This occurred because in week 3 they lost to Montreal. Now Montreal might be the worst team in the league (although their fortunes will be on the up now they have Johnny Football! /s) but just because a team loses to them once, doesn’t mean they are necessarily worse than them. If you look at the CFL’s own power rankings they went from the 6th best team in week 3, to the 9th (and last) team for week 4 and up to 8th going in to week 6. TSN had them going from 7th ranked to 9th going in to week 4 and 8th going in to week 6.
These pundit underratings, or over compensation for a loss to the worst team, was also reflected in the bookmaker’s odds. From my modelling point of view this equated to massive differences between the betting odds and my Elo ratings for their next two games, in weeks 4 and 6 (no game in week 5), which is apparent in the graph below for the Saskatchewan Roughridgers edge. Their edge goes from a fairly low margin to jump up and then back down again.
It was these two large edges that created the environment for good betting spots. I had them 56% probability of beating Hamilton in week 4 and 47% chance of beating Hamilton in week 6. I managed to get a 2.2 to 1 win then a 4.4 to 1 win on what were roughly coin tosses. Thank you bookmakers.
The Hamilton trend line in the graph above shows that I also have the bookies consistently overrating Hamilton and thus creating negative edges at every game this year. This has not been by a particularly significant amount but all 3 of my bets on the CFL this year have been betting on teams to beat Hamilton. These have all been big, underdog winners with the third bet on Ottawa at nearly 2 to 1 when I had them as a slight favourite.
The third bet is that large Ottawa edge in week 7 on the graph. Now if you are interpreting that first, positive y-axis gridline as the threshold for when I place a bet, then I’m sorry to disappoint, but it’s not quite that simple.
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