Hello, Welcome to the third and final part of my replacing Nikita Parris series. If you haven’t caught the first 2 blogs go check out before this one as they take you through the various parts of the process. We identified our 3 best candidates to replace Nikita Parris: Francesca Kirby, Millie Farrow and Vivianne Miedema.
Above you can see a small sample of information for the 3 players. Despite lots of googling I couldn’t find any information on the length of Millie Farrows contract. However she signed for Reading in 2018 so its likely to go on for a few more years yet. Miedema looks like she could be the most expensive option to go for with a new long term contract recently signed and she is the youngest of the 3 and therefore has the largest upside.
Above you can see a summary of the adjusted expected goals per 90 with the 3 options highlighted. This is where there is a problem with Farrow. She is rated high for adjusted xG per 90 however the sample size is small. Therefore I need to be cautious with her results.
The three players average pitch touch locations are pretty similar to Parris’s, They are all pretty high up the pitch and fairly central.
When looking at the expected assists it highlights the difficulty in replacing Parris. There’s Farrow who has done excellently at this metric however as we have seen has a small sample size and these numbers would surely regress. Moving onto Miedema and Kirby this seems to be a weaker area for their games which could suggest with the players I have data for Parris’s goals could be replace but not her creativity.
The Fran Kirby FInal thirds pass map is good. She clearly completes a lot f her final 3rd passes. However a lot of these seem to be backwards or around the outside of the box. If you compare to Parris’s a lot of her final 3rd passes are aimed in the box. She actively tries to create chances of her team.
Farrow has 100% completion but the sample size is so small that no judgement can be made.
Miedema pass map is probably the most similar to Parris’s and therefore for being creative in the final third she is probably a good option.
Dribble percent they are all pretty similar with Farrow the best based on a small sample size. Therefore if either of the players are signed then they wont effect the team currently when it comes to dribbling.
There’s a snapshot of the 3 players selected wit some of their strengths and weaknesses. Overall I have enjoyed this task immensely. I have definitely found the data set with 160 odd column difficult to manage to access the data I required. Let me know your thoughts and whether you agree with my findings.