Decision Making within an NFL Context Using Multiple Objective Decision Analysis

The National Football League (NFL) is the most popular sports league in the world, with millions of viewers every game and billions of dollars generated every season. Statistics are an important part of an NFL team’s business operating model and contribute greatly towards their decision making. Every season, general managers try to sign players that give the team the highest probability of winning games throughout the year. There are many factors that go into this decision, including the amount of money the team has to spend and the value that available players can bring to a team. Teams must abide by a league-sanctioned salary cap to pay players that they believe will give their team the best probability of winning. There are many statistics currently used in the NFL to value players, but this research aims to use multiple objective decision analysis to combine aspects of a player into one value for a given position. The scope of this research will be focused on the wide receiver group specifically, but the methodology used can be adapted to any position group within an NFL team. This research will provide a new way of quantifying players’ value for the use of decision makers in the decision-making process of signing free agents to their team

Fuzzy Logic and Its Application in Football Team Ranking

Fuzzy set theory and fuzzy logic are a highly suitable and applicable basis for developing knowledge-based systems in physical education for tasks such as the selection for athletes, the evaluation for different training approaches, the team ranking, and the real-time monitoring of sports data. In this paper, we use fuzzy set theory and apply fuzzy clustering analysis in football team ranking. Based on some certain rules, we propose four parameters to calculate fuzzy similar matrix, obtain fuzzy equivalence matrix and the ranking result for our numerical example, T7, T3, T1, T9, T10, T8, T11, T12, T2, T6, T5, T4, and investigate four parameters sensitivity analysis. The study shows that our fuzzy logic method is reliable and stable when the parameters change in certain range

SISTEM PENDUKUNG KEPUTUSAN PENENTUAN ATLET BERBAKAT MENGGUNAKAN METODE FUZZY MAMDANI

AbstrakPerkembangan taekwondo di Kota Pontianak pada saat ini sangat cepat dan persaingan antara tiap atlet di Kota Pontianak sangat ketat. Kebijaksanaan pelatih dalam mengambil sebuah keputusan untuk memilih atlet yang akan diberangkat ke kejuaraan tingkat nasional bukanlah hal yang mudah, karena perlu melakukan pertimbangan supaya mendapatkan hasil medali yang terbaik di tingkat nasional.      Sistem pendukung keputusan yang dibangun menggunakan metode fuzzy mamdani dalam pemrosesan data input dan output, serta informasi pendukung berupa rangking atlet yang sangat mendukung dalam pengambilan keputusan untuk menentukan seorang atlet untuk menjadi atlet yang dipilih mengikuti kejuaraan di tingkat nasional.      Hasil dari penelitian ini dapat memberi suatu bantuan kepada pelatih taekwondo untuk memilih atlet yang akan diturunkan di kejuaraan tingkat nasional. Pengujian sistem ini dilakukan dengan membandingkan hasil sistem dengan total bobot perolehan medali dengan tingkat korelasi sebesar 0,8

Designing Sports Player’s Valuation Indices (Case Study: Volleyball Players)

The purpose of the present article is to design indicators and variables that represent the value of volleyball players. This research method is applied, which was done in a quantitative and qualitative way. The research tool was a semi-structured interview with experts in the field of player valuation. In this research, the statistical population included all the experts and specialists in human resources and financial management issues in sports, and also volleyball experts. The sample size included a number of volleyball sports experts who expressed their ideas to determine the variables. A total of 60 variables were extracted, of which 40 are quantitative indicators and 20 are qualitative indicators. These indicators are not only effective in the selection of players, but can also determine the price and final value of the players

Developing an Operationalized Framework for Comparing Consumer-Directed Care for Older Adults: Evidence from Expert Survey and Cross-National Comparison

Consumer-directed care (CDC) programs for older people aim to optimize health outcomes by offering clients control and flexibility regarding service arrangements. However, policy design features may differ due to heterogenous sociostructural systems. By operationalizing a framework with three dimensions of CDC, i.e. control and direct services, variety of service options, and information and support, we analyzed how countries vary in their policy designs to achieve consumer direction. Using an expert survey (n = 20) and cross-national document analysis, we analyzed 12 CDC programs from seven selected countries: the United States, the United Kingdom, Germany, the Netherlands, China, Australia, and Spain. Among the three dimensions, CDC programs placed more emphasis on and displayed more homogenous performance of policy designs that achieve consumer direction in the dimension of control and direct services, while less emphasis was placed on and more heterogenous performance displayed in the dimensions of variety of service options and information and support. We offer a systematically operationalized framework to investigate CDC policy designs. Findings advance our understanding of CDC policy features from a cross-national perspective. Policymakers could incorporate these findings to empower older people in their respective societies

Evaluation of Elite Athletes Training Management Efficiency Based on Multiple Criteria Measure of Conditioning Using Fewer Data

Innovative solutions and techniques in the sports industry are commonly used and tested in real conditions. Elite athletes have to achieve their peak performance before the main competition of the year, which is the World Championship, and every fourth year before the Olympic Games, when the main competition of athletes takes place. The present study aims to analyze and evaluate the ability of elite kayakers to achieve the best form at the right times, with the Olympic Games taking the greatest importance. Target values for multiple measures of conditioning are compared to target values set by experts. A weighted least squares metric with weights varied by time period is developed as a measure of fulfillment of the athletes’ conditioning plans. The novelty of the paper is the idea of using linear combination of polynomials and trigonometric functions for approximating the target functions and application of the proposed methodology for the optimization and evaluation of athletic training.This article belongs to the Special Issue Mathematical Methods in Applied Science

A Modified TOPSIS Method Based on D

Multicriteria decision-making (MCDM) is an important branch of operations research which composes multiple-criteria to make decision. TOPSIS is an effective method in handling MCDM problem, while there still exist some shortcomings about it. Upon facing the MCDM problem, various types of uncertainty are inevitable such as incompleteness, fuzziness, and imprecision result from the powerlessness of human beings subjective judgment. However, the TOPSIS method cannot adequately deal with these types of uncertainties. In this paper, a D-TOPSIS method is proposed for MCDM problem based on a new effective and feasible representation of uncertain information, called D numbers. The D-TOPSIS method is an extension of the classical TOPSIS method. Within the proposed method, D numbers theory denotes the decision matrix given by experts considering the interrelation of multicriteria. An application about human resources selection, which essentially is a multicriteria decision-making problem, is conducted to demonstrate the effectiveness of the proposed D-TOPSIS method

Strategies for Improving Data Protection to Reduce Data Loss from Cyberattacks

Accidental and targeted data breaches threaten sustainable business practices and personal privacy, exposing all types of businesses to increased data loss and financial impacts. This single case study was conducted in a medium-sized enterprise located in Brevard County, Florida, to explore the successful data protection strategies employed by the information system and information technology business leaders. Actor-network theory was the conceptual framework for the study with a graphical syntax to model data protection strategies. Data were collected from semistructured interviews of 3 business leaders, archival documents, and field notes. Data were analyzed using thematic, analytic, and software analysis, and methodological triangulation. Three themes materialized from the data analyses: people--inferring security personnel, network engineers, system engineers, and qualified personnel to know how to monitor data; processes--inferring the activities required to protect data from data loss; and technology--inferring scientific knowledge used by people to protect data from data loss. The findings are indicative of successful application of data protection strategies and may be modeled to assess vulnerabilities from technical and nontechnical threats impacting risk and loss of sensitive data. The implications of this study for positive social change include the potential to alter attitudes toward data protection, creating a better environment for people to live and work; reduce recovery costs resulting from Internet crimes, improving social well-being; and enhance methods for the protection of sensitive, proprietary, and personally identifiable information, which advances the privacy rights for society