Introduction
When considering why I predicted the closing line wrong for Mexico/England and Spain/Belgium it dawned on me I *may* have had a flaw in my approach to football betting for the last 9 years. I’ve put a lot of work into developing my ratings with numerous adjustments, but it was the conversion of the ratings into match odds that I have been somewhat overlooking (which relates to the format of the rating).
I was using team ratings in terms of (adjusted) xG difference. If team A had average scorelines of 1.4-0.6 and team B had average scorelines of 2.0-1.2 I’d view both teams as equal strength given their shared goal supremacy of 0.8. I’d work out the goal line (total goals expected in the match) separately. I gravitated to ratings in terms of (adjusted) xG difference because it seemed convenient to work with. Schedule adjustments, game state adjustments, pricing up a match between two teams, it all worked well.
The problem is there may be a flaw as 2 teams posting similar xG differences may not always be of the same skill level. Team A scores 70% of the goals in their games while team B only scores 62.5% of them (Team A’s matches are much lower scoring). If, instead of expecting an average supremacy from team A of 0.8 goals per game we expect them to score (on average) 70% of the goals this is a dramatic switch-up of approach.
Consider pitting team A against team B. We’ll say they’re both from a league that has an average of 2.6 goals per game. From team A’s perspective, team B will add 0.6 goals to this game compared to team A’s average game. Using my original method, these 0.6 goals will be distributed equally to team A and team B. This means we rate both teams equally and treat the higher game total as separate.
However, now consider team ratings as the ratio of goals scored. Team A is rated better (0.7 vs. 0.625). This means when we match them up, team A will be the favourite. They’ll be even more favoured when they are awarded more than a fair share of the 0.6 goals added to the game as well.
So, is team A the better team in this scenario? I think we can say they are definitely *some* amount better. An average scoreline of 1.4-0.6 is worth almost 3 expected points more than an average scoreline of 2-1.2 over a 38-game season. Their defence is twice as good, but their attack is more than half as good. Their games are not so low scoring that they will suffer too many draws.
I need to put more effort into thinking about this. Is the expected scoreline for this game 1.3-1.3, is it 1.53-1.07 (using ratios ) or it is somewhere between the two? Do teams who score 70% of the goals in their low scoring games still score 70% of the goals in higher scoring games?
Today I’ll use ratios to preview the two semi-finals.
France vs. Spain
Figure 1 (‘Perf1’ ‘Perf2’ ‘Perf3’ in the top table should say Last 32, Last 16, Quarter-Final)
All performance and MIR (market inferred performance) figures are schedule adjusted.
For the 2nd table I only used the last 2 games for MIR and excluded the 3rd game for performance (motivation questions in that game for both teams).
The more we weight towards performance the further things swing towards Spain -Spain’s performance have bene consistently strong. The markets opened with France around 2.4 and they have now drifted out to 2.63. France are coming off a very strong performance vs. Morocco. My draw price is a bit off; I will work on that.
We’re quite close to kick off now as I write this so I’m not going to predict a move from now as between 50% and 75% MIR weight seems reasonable.
Closing line 2.62-3.325-3.175
Argentina vs. England
Figure 2 (‘Perf1’ ‘Perf2’ ‘Perf3’ in the top table should say Last 32, Last 16, Quarter-Final)
Ok I have Argentina as the favourite here across all MIR/Performance blends.
As I write at 6:18pm UK time on Tuesday the market is 2.81 – 3.025 – 3.175
I’m going to predict a closing line of 3.0-3.0-3.0! If I’m wrong, I’ll hopefully learn why.
Thanks for reading, subscribe using the white box on my home page to be notified of any posts.
Leave a Reply