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Alteryx For Sport: Replacing The Irreplaceable (Part 3)

When a member of your team is on his way out, whether that’s being sold to another club, being out of contract or due to long-term injury, a replacement needs to be found. When this player is key member of your team it is important to replace the attributes that the player had brought to the club.

So how do you go about finding a player who can bring you these soon to be missing attributes?


Find Nearest Neighbors:

In part 3 of this 4-part vlog series we use the Find Nearest Neighbors tool in Alteryx to search for similar players based upon their Euclidean distance – a metric that we can use to asses the relationship, dependent upon our specified attributes, between the players in our dataset and our outgoing player and find the most similar players.

Take a look at parts 1 & 2  in this series first:

Replacing The Irreplaceable (Part 1): Principal Component Analysis

Replacing The Irreplaceable (Part 2): K-Mean Clustering


Alteryx For Sport: Find Nearest Neighbors


Useful Links

Introduction To How K-Nearest Neighbors: Simplified

How K-Nearest Neighbors Works

Measures Of Distance Between Samples: Euclidean

Brian Prestidge

Manchester, UK

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