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Learn / How we price a slip
18 MIN READ Run a slip

The method · updated for the 2026 season

How we price a slip

There is no secret. There are five steps, each of them boring, and the whole edge is in doing all five instead of three. This page shows every one of them on a real ticket, including the arithmetic, so you can check our work or go do it yourself.

Steps5
Books polled per market14
Sims per game50,000

The one-paragraph version. We take every price a book shows, remove the book's cut so the numbers add to 100%, build our own probability for the same event from a simulation of the whole game, compare the two, and then — the part almost nobody does — check whether your legs are secretly the same bet before we multiply them together. What comes out is one number: the cents on the dollar you're paying above or below fair.

Read this first

A slip we grade positive can lose. A slip we grade negative can win, and often will. Nothing on this page predicts a game. It prices one. If you want the version of this that promises winners, there are about four hundred accounts on X ready to sell it to you.


STEP 01Strip the vig

A betting line is not a probability. It's a probability plus the house's cut, and the cut is baked in so smoothly that most people never subtract it. Take a standard two-way prop:

Drake London 5+ receptions -130 → implied 56.52% Drake London under 5 rec +105 → implied 48.78% ───────────────────────────────────────────── total 105.30% ← the 5.30% is the book's

Those two outcomes cover everything that can happen, so honest probabilities have to sum to 100%. The extra 5.30 points is overround. Removing it is called devigging, and how you remove it matters more than people expect.

Three ways to do it, and why we don't use the easy one

The obvious approach is to scale both numbers down proportionally until they sum to 1. That's the multiplicative method, and it's what most free calculators use:

Multiplicative 56.52 / 105.30 = 53.68% Shin adjusts for insider money = 53.41% Power pk solved so probabilities sum to 1 = 53.22%

On a near-coinflip the three answers agree to within half a point and it doesn't matter. On a longshot they diverge badly, and that's where parlays live. Bettors systematically overpay for big prices — the favorite-longshot bias — so the book's cut isn't spread evenly across both sides. It's loaded onto the longshot.

Kyle Pitts anytime TD · +260 / -340 · the method changes the answer
MethodTrue probFair priceBook's edge
Multiplicative26.1%+2836.1%
Shin25.2%+2977.9%
Power24.4%+3109.6%

Three and a half points of probability sounds small. On a four-leg parlay, a three-point error on one leg moves the whole ticket's fair price by more than 200 cents. We use the power method on any leg priced longer than +150, multiplicative below it, and we show you which one we used.

Why we poll 14 books

One book's line is one book's opinion. The consensus of a sharp market — weighted toward the books that move first and take the biggest bets — is a much better starting probability than the number sitting in your app. Half of the "edges" you'll find in a slip aren't edges at all, they're your book being slow.


STEP 02Build a distribution, not a projection

Here's the mistake that sinks most homemade prop models. Someone projects Bijan Robinson for 58 rushing yards, sees a line of 60+, and concludes the over is a loser. That reasoning is wrong even when the projection is right.

"60+ rushing yards" is not a question about the average. It's a question about the tail: how often does the top half of this player's outcome distribution clear a number. Two backs projected for the same 58 yards can have wildly different answers.

Back A workhorse, 17 carries, low variance mean 58 · sd 22 → P(60+) = 46.4% Back B committee, 9 carries + occasional 40-yd screen mean 58 · sd 38 → P(60+) = 47.9% same projection, different tickets — and the gap widens fast as the line moves away from the mean

How the number actually gets built

We don't model the prop. We model the game and then read the prop off it. For each matchup we run 50,000 simulations, and each one plays out roughly like this:

  1. Possessions. Draw a plausible number of drives from the pace distribution of these two teams, adjusted for the projected score margin — trailing teams run more plays.
  2. Play mix. On each drive, sample run or pass from the offense's tendency, conditioned on down, distance, and current game state.
  3. Usage. Assign the touch to a player from their route-participation and carry-share distribution, not their season average — shares move with personnel.
  4. Outcome. Draw yards from that player's own yardage distribution against this defense's allowed distribution, then check for the goal-line, red-zone, and turnover branches.
  5. Tally. At the end of the sim, record everything: every player's yards, receptions, touchdowns, and the final score.

The payoff is that every prop, every total, and every side comes out of the same 50,000 games. So when we ask "how often did Drake London get 5 catches and the game went over 44.5," we don't have to estimate it. We just count the sims where both happened. That count is the entire reason the next step works.


STEP 03Join the legs

Parlay math taught to a beginner says multiply the probabilities. That is correct if — and only if — the legs are independent. Legs from the same game are never independent. Legs from the same drive are barely even separate events.

Naive (independent) — what a parlay calculator tells you 0.585 × 0.505 × 0.545 × 0.235 = 3.78% Counted from the sims — what actually happened sims where all four hit: 2,157 / 50,000 = 4.31% The gap is correlation. It is worth 53 basis points of ticket probability, or about 500 cents of fair price.

Notice which way it went. Correlation made this ticket more likely, not less, because three of the four legs want the same thing: Atlanta throwing the ball a lot in a game that stays competitive. That's good news for you and it's why same-game parlays exist at all. It is also exactly why books shade the price. The full treatment of this is its own page — Same bet twice — because it's where most of the money is won and lost.


STEP 04Price the ticket

Now it's arithmetic. Convert the offered American odds on each leg into decimal, multiply them for the payout multiple, and compare the payout to the probability we counted.

-115 → 1.8696 -130 → 1.7692 -110 → 1.9091 +260 → 3.6000 payout multiple = 1.8696 × 1.7692 × 1.9091 × 3.6000 = 22.734 (+2173) market implies = 1 / 22.734 = 4.399% we counted = 4.310% EV = 0.04310 × 22.734 = 0.9798 → −2.02% per dollar

Read that last line carefully, because it's the only number on the site that matters. It does not say the ticket loses. It says that if you played this exact ticket at this exact price a thousand times, you'd end up with about 98 cents for every dollar you put in. Two cents on the dollar is a fairly gentle beating by parlay standards — the median four-leg slip we examine holds 11.4%. But it's still the wrong side of zero, and it's fixable.


STEP 05Choose the cut

The intuitive move is to drop the leg with the worst standalone edge. That intuition is wrong often enough to matter, because a leg in a parlay isn't judged on its own probability. It's judged on its probability given that everything else on the ticket already hit.

The rule, in one line

A leg belongs on the ticket if  P(leg | all other legs hit) × its decimal price > 1.

Everything below is that one comparison, run four times.

Leave-one-out: what each leg is really contributing
LegSoloGiven the rest hitPriceMarginal
Bijan 60+ rush58.5%61.2%1.8696+14.4%KEEP
ATL/CAR over 44.554.5%57.8%1.9091+10.4%KEEP
Pitts anytime TD23.5%26.7%3.6000−3.9%TOLERATE
London 5+ rec50.5%52.9%1.7692−6.4%CUT

Look at what correlation did for Drake London. His standalone probability is a coin flip at 50.5%, but conditional on Atlanta going over the total and Kyle Pitts finding the end zone, he gets to 52.9% — the ticket's other legs have already told us this was a passing game. Correlation gave him 2.4 free points. He still isn't worth −130. That's the cut.

The cut ladder

Once you accept the rule, an obvious question follows: if cutting one bad leg helps, why not cut two? Usually it does help. We show you the whole ladder and let you pick where to stop, because a bettor who wants a lottery ticket on Sunday is making a legitimate choice and we're not going to pretend otherwise.

Same $20 · every version of this ticket
VersionPriceHitsPaysEV
All four legs+21734.31%$454.68−2.0%
Cut London+11858.15%$257.00+4.7%
Cut London & Pitts+25732.5%$71.40+16.0%
Bijan alone-11558.5%$37.39+9.4%

The two-leg version is the best bet on the board and it pays $71 instead of $455. We know which one you're going to play. We'd just rather you play it knowing what it costs, and the honest framing is that the difference between the four-leg and the three-leg is $1.34 of expected value on a $20 ticket — real, repeatable, and free to take.


STEP 06What we can't do

Every model page on the internet ends with a victory lap. Here's the other thing instead.

  • We're behind on news. Our board rebuilds every four minutes. A beat writer's tweet about a limited practice will move a market before we've re-simulated anything. On inactive-report Sundays, trust the market over us for the first fifteen minutes.
  • Thin markets break the devig. A Tuesday MACtion receiving prop offered at two books with a 14% overround has no reliable fair price. We flag those THIN and we'd rather you skipped them.
  • Our correlations are estimates. They come from simulation plus seven seasons of play-by-play. A pair we've seen a thousand times is solid. A pair involving a rookie tight end in a new scheme is a guess with error bars, and the error bars don't show up in a clean-looking number like +0.31.
  • We don't know your book. Limits, boosts, SGP restrictions and how badly you'll get squared away for winning are all outside the model.
  • Being right is not the same as winning. A +4.7% edge means that over a very long run you keep about five cents of every dollar. The distribution of outcomes around that is enormous. You can be correct all season and finish down.
Terms used on this page

Overround — how much more than 100% a market's implied probabilities sum to. Devig — removing it. Power method — a devig that raises each probability to a shared exponent, which takes more of the cut off the longshot. Marginal EV — what one leg adds or subtracts from a whole ticket. CLV — closing line value, whether your price beat the market's final one.

07 · Straight bets, spreads and totals

Everything above works on a single wager too, and most of the value we find lives there. A straight bet has no correlation problem — it has a price problem. The same three steps apply, minus the joining step: strip the vig, build a distribution, compare the fair number to what the book is charging you.

Moneyline −145 → implied 59.2% → de-vigged fair 56.8% → fair price −131
You are paying 1.4 points of edge, or about 2.2% hold on a two-way market
Breakeven at −145 is 59.2%. Our model says 56.8%. That bet loses 2.4 cents per dollar long run.

Spreads and totals get the same treatment, except the distribution matters more than the price. A half point at the key numbers — 3 and 7 in football, 2.5 in a hockey puck line, 0.5 in a soccer total — is worth far more than a half point anywhere else, because a huge share of games land exactly there. We price the half point from the actual margin distribution, not from a flat rule of thumb.

The single-bet rule we keep repeating: a straight bet at a bad number is worse than a parlay at a good one. Most people have this backwards because parlays feel reckless and singles feel responsible. Responsible is a number, not a bet type.

Player props and alternate lines

Props are two-way markets with three-way pricing behavior: books hold more on them because the limits are lower and the information is thinner. Median hold on a mainstream side or total sits near 4.4%. On a receiving-yards prop it is often 7–9%, and on an anytime touchdown it can pass 12%. We show the hold on every single leg you paste, even if you only paste one, because knowing you are paying 9% is the whole point.

Alternate lines — the 60+ rushing yards version of a 48.5 line — are just a different slice of the same distribution. If our distribution and the book's disagree about the shape of the tail, the alternate line is where that disagreement shows up as money.

2025 season · verified

Super Bowl LX: Seattle 29, New England 13 (SEA closed −4.5, won by 16). Stafford 4,707 yards / 46 TD and AP MVP. James Cook 1,621 rushing yards. Jaxon Smith-Njigba 1,793 receiving yards. Myles Garrett 23.0 sacks. Full graded plays live on the ledger.

08 · Reading a price honestly

Four numbers describe any wager, single or combined, and we always show all four:

Implied probability — what the posted price says has to happen.
Fair probability — the same market with the vig removed and the books weighted by how sharp they are.
Hold — the gap between those two, expressed as the book's cut.
Expected value — cents won or lost per dollar staked, assuming our number is right.

Expected value is the only one of those four that can be wrong in an interesting way, because it inherits every assumption in the distribution. That is why we publish the ledger: an EV number with no track record behind it is decoration.

A worked example, start to finish

Take a total posted at Over 44.5 (−110) / Under 44.5 (−110). Implied: 52.4% each, summing to 104.8%, so the market holds 4.6%. Remove the vig proportionally and each side is 50.0% fair. Our simulation of that game puts the over at 51.8%. Fair price on the over is therefore −107, and you are being asked for −110. That is a 1.4% edge before you account for the fact that we could simply be wrong by more than 1.8 points of probability — which, on a total, we frequently are. We would call that a pass, and we would say so in the output rather than dressing it up as a play.

Now take the same game's alternate total, Over 41.5 at −175. Implied 63.6%. Our distribution says 68.9%. Fair price −222. That is a 5.3-point edge on a market almost nobody shops, and it is the kind of thing that only turns up when you price the whole distribution instead of the headline number.