The Research of Key Indicators of Performance to Predict to Advance the Knock Out Stage in the International Football Tournament

Abstract

The aim of this research was to analyse football tournaments, UEFA Euro 2021 and Copa America 2021, to provide statistical measurement to predict which teams were likely to be qualified to the next round in the knockout stage. The research method used to collect six key variables statistics including total attempts, on target, possession, passes attempted, passing accuracy, and corners taken from 79 matches in UEFA Euro 2021 and Copa America 2021. The data were analysed by the grey relational analysis (GRA). The results were as follows: first, this study presented variables related to goals scored and offense correlated on goals scored. Second, this study proposed a GRA model that provides an efficient way to predict match outcomes. Third, the GRA model will perform better than the FIFA world ranking when more teams participated and the world ranking were tight.

Predicting Team Advancement in Major League Baseball Postseason Using Borda Count

“…In the data applied, the technical variables correspond to values of the teams, not to the individual values of the players. All the ten criteria (technical variables) were used [3][4] as criteria including earned run average (ERA), walks and hits per inning pitched (WHIP), batting average against (AVG), strkeouts per 9 IP (SO/9), walks per 9 IP (BB/9), runs batted in (RBI), batting average (HAVG), on-base percentage (OBP), slugging percentage (SLG), at bats per home run (AB/HR). Before using Borda Score, we used regression analysis in which Wins were the dependent variable, and ERA, WHIP, AVG, SO/9, BB/9, RBI, HAVG, OBP, SLG and AB/HR were independent variables.…”

“…According to the data presented in and Jia et al [3] in their utilization of extensive data and algorithms to predict game outcomes. For an extended period, predicting the results of baseball games has been a topic of great interest for many scholars and fans.…”

“…Research related to predicting sports event outcomes can be broadly categorized into two main types. One category focuses on predicting individual performance of professional sports teams [1], while the other category involves predicting team performance [2][3]. However, most studies in this field rely on extensive data for prediction.…”

“…For example, Bailey, Loeppky, and Swartz [1] utilized logistic regression analysis to predict the batting average of hitters in the Major League Baseball (MLB), using data from over 30 teams and more than 162 games per season (over 2,400 games), which generated over 30 batting indicators per game. On the other hand, Jia et al [3] However, many sporting events do not have as many matches or accumulate a large volume of game data, making it less convenient to analyze them using big data methods. For instance, the MLB postseason, which garners significant attention from baseball enthusiasts worldwide, lasts approximately one month and consists of 28 to 45 matches, which is significantly fewer compared to more then 2,000 matches played in a single regular season of MLB.…”

Evaluation of Goalkeepers’ Performance via Grey Relational Analysis Method: Example of Africa Cup of Nations

“…The GRA method was used to analyze the data. The steps taken within the scope of the analysis are as follows: (Tutak & Brodny, 2023;Chen et al, 2022;Rehman & Rehman, 2022;Özdemir & Kılıçarslan, 2021) •…”