MatchWiz

StackLab

Pick a game from tonight's slate, lock the legs you like, and the model fills the rest. Every price is a real one a book is posting right now.

Book
Target payout
Legs
Same-game parlay0 legs · MIN @ ORL
—
Lock a leg, or hit Fill the rest
  • Nothing picked yet
Leg pool175 legs at DraftKings · 350 rungs folded in
PlayerPropPriceOursBookEV
Desmond BaneGAssists 4.5++24539%—+35.8%
Desmond BaneGPts+Ast 24.5++17945%—+24.7%
Desmond BaneGPts+Reb 21.5+-11967%51%+23.3%
Desmond BaneGPts+Reb+Ast 25.5+-10964%51%+22.4%
Jaden McDanielsFAssists 2.5++12153%44%+16.7%
Jalen SuggsGAssists 3.5+-24282%—+16.4%
Desmond BaneGPts+Reb 19.5+-17873%—+14.6%
Jalen SuggsGReb+Ast 11.5++30028%—+11.8%
Desmond BaneGPts+Ast 19.5+-15267%—+11.1%
Desmond BaneGPts+Reb+Ast 19.5+-34385%—+9.9%
Desmond BaneGReb+Ast 9.5++23532%—+6.9%
Jalen SuggsGAssists 5.5++15941%—+6.7%
Wendell Carter Jr.CPts+Reb+Ast 14.5+-42186%—+6.1%
Desmond BaneGPoints 11.5+-44486%—+5.6%
Jalen SuggsGAssists 2.5+-57190%—+5.4%
Desmond BaneGAssists 2.5+-20470%—+4.6%
Jalen SuggsGPts+Reb+Ast 14.5+-61090%—+4.4%
Desmond BaneGPts+Reb 14.5+-53487%—+3.6%
Desmond BaneGPts+Ast 14.5+-46385%—+3.5%
Wendell Carter Jr.CPoints 14.5++23531%—+3.1%
Franz WagnerFRebounds 3.5+-44384%—+3.1%
LaMelo BallGPoints 9.5+-99094%—+3.0%
Jalen SuggsGPts+Ast 14.5+-25574%—+2.4%
Jalen SuggsGRebounds 2.5+-32478%—+2.0%
Jalen SuggsGThrees 1.5+-16863%59%+0.9%
Jalen SuggsGPts+Reb 9.5+-82090%—+0.7%
Franz WagnerFRebounds 4.5+-21168%—+0.5%
Wendell Carter Jr.CRebounds 4.5+-58186%—+0.5%
Jalen SuggsGThrees 2.5++16238%—+0.2%
Wendell Carter Jr.CPts+Reb 14.5+-29475%—+0.1%
Wendell Carter Jr.CPoints 7.5+-31376%—+0.0%
Desmond BaneGReb+Ast 4.5+-65086%—-0.6%
Paolo BancheroFPts+Ast 27.5+-11453%50%-0.6%
LaMelo BallGPoints 11.5+-58185%—-0.8%
LaMelo BallGThrees 1.5+-67086%—-1.3%
Paolo BancheroFPts+Reb+Ast 39.5++14640%—-1.6%
Wendell Carter Jr.CPoints 9.5+-16762%—-1.6%
LaMelo BallGPts+Reb 14.5+-78087%—-1.6%
Desmond BaneGPoints 9.5+-79087%—-1.7%
Desmond BaneGRebounds 2.5+-38778%—-2.3%
Anthony EdwardsGAssists 2.5+-24369%—-2.3%
Jalen SuggsGPoints 7.5+-53682%—-2.3%
Wendell Carter Jr.CPts+Reb 19.5++10248%—-2.3%
Jalen SuggsGPts+Ast 17.5+-12654%51%-2.4%
Wendell Carter Jr.CPoints 5.5+-67085%—-2.8%
Desmond BaneGRebounds 3.5+-16661%—-2.8%
Paolo BancheroFPts+Reb 34.5++16636%—-3.0%
Paolo BancheroFPts+Ast 24.5+-21266%—-3.0%
Jalen SuggsGThrees 0.5+-75085%—-3.3%
Jalen SuggsGReb+Ast 7.5+-19063%—-3.5%
Paolo BancheroFPts+Reb+Ast 29.5+-38376%—-3.6%
Paolo BancheroFPts+Reb+Ast 34.5+-15759%—-3.7%
Desmond BaneGRebounds 5.5++23529%—-3.8%
Paolo BancheroFPoints 17.5+-29572%—-3.9%
Jalen SuggsGPoints 9.5+-28371%—-4.5%
Rudy GobertCRebounds 11.5+-12653%52%-4.5%
LaMelo BallGAssists 4.5+-69083%—-4.6%
Jaden McDanielsFThrees 2.5++34621%—-4.8%
Jonathan KumingaFAssists 2.5++13840%—-4.8%
Paolo BancheroFAssists 5.5++10247%—-4.9%
Paolo BancheroFPoints 14.5+-65082%—-5.0%
LaMelo BallGThrees 3.5+-11851%—-5.3%
Rudy GobertCPoints 5.5+-47678%—-5.3%
Rudy GobertCPts+Reb 14.5+-63082%—-5.5%
Jaden McDanielsFPoints 9.5+-51279%—-6.0%
Jonathan KumingaFRebounds 3.5+-41576%—-6.2%
Paolo BancheroFPts+Ast 19.5+-65081%—-6.3%
Jaden McDanielsFReb+Ast 4.5+-52579%—-6.4%
LaMelo BallGReb+Ast 9.5+-39074%—-6.6%
LaMelo BallGPts+Ast 19.5+-46877%—-6.6%
Paolo BancheroFAssists 3.5+-41775%—-6.7%
Jaden McDanielsFPts+Reb+Ast 14.5+-69081%—-7.4%
Jaden McDanielsFPts+Ast 14.5+-25466%—-7.6%
Jaden McDanielsFPts+Ast 9.5+-92083%—-7.8%
Jaden McDanielsFPts+Reb 14.5+-44975%—-8.0%
Wendell Carter Jr.CPts+Reb+Ast 19.5+-14154%—-8.0%
LaMelo BallGReb+Ast 7.5+-100083%—-8.3%
Rudy GobertCPts+Reb+Ast 14.5+-96083%—-8.8%
Jalen SuggsGPts+Reb+Ast 19.5+-19660%—-8.9%
Jaden McDanielsFPoints 7.5+-93082%—-9.2%
Jalen SuggsGPoints 13.5+-10146%47%-9.3%
Rudy GobertCPoints 7.5+-20561%—-9.4%
Franz WagnerFPoints 17.5+-26866%—-9.5%
LaMelo BallGPts+Reb+Ast 24.5+-42073%—-9.5%
LaMelo BallGPts+Reb+Ast 19.5+-99082%—-9.7%
Paolo BancheroFPts+Reb 24.5+-39272%—-9.9%
Paolo BancheroFReb+Ast 9.5+-80080%—-10.0%
LaMelo BallGRebounds 3.5+-28967%—-10.3%
Rudy GobertCPts+Reb+Ast 22.5+-12650%—-10.3%
LaMelo BallGThrees 2.5+-25264%—-10.5%
LaMelo BallGAssists 5.5+-37271%—-10.5%
Paolo BancheroFRebounds 5.5+-67078%—-10.8%
Rudy GobertCRebounds 7.5+-72078%—-10.9%
Rudy GobertCPts+Reb 21.5+-10646%48%-11.3%
Wendell Carter Jr.CRebounds 6.5+-18157%—-11.3%
LaMelo BallGRebounds 2.5+-66077%—-11.4%
Rudy GobertCRebounds 9.5+-28265%—-11.7%
Jaden McDanielsFThrees 0.5+-34869%—-11.8%
Jaden McDanielsFRebounds 2.5+-73078%—-11.8%
LaMelo BallGPts+Reb 19.5+-28865%—-11.9%
Franz WagnerFReb+Ast 7.5+-47573%—-12.0%
Jalen SuggsGPts+Reb+Ast 24.5++13937%—-12.1%
Paolo BancheroFRebounds 6.5+-35468%—-12.5%
Jaden McDanielsFRebounds 3.5+-31466%—-12.6%
Jonathan KumingaFRebounds 4.5+-19658%—-12.7%
Paolo BancheroFReb+Ast 14.5++10044%—-12.9%
Jaden McDanielsFPts+Ast 17.5+-12548%51%-13.0%
Paolo BancheroFRebounds 7.5+-19858%—-13.2%
Rudy GobertCRebounds 8.5+-44171%—-13.3%
Franz WagnerFThrees 2.5++37618%—-13.5%
Rudy GobertCPts+Reb 19.5+-16954%—-13.5%
Paolo BancheroFAssists 4.5+-18856%—-13.5%
Jonathan KumingaFReb+Ast 4.5+-70076%—-13.6%
Paolo BancheroFThrees 0.5+-32366%—-13.7%
Franz WagnerFRebounds 5.5+-11245%—-14.0%
Franz WagnerFPts+Reb 19.5+-54973%—-14.0%
Desmond BaneGThrees 1.5+-22660%—-14.1%
Desmond BaneGThrees 2.5++12438%—-14.2%
Jaden McDanielsFReb+Ast 7.5+-11145%49%-14.6%
Anthony EdwardsGRebounds 2.5+-91077%—-14.6%
Anthony EdwardsGReb+Ast 7.5+-19556%—-14.7%
Rudy GobertCPts+Reb+Ast 19.5+-25261%—-15.0%
LaMelo BallGAssists 6.5+-21458%—-15.4%
Anthony EdwardsGAssists 3.5++10042%—-15.4%
Franz WagnerFPts+Reb+Ast 24.5+-51270%—-15.8%
Jaden McDanielsFPts+Reb+Ast 19.5+-24660%—-16.2%
LaMelo BallGRebounds 5.5++12537%—-16.3%
Paolo BancheroFReb+Ast 11.5+-32064%—-16.6%
Anthony EdwardsGReb+Ast 8.5+-11745%49%-16.8%
Paolo BancheroFRebounds 8.5+-12346%51%-16.8%
Jaden McDanielsFPoints 14.5+-14849%—-17.2%
Anthony EdwardsGRebounds 3.5+-34264%—-17.2%
Jalen SuggsGRebounds 5.5++27522%—-17.3%
Jalen SuggsGPts+Reb 14.5+-21156%—-17.6%
Rudy GobertCDouble double+14334%—-18.1%
Franz WagnerFThrees 0.5+-35664%—-18.5%
Franz WagnerFPts+Ast 19.5+-51368%—-18.5%
Anthony EdwardsGRebounds 5.5++11937%—-18.6%
Wendell Carter Jr.CRebounds 10.5++33519%—-18.7%
Jonathan KumingaFPoints 17.5++35318%—-19.5%
Jonathan KumingaFPoints 7.5+-48267%—-19.5%
Jaden McDanielsFRebounds 4.5+-16149%—-19.9%
Anthony EdwardsGRebounds 4.5+-16149%—-21.0%
Jonathan KumingaFRebounds 6.5++17329%—-21.1%
Franz WagnerFPts+Reb 24.5+-19752%—-21.2%
Paolo BancheroFThrees 1.5++12934%41%-21.9%
Anthony EdwardsGPoints 19.5+-80069%—-22.1%
Anthony EdwardsGThrees 2.5+-31959%—-22.5%
Anthony EdwardsGPts+Reb+Ast 34.5+-21353%—-22.8%
Franz WagnerFAssists 2.5+-77068%—-23.0%
Jonathan KumingaFReb+Ast 9.5++21524%—-23.0%
Jonathan KumingaFThrees 0.5+-26156%—-23.2%
LaMelo BallGAssists 7.5+-12642%52%-24.1%
LaMelo BallGPoints 17.5+-16747%—-24.2%
Anthony EdwardsGPts+Reb 24.5+-73067%—-24.2%
Franz WagnerFPoints 19.5+-17348%—-24.7%
Jaden McDanielsFPts+Reb 19.5+-15846%—-24.8%
Jonathan KumingaFPts+Ast 9.5+-49062%—-25.1%
LaMelo BallGReb+Ast 12.5+-13042%53%-25.1%
Anthony EdwardsGPts+Ast 33.5+-10638%48%-25.3%
LaMelo BallGReb+Ast 11.5+-19049%—-25.6%
Anthony EdwardsGPts+Ast 24.5+-56163%—-26.0%
Anthony EdwardsGPts+Reb+Ast 29.5+-51262%—-26.4%
Jonathan KumingaFPts+Reb+Ast 14.5+-45260%—-26.7%
Paolo BancheroFDouble double+12033%—-27.5%
Jaden McDanielsFRebounds 5.5++11234%—-28.5%
LaMelo BallGPts+Ast 24.5+-19947%—-28.7%
Jonathan KumingaFPts+Ast 14.5+-11638%49%-29.7%
LaMelo BallGPts+Reb+Ast 29.5+-19446%—-30.1%
Anthony EdwardsGPts+Ast 29.5+-21247%—-30.2%
Anthony EdwardsGPts+Reb 29.5+-27851%—-30.3%
Anthony EdwardsGThrees 3.5+-13640%55%-31.0%
Anthony EdwardsGPts+Reb 34.5+-12037%—-31.8%
Jonathan KumingaFPts+Reb+Ast 24.5++22620%—-34.8%
Jonathan KumingaFPts+Reb 17.5+-12636%50%-36.2%

One leg per player. Three rungs of the same man's ladder are the same bet three times — they win and lose together, and no book will take them in one slip. You get his best rung in each price band rather than every rung, for the same reason. Book is the de-vigged market price, or a dash where the market is quoted one way only and the hold can't be stripped out.

Why the number isn't a multiply

A multiply is wrong in basketball, and it's wrong in both directions at once. Which one you get depends on whether your legs are one player or two.

Stack one man's night and the legs ride together. We measured it on 79,638 real player-games across three seasons: his points and his assists both going over hits 28.7% more often than the multiply says, and his rebounds and made field goals 36.2% more often. Pair his points with his points-rebounds-assists and it's 92.4% — the same night counted twice. A multiply prices that slip as a much longer shot than it is.

Two teammates fight instead. One ball, about a hundred possessions, so a teammate's big night comes partly out of yours: two players both going over on points lands 4.7% less often than the product, and on made field goals 4.2% less. Here the multiply flatters the slip, which is the trap, because that's the stack that looks diversified.

Opponents barely move at all — within half a percent of the plain product on points and rebounds. The pace both teams play lifts both benches a little, and that's the whole of it.

So StackLab doesn't multiply. Every game here is simulated thousands of times off the players' own game logs, and each posted line carries a record of which runs it hit. The chance a whole slip lands is the share of runs where every leg hit at once.

What the EV number means

EV is our win probability times what the slip pays, minus one. Positive means our model makes the parlay worth more than it costs. Negative means the book is ahead of us, and that's the common answer — it should be. Books hold a margin on every leg, and a parlay multiplies it.

Which is why the leg-count strip matters. Inside a fixed payout band, each extra leg multiplies the same hold again, so EV falls as the count rises. The strip shows that shape on the pool in front of you.

Fill the rest won't pick a leg we can't stand behind. 7 of the 25 legs we can compare sit more than 10 points from the book's own number, and our pricer calls a gap that size a stale line or an injury we don't know about rather than an opportunity. The model is unbiased on average here and wide game to game, so those are the rows where it's likeliest to be the one that's wrong — and ranking by EV would otherwise reach for them first.

They're still on the board, and you can still lock one. That's your call to make with the number in front of you; what the model won't do is choose it for you and call the result an edge.

Every leg here is one a book is quoting

A leg only appears when a sportsbook is posting that exact line and we hold simulated runs behind it. The percentage beside a player is the same one his prop board shows — one model, one number, two pages.

The runs come from his own games. A player's line is priced off the shape of his last 40-plus box scores rather than a bell curve, because a counting stat isn't shaped like one, and the simulation draws whole box scores rather than one stat at a time. That's why his points and his rebounds move together by exactly as much as they really do.

We also publish how the model does against the market, and on NBA player props the market wins. Nothing here is sold as a pick. It's our number next to the book's, and a payout that's honest about what the legs do to each other.