Hello everyone! Not sure if this is the right topic, if not please redirect me.
I'm Portuguese and this is my first post on your forum. I just finished my Master Degree in Big Data Applied to Football and I selected Wolverhampton (a club that I have been following closely for the last seasons for obvious reasons) to serve as subject for my end of Master Project, and would like to share the results with you.
I, and a colleague of mine, developed a proposal for the Summer Transfer Window for Wolves, resorting to Wyscout Data, Python and Machine Learning Techniques.
To put it simply, we defined from over 60+ metrics what would the most valuable be for each position in the Wolves model of play (Center Back, Wing Back, Midfielder, Winger and Striker), and via a machine learning model created with python we clustered the results and ranked them subsequently. In the end we used a pinch of human judgement in order to remove from the equation players that were either realistically unnatainable for Wolves and players that no longer are available on the market (Kolo Muani for instance, which would have made it as a top 1 pick for the Striker position).
Take the Market Value figures with a pinch of salt as this is Transfermarkt data and not fiable or realistic in some cases.
I will not attach the full work but just the conclusions we took out of it. Hope you enjoy the work and effort we put into this, and maybe we'll see if any of these players will make it to Wolves during this transfer window (Nathan Collins ranked 51st on our model for center backs, for instance). I really wish Lage can succeed and have the best season yet for Wolves this year.
Cheers!
(Just in case you can't see the PDF I will attach the content with images. They are resized in order to comply with the limits of the forum, and thus not as clear as the PDF)
I'm Portuguese and this is my first post on your forum. I just finished my Master Degree in Big Data Applied to Football and I selected Wolverhampton (a club that I have been following closely for the last seasons for obvious reasons) to serve as subject for my end of Master Project, and would like to share the results with you.
I, and a colleague of mine, developed a proposal for the Summer Transfer Window for Wolves, resorting to Wyscout Data, Python and Machine Learning Techniques.
To put it simply, we defined from over 60+ metrics what would the most valuable be for each position in the Wolves model of play (Center Back, Wing Back, Midfielder, Winger and Striker), and via a machine learning model created with python we clustered the results and ranked them subsequently. In the end we used a pinch of human judgement in order to remove from the equation players that were either realistically unnatainable for Wolves and players that no longer are available on the market (Kolo Muani for instance, which would have made it as a top 1 pick for the Striker position).
Take the Market Value figures with a pinch of salt as this is Transfermarkt data and not fiable or realistic in some cases.
I will not attach the full work but just the conclusions we took out of it. Hope you enjoy the work and effort we put into this, and maybe we'll see if any of these players will make it to Wolves during this transfer window (Nathan Collins ranked 51st on our model for center backs, for instance). I really wish Lage can succeed and have the best season yet for Wolves this year.
Cheers!
(Just in case you can't see the PDF I will attach the content with images. They are resized in order to comply with the limits of the forum, and thus not as clear as the PDF)
)
