Scrapping data from the transferMarket website about Summer Football 2022 markert transfer
Data scraped from Market Transfer website in below images show the data that has scraped for each player.
for example Phili Foden mancity player
Frist webpage has his name, age, market value and other.
Second webpage has some insights about progress with team.
Third webpage has some insights about progress with National team.
Data contains 28401 players each one has 19 feature represents below.
Feature Name
Type
Description
age
Numerical
Player age at this season
position
Categorical
player position could be goolkeeper
, defence
, midfield
or attack
country
Categorical
Player country
apperance
Numerical
No. Played matches
goals
Numerical
No. Scored goals
assists
Numerical
No. Assists
yellow_card
Numerical
No. Yellow card
2nd_ycard
Numerical
No. 2nd yellow card
red_card
Numerical
No. Red card
min
Numerical
No. Played minutes
National_Team
Binary
Refer to has play with national team before or not 1
play and 0
doesn't
apperance_NT
Numerical
No. Played matches with national team
goals_NT
Numerical
No. Scored goals with national team
assists_NT
Numerical
No. Assists with national team
yellow_card_NT
Numerical
No. Yellow card with national team
2nd_ycard_NT
Numerical
No. 2nd yellow card with national team
red_card_NT
Numerical
No. Red card with national team
min_NT
Numerical
No. Played minutes with national team
cost
Numerical
Transfer cost
Regex used to extract data from the website using some libraries:
selenium
beautifulsoup
requests
Machine learning algorithms
Model Name
Train accuracy %
Test accuracy %
Simple Linear Regression
75.07
71.97
XGBoost Algorithm
99.15
98.99
Model Name
Train MSE
Test MSE
Neural Network
2.6162e-05
2.0937e-05
Graph show losses during training and validation