Thursday, 10 March 2016

A Bayesian network to determine optimal strategy for Spurs' success


As a committed Spurs fan I have spent the last few months salivating at the club's sudden and unexpected rise and the prospect of them winning their first league title since 1961. By mid-February they were clear favourites to win the Premier League title. However, in my view, the challenge was compromised by the team becoming overstretched by playing too many matches in a short space of time. In particular, I felt that their involvement in the Europa League was an unnecessary distraction and burden. When I expressed these views on a Spurs online forum (backed up with some data showing consistent under-performance during periods when they were involved in the Europa League) I got heavily criticised by other fans who said it was important to try to win every competition.

Having simultaneously been involved in research discussions about the use of decisions in Bayesian networks, I decided to build a small model in AgenaRisk to resolve the dilemma once and for all. I have written up the results of the analysis here. The model can be downloaded from here.

In summary, there were 4 strategic options available to Spurs' manager Mauricio Pochettino at the time I started to do the analysis:
  1. Focus on Premier League 
  2. Focus on Premier League and FA Cup 
  3. Focus on Premier League and Europa League 
  4. Focus on all three competitions  
My BN model shows that the optimal decision (based on my subjective utility values of the different outcomes) was to go for 1 with 2 a close second. Unfortunately  (I believe) Pochettino opted for 3 which, as the model shows, suggests his personal utility value for winning the Europa League was actually higher than winning the Premier League.

Downloads:

See also: The problem with predicting football results - you cannot rely on the data
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