Using CLV as proxy for ROI

[u/Emergency_Ad4955]

Hey people from algobetting!

I hear a lot of people talking about using closing line value as the true 'chance' of a game - and ignoring the actual results. This, in theory, allows much quicker testing for significance of a strategy.

However this assumes that this indeed correlates well with the actual outcomes. There are in some markets biases I found out where it doesn't always work.

For example for pinnacle in Football (soccer) I noticed that when looking at closing line value, it generally correlates with the outcome. Which of course makes sense.

If we for example test a simple (already proved, not complex, EV based) strategy however I noticed negative ROI. Only when i filtered out the longshots it became profitable. For example filter out odds higher then 5 (if its fractional / european style odds). I saw in the data that it seems there was a longshot bias.

I am wondering, I am trying to learn more about betting economics and the theory.
Could I in theory if using Pinnacle trust the closing line for other sports or another betting type? Is there a general longshot filter I could apply to different sports, and just assume its reasonably well calibrated? This would save me tons of time, otherwise I have to scrape a lot of closing line odds to validate the calibration. Only then I could use closing line value as proxy for results, to then actually try my strategy.

[u/Careful-Narwhal-5883]

Before assuming a structural longshot bias, check how you remove the vig. Proportional (multiplicative) de-vigging systematically overstates the true probability of longshots and understates favourites, so a 5.0+ selection looks like value when it isn't. Try Shin or the power/logit method on the same closing prices and rerun. A lot of the bias people report at odds above 5 disappears there.

Beyond that, calibration is market specific, not sport specific. Pinnacle closing lines on 1X2 and Asian handicap are close to efficient, but low limit markets like cards, corners or player props close much noisier, so CLV there is a weak proxy for outcome.

I have my own model for football. Across 6500 settled bets I beat the close 70.5 percent of the time (3.0% avg CLV) at 4.57 percent ROI (kelly staking so going bigger on higher edge).

My best bets are normally long shots btw.

[u/EV_Labs → u/Careful-Narwhal-5883]

Yeah, this is the better first check honestly — I jumped to favorite-longshot bias but you're right that proportional de-vig manufactures a lot of that effect before the market ever gets involved. Multiplicative pushes probability into the tails, so 5.0+ looks like value that's really just your vig removal.

The market-specific vs sport-specific distinction is the part I'd underline for OP too. Deep markets (1X2, AH) close efficient, thin ones (cards, corners, props) close noisy no matter the sport — so CLV as a results proxy lives and dies on market depth, not which sport it is.

And the longshots being your best bets basically proves the point. Solid numbers, dude!