Prediction

Reminder 1: during the World Cup, I suggested two models to explain scores of national men’s football team games based on matches from August 2012 to December 2013. The first model was based on 13 variables: population, GDP per capita, climate, experience, percentage of players, player quality, foreign managers, technology transfer through managers, home advantage, prize, prize difference in favour of the favourite, prize difference in favour of the underdog, no prize. The second model was based on home advantage and dummies for every team (1 when a team plays at home, -1 when a team plays away).

Reminder 2: so as to propose predictions for the UEFA Euro 2016 qualifiers, Wladimir Andreff and I applied the same models in taking into account only European national teams. For the first model, we also compared real scores and those provided by the model. Thus, we calculated the average gap per game for every team that we included then so as to correct the model.

Here are our predictions for Match Day 3 (12, 13 and 14 October):

¹Given that Gibraltar did not play in the past, we arbitrarily chose to allocate San Marino’s coefficient to Gibraltar.

About Dr Nicolas Scelles

Nicolas Scelles is a Lecturer at the School of Sport, Stirling University, Scotland. He holds a PhD in sports economics from the University of Caen Basse-Normandie, France. He has articles in international journals including Applied Economics, Economics Bulletin, International Journal of Sport Finance and International Journal of Sport Management and Marketing.