The effect of football/soccer players performance on their market value - Research Paper Example

Those players who transfer with huge amounts are the ones noted mostly, unlike the low valued players, who mostly play for the small clubs. Among the most expensive players are playing in the English Premier League, La Liga Serie A and the German’s Bundesliga. Therefore, this project seeks to appraise the statistical facts that exist between player’s field performance and their market value. This project will compare the data collected from different players in the different soccer leagues.

Task and the methodology This project will evaluate the relation between the market value and performance of soccer players. It will depict a clear and precise picture of how a player’s performance determines his market value. The sample will consist of randomly selected players of all positions in a soccer field. These data will show a player’s progress of performance within a certain period of time, and the player’s current market value. Some other variables that directly determine a player’s performance may also be used to create a clear performance profile of the player.

Once the relevant variables have been tabulated, a correlation between these indicator variables and the aspect under consideration will be established. Correlation will be calculated, and evaluated whether it is a positive or a negative correlation. Once I calculate the correlations, I will make a supported justification as to whether performance affects a player’s market value. Data I acquired the data I used in my analysis from secondary sources in the internet. All these data are as recorded in the football web pages.

They include the English Premier League, Primera Division, Serie A and the Bundesliga. The data collected from these sources have not been altered, hence they are reliable for examining the relationship. The tables contain all the variables needed to evaluate the relationship between the two aspects in soccer. The variables considered can be presented in a simplified table as shown below. Variables Type Age Discrete Games Played Discrete Goals Discrete Assists Discrete Time Played Discrete STRIKERS Player Age Games played Time played (Minutes) Goals Scored Assists Market Value(?) 1 Wayne Rooney 26 14 1192 11 3 47,500,000 2 Chicharito 23 13 708 6 1 16,500,000 3 Federico Macheda 20 2 20 0 0 2,500,000 4 Theo Walcott 22 15 1130 2 5 14,000,000 5 Robbin Van Persie 28 15 1261 19 5 26,500,000 6 Alexander Mark 18 1 29 0 0 5,300,000 7 Castaignos 19 4 148 1 0 4,000,000 8 Diego Milito 32 9 567 3 1 15,000,000 9 Diego Forlan 32 5 355 1 1 7,500,000 10 Mario Gomez 26 15 1229 15 3 31,000,000 11 Petersen Nils 23 7 140 2 0 3,500,000 12 Ivica Olic 32 7 120 1 0 5,500,000 13 Lionel Messi 24 16 1380 17 9 88,000,000 14 Ronaldo 26 15 1293 17 7 79,000,000 15 David Villa 30 15 896 5 2 39,500,000 16 Jose Maria 24 6 136 1 0 6,200,000 17 Lautaro Acosta 23 5 269 1 0 875,000 18 Kone Mamadoe 19 6 398 0 0 175,000 19 Andres Iniesta 27 10 603 7 5 57,500,000 20 Craig Bellamy 32 9 317 1 1 3,500,000 DEFENDERS Player age Games Played Time Played (Minutes) Goals Scored Assists Market Value(?) 1 Sebastian Coates 21 1 234 0 0 2,200,000 2 Glen Johnson 27 8 680 1 0 13,500,000 3 Kolo Toure 30 4 119 0 0 13,000,000 4 Gerald Pique 24 9 1233 1 1 35,500,000 5 Nemanja Vidic 30 6 768 2 0 32,500,000 6 Ashley Cole 30 19 1260 0 3 22,000,000 7 Paulo Fereira 32 1 49 0 0 1,300,000 8 Dany Alves 28 15 1315 1 7 31,000,000 9 Fontas