Our published closing-line value was measured against the raw closing price with the bookmaker's ~6% margin still inside it; measured honestly, against the vig-stripped Betfair exchange close, our bets have beaten the fair price only about 22-33% of the time with an average CLV of roughly -1 to -2 percentage points, so the market is currently beating us, and we would rather show you that number than the flattering one.
We were publishing a stat we were proud of: our picks beat the closing line about 72% of the time. Then someone on r/algobetting posted their own model's CLV, negative, on their front page, and explained they measure against the devigged closing consensus. We checked whether ours would survive the same treatment.
It didn't.
Closing-line value asks one question: did you get a better price than the market's final price? It's the sharpest known predictor of long-term profit, because it doesn't wait for results. The catch is the phrase "the market's final price". We were using the raw closing odds, and raw odds carry the bookmaker's margin, the vig. On our sample the closing books summed to about 106% implied probability. That extra 6% means every quoted price is shortened from fair, on both sides. Beat a shortened price and you've proven very little. You might still be taking worse than fair.
July 29, we backed Jessica Lu at 3.95. The book closed her at 3.75. Old method: 3.95 beats 3.75, chalk up a CLV win, +5%.
Now do it honestly. The closing pair was Lu 3.75, Hontama 1.25. As probabilities that's 26.7% + 80.0% = 106.7%. Scale both back so they sum to 100% and Lu's fair closing probability is 25.0%, which is fair odds of 4.00.
We took 3.95. Fair was 4.00. We got a worse price than the market's true final opinion, and the old method called it a win. About one in five of our "beat the close" bets turns out to be exactly this: negative CLV wearing a positive costume.
| Benchmark | Beat close | Avg CLV |
|---|---|---|
| Raw close, vig included (old method) | ~40-56% | roughly flat |
| Devigged fair close (honest) | ~22-33% | -1 to -2 pp |
The ranges cover our two samples: the full settled history (670 moneyline bets, mostly graded against devigged book closes) and the smaller recent subset where we recorded the actual exchange price we bet at. The honest read of both is the same. The market is beating us. A neutral bettor taking random prices would land near 50% against the fair close. We're below that.
Because the flattering version was still live on this site, and leaving it up once you know better is how tipster marketing works. We'd rather be the other thing. The efficient-market literature says this is the expected result anyway: Pinnacle's tennis closing prices are nearly perfectly calibrated, and nobody's simple strategy beats them over twelve years of data. Starting negative against the sharpest benchmark isn't shameful. Pretending otherwise is.
So this is the new baseline, in public. Every pick is now graded against the devigged Betfair exchange close, captured both sides at match start, and the board shows that number instead of the old one. When it crosses positive, you'll have watched it happen live rather than taken our word for it. If it doesn't cross, you'll see that too.
We use the standard proportional (multiplicative) devig: scale both sides' implied probabilities to sum to 100%. It's the method sharp bettors use to price fair lines (see EdgeSlip's explainer or SharkBetting on the three devig methods). Its known weakness, noted in both write-ups: it assumes the vig splits evenly between favourite and underdog, while real markets load more of it onto the underdog (OddsShopper covers this, and so does our own favorite-longshot study). Since we bet a lot of underdogs, this makes our negative number slightly too harsh on us, maybe half a point. It does not turn it positive. Second caveat: exchange closes are only captured going forward from July 30, so most of the history is graded against devigged book closes, the best benchmark available for those bets. Third: these are hundreds of bets, not thousands. The direction is clear; the second decimal is not.
Method: settled moneyline bets from the live forward track, entry price vs the closing pair devigged by proportional normalisation (both sides' implied probabilities scaled to sum to 100%). Exchange closes (Betfair, both sides, captured at match start) preferred from 2026-07-30 onward; devigged book closes as the historical fallback; bets with no comparable close excluded, never estimated. Live record and per-bet fair CLV at /bot.
Not yet, on the honest metric. Against the devigged Betfair exchange close our closing-line value is currently negative (roughly 22-33% beat-close depending on the sample). We publish it anyway, and every pick from July 30 onward is graded against this same fair benchmark.
The bookmaker's margin removed from the closing odds, so your bet is compared to the true fair price instead of an inflated one. Convert both sides' closing odds to probabilities, they sum to more than 100%, and the excess is the vig. Scale both back to 100% and you have the fair line. Beating that line is the only version of CLV that predicts real profit.
It compared our price to the raw closing odds with roughly 6% of margin still in them. A shortened price is an easy bar: you can 'beat the close' while still taking worse than the fair price. Devigging removed the illusion, and about one bet in five flipped from beat to miss.
See today's picks — published before the match, graded in public →