Commercial & Player Revenue Comparison for Transfers

Inspiration

Front office knows that players like Zlatan have a large marketing and commercial increase to teams but at what cost, and how much of that generates revenue?

What it does

We wanted to create a tool that would go directly in an MLS front office to demonstrate the quantified benefits and trade offs of getting a popular veteran (ie Zlatan Ibrahimovic) and the contribution that player has to your team revenue (commercial) vs. going for an up and coming DP (ie. Ezequiel Barco) based on potential resale value and growth potential. This insight would lead to smarter, data-driven, transfer decisions based off the club’s desired objectives.

How I built it

We created a regression model that aims to quantify the commercial revenue generation that can be attributed to a specific player, while controlling for facts they cannot influence such as market size, stadium built date, previous year’s performance, median household income, gdp by metro, number of companies in market, and mls championship appearances. We used the average overall ratings by position and age to develop an estimated increase over time as a player ages, and applied those standardized increases to each player. This then allowed us to project his new market value at the new overall rating. We decided to do two calculations here: one if the player has reached his potential (thus his market perceptions have lowered) and one if the player has not reached his potential (thus the market believes he still has room to improve).