Man United v Man City detailed modelling preview

Introduction Even early in the season, Saturday’s Manchester derby appears one of those matches that will have a significant bearing on the Premier League title. Added to this it’s the first meeting of the teams’ two new managerial behemoths – so it seems appropriate to give this game added scrutiny from a modelling point of view….

Bad Numbers

Simply placing the word “bad” before a dreary noun seemingly endows an intimidating edge, perfect for a Hollywood movie title; Santa, neighbours, teachers, moms, and even grandpa all get the formulaic comedy treatment. It’s Bad meaning bad-ass in a way that gets past the censor. Three games into the season, if only there was a…

La Liga 2016/17 Projection

La Liga 2016/17 projection, modelled solely using adjusted goal ratings (i.e. only uses retrospective data) Expected points

2016/17 Premier League Projection – Value in Spurs

After reviewing the impact of close season activity for each Premier League team, I’m now in a position to compile my first projection for the 2016/17 season. Unlike last year I have made some adjustment for each club’s player turnover. I’ve also made an allowance for the impact of teams’ participation in European Competition compared…

Championship 2016/17 Projection

The Championship starts tomorrow. It should be a fascinating season, with two erstwhile Premier League giants and Norwich joining from the top division, first-timers Burton, and clashes between former European Champions and former Champions League winning managers. I’ve run the numbers through my projection model (using my adjusted goals rating system) and it’s produced the following…

Risk and Reward – managing your betting pot

So you’ve identified a value betting opportunity – how much do you wager? The answer will probably make or break your chances of long-term success. Even if you consistently spot genuine value, the capricious nature of chance dictates that undisciplined staking is the road to ruin. Yet, whilst there are no guarantees in the fickle…

Euro 2016 modelling review

So as the dust (and moths) settle on Euro 2016, I’m able to review the full performance of my model. Before the tournament I created a model that rated teams using the strength of their underlying players, which in turn were evaluated using the adjusted goals rating of their club teams (explained here). Tournament and individual…

Euro 2016 – Third round of group matches, assessing the model

Just 22 goals were scored in the final round of group matches, averaging 1.8 per game. Group F provided the only incentive fuelled high scoring denouement. Perhaps the 24 team structure generated more caution than usual for the final group matches, as this is historically the highest scoring stage of a tournament. As a result my model overestimated the number of goals…

Euro 2016 – Second round of group matches, model assessment

As expected the scoring rate has increased in the second round of group matches, to 2.1 from 1.8 per game in the first round of matches. This reflects the need of some teams to eschew their initial caution. Even so, scoring rate is still historically low, in previous tournaments the average rate for the second round has been at…

Euro 2016 – first round of group matches, model assessment

As expected the first round of group matches has been low scoring, with an average of  1.83 goals per game, this is even lower than the historical average 2.10. Strangely though we haven’t seen a 0-0 draw, with match results clustered around a few outcomes: 1-0, 1-1, 2-0 and 2-1. My model expected a total of 25.6 goals…

Euro 2016 – full projection

After creating attack and defence ratings for the 24 Euro 2016 teams, based on their underlying squad strength (as described here), I can run simulations to look at the likelihood of different tournament outcomes, including the winner. My projection simulates the score of each match for 5000 different possible tournament outcomes – including potential extra time…