone had 4% greater fishing power than boats without a GPS. The addition of a plotter raised the power by 7% over boats without the equipment. For each year between the first to third that a fisher has been working with plotters, there is an additional 2 or 3% increase. It appears that when all boats have a GPS and plotter for at least 3 years, the fishing power of the fleet will increase by 12%. Management controls have reduced the efficiency of each boat and lowered the number of days available to fish, but this may not have been sufficient to counteract the increases. Further limits will be needed to maintain the desired levels of mortality.

scholarly journals A Bayesian Analysis of the Inversion of the SARS-COV-2 Case Rate in the Countries of the 2020 European Football Championship

2021 ◽  
Vol 13 (8) ◽  
pp. 212
Author(s):  
Luca Casini ◽  
Marco Roccetti
Keyword(s):  
Bayesian Analysis ◽  
Linear Model ◽  
Generalized Linear Model ◽  
Piecewise Regression ◽  
Before And After ◽  
Case Rate ◽  
European Football

While Europe was beginning to deal with the resurgence of COVID-19 due to the Delta variant, the European football championship took place from 11 June to 11 July 2021. We studied the inversion in the decreased/increased rate of new SARS-COV-2 infections in the countries of the tournament, investigating the hypothesis of an association. Using a Bayesian piecewise regression with a Poisson generalized linear model, we looked for a changepoint in the timeseries of the new SARS-COV-2 cases of each country, expecting it to appear not later than two to three weeks after the date of their first match. The two slopes, before and after the changepoint, were used to discuss the reversal from a decreasing to an increasing rate of the infections. For 17 out of 22 countries (77%) the changepoint came on average 14.97 days after their first match (95% CI 12.29–17.47). For all those 17 countries, the changepoint coincides with an inversion from a decreasing to an increasing rate of the infections. Before the changepoint, the new cases were decreasing, halving on average every 18.07 days (95% CI 11.81–29.42). After the changepoint, the cases begin to increase, doubling every 29.10 days (95% CI 14.12–9.78). This inversion in the SARS-COV-2 case rate, which happened during the tournament, provides evidence in favor of a relationship.

scholarly journals A Bayesian Analysis of the Inversion of the SARS-COV-2 Case Rate in the Countries of the 2020 European Football Championship

2021 ◽  
Author(s):  
Luca Casini ◽  
Marco Roccetti
Keyword(s):  
Bayesian Analysis ◽  
Linear Model ◽  
Generalized Linear Model ◽  
Piecewise Regression ◽  
Increase Rate ◽  
Before And After ◽  
Case Rate ◽  
European Football

While Europe was beginning to deal with the resurgence of COVID-19 due to the Delta variant, the European football championship took place, June 11 - July 11, 2021. We studied the inversion in the decrease/increase rate of new SARS-COV-2 infections in the countries of the tournament, investigating the hypothesis of an association. Using a Bayesian piecewise regression with a Poisson Generalized Linear Model, we looked for a changepoint in the timeseries of the new SARS-COV-2 cases of each country, expecting it to appear within four weeks since the date of their first match. The two slopes, before and after the changepoint, were used to discuss the reversal from a decreasing to an increasing rate of the infections. 17 out of 22 countries (77%) have had a changepoint 14.97 days after their first match [95% CI 12.29 to 17.47]. For all those 17 countries, the changepoint coincides with an inversion from a decreasing to an increasing rate of the infections. Before the changepoint, the new cases were decreasing, halving on average every 18.07 days [95% CI 11.81 to 29.42]. After the changepoint, the cases begin to increase, doubling every 29.10 days [95% CI 14.12 to 49.78]. This inversion in the SARS-COV-2 case rate, happened during the tournament, provides evidence in favor of a relationship.

scholarly journals Impacts of ivermectin mass drug administration for onchocerciasis on mosquito populations of Ogun state, Nigeria

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Olaitan Olamide Omitola ◽  
Cynthia Uchechukwu Umunnakwe ◽  
Adedotun Ayodeji Bayegun ◽  
Samuel Akinjide Anifowose ◽  
Hammed Oladeji Mogaji ◽  
...  
Keyword(s):  
Linear Model ◽  
Drug Administration ◽  
Mass Drug Administration ◽  
Generalized Linear Model ◽  
The Other ◽  
Climatic Data ◽  
Ogun State ◽  
Parity Rate ◽  
The Impact ◽  
Indoor And Outdoor

Abstract Background The impact of single-dose mass drug administration (MDA) of ivermectin for onchocerciasis on mosquito populations was investigated in Ogun State, Nigeria. Methods Indoor and outdoor collection of mosquitoes was carried out in two intervention (IC) and two control communities (CC) at three different periods: pre-MDA (baseline), 2–3 days after MDA and 13–14 days after MDA. The density and parity rate of female Anopheles and Culex mosquitoes were determined and compared. Environmental and climatic data of study locations were obtained to perform generalized linear model analysis. Results A total of 1399 female mosquitoes were collected, including 1227 Anopheles and 172 Culex mosquitoes. There was a similar magnitude of reduction in the indoor density of Anopheles by 29% in the IC and CC 2–3 days post-MDA but the reduction in indoor parity rate was significantly higher (p = 0.021) in the IC, reducing by more than 50%. In the IC, observation of a significant reduction at 2–3 days post-MDA was consistent for both the indoor density (1.43 to 1.02) and indoor parity rate (95.35% to 44.26%) of Anopheles mosquitoes. The indoor parity rate of Anopheles remained significantly reduced (75.86%) 13–14 post-MDA. On the other hand, the indoor density of Culex increased from 0.07 to 0.10 at 2–3 days post-MDA while the indoor parity rate of Culex did not change. The outdoor density of Anopheles in the IC increased (p = 0.394) from 0.58 to 0.90 at 2–3 days post-MDA; a similar observation was consistent for the outdoor density (2.83 to 3.90) and outdoor parity rate (70.59% to 97.44%) of Culex, while the outdoor parity rate of Anopheles reduced from 85.71 to 66.67% at 2–3 days post-MDA. A generalized linear model showed that ivermectin MDA significantly caused a reduction in both the indoor density (p < 0.001) and indoor parity rate (p = 0.003) of Anopheles in the IC. Conclusion Ivermectin MDA resulted in the reduction of both the survival and density of Anopheles mosquitoes. This has strong implications for malaria transmission, which depends strongly on vector survival. Graphic abstract

scholarly journals Initial Selection and Cause of Disability for Individual Permanent Health Insurance

2000 ◽  
Vol 30 (2) ◽  
pp. 369-389
Author(s):  
María Cristina Gutiérrez-Delgado ◽  
Athol A. Korabinski
Keyword(s):  
Health Insurance ◽  
Mental Disorders ◽  
Moral Hazard ◽  
Linear Model ◽  
Generalized Linear Model ◽  
Musculoskeletal Diseases ◽  
Early Years ◽  
Insurance Claim ◽  
The Impact ◽  
Initial Selection

AbstractWe investigate the influence of initial selection (the impact of underwriting during the early years of a policy's life) on individual Permanent Health Insurance claim inceptions. In Gutiérrez-Delgado (1999) a decreasing trend was found. In this paper we include the effect of cause of disability and fit a generalized linear model in order to gain a greater understanding of the phenomenon. Both effects, policy duration and cause of disability, are found to have a significant effect on the number of claims. We describe their influence using factors that collect the information available through the fitted model. Results from both factors suggest that the grouping of diseases selected for the research helps to explain partially our earlier results. In addition there is some evidence of moral hazard in mental disorders and musculoskeletal diseases which also contributes to the understanding of the negative trend found.

scholarly journals Open Application of Statistical and Machine Learning Models to Explore the Impact of Environmental Exposures on Health and Disease: An Asthma Use Case

2021 ◽  
Vol 18 (21) ◽  
pp. 11398
Author(s):  
Bo Lan ◽  
Perry Haaland ◽  
Ashok Krishnamurthy ◽  
David B. Peden ◽  
Patrick L. Schmitt ◽  
...  
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Linear Model ◽  
Generalized Linear Model ◽  
Environmental Exposures ◽  
Predictor Variables ◽  
Use Case ◽  
Airborne Particulate ◽  
Particulate Exposure ◽  
The Impact

ICEES (Integrated Clinical and Environmental Exposures Service) provides a disease-agnostic, regulatory-compliant approach for openly exposing and analyzing clinical data that have been integrated at the patient level with environmental exposures data. ICEES is equipped with basic features to support exploratory analysis using statistical approaches, such as bivariate chi-square tests. We recently developed a method for using ICEES to generate multivariate tables for subsequent application of machine learning and statistical models. The objective of the present study was to use this approach to identify predictors of asthma exacerbations through the application of three multivariate methods: conditional random forest, conditional tree, and generalized linear model. Among seven potential predictor variables, we found five to be of significant importance using both conditional random forest and conditional tree: prednisone, race, airborne particulate exposure, obesity, and sex. The conditional tree method additionally identified several significant two-way and three-way interactions among the same variables. When we applied a generalized linear model, we identified four significant predictor variables, namely prednisone, race, airborne particulate exposure, and obesity. When ranked in order by effect size, the results were in agreement with the results from the conditional random forest and conditional tree methods as well as the published literature. Our results suggest that the open multivariate analytic capabilities provided by ICEES are valid in the context of an asthma use case and likely will have broad value in advancing open research in environmental and public health.

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