MatchWiz

StackLab

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

Book
Target payout
Legs
Cross-game parlay0 legs
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Lock a leg, or hit Fill the rest
  • Nothing picked yet
Leg pool109 legs at Fanatics · best 170 across tonight's slate · 895 not simulated
PlayerPropPriceOursBookEV
Saddiq BeyGPoints 17.5++37554%—+156.3%
Bennedict MathurinGRebounds 4.5++29057%—+121.0%
Saddiq BeyGRebounds 5.5++37546%—+118.7%
Tre JonesGPoints 14.5++37544%—+109.6%
Bennedict MathurinGPoints 17.5++35042%—+87.5%
Kelly Oubre Jr.GPoints 16.5++37539%—+87.1%
Pelle LarssonGPoints 13.5++35041%—+84.9%
Deni AvdijaFAssists 6.5++27047%—+75.5%
Tari EasonFRebounds 7.5++35038%—+69.6%
Tim Hardaway Jr.GPoints 14.5++37534%—+61.8%
Josh GiddeyGRebounds 9.5++29041%—+58.7%
Neemias QuetaCPoints 12.5++37533%—+56.5%
Naji MarshallFPoints 19.5++40031%—+53.8%
Toumani CamaraFPoints 15.5++29039%—+52.6%
Payton PritchardGPoints 22.5++37532%—+51.1%
De'Anthony MeltonGPoints 15.5++35033%—+50.0%
Deni AvdijaFPoints 25.5++19051%—+48.7%
Alex SarrCPoints 18.5++32035%—+48.2%
Andre DrummondCRebounds 9.5++30037%—+46.8%
Andrew NembhardGPoints 19.5++27039%—+45.6%
Amen ThompsonGAssists 5.5++21047%—+44.4%
Payton PritchardGAssists 5.5++22544%—+44.0%
Scottie BarnesFRebounds 9.5++32034%—+43.0%
Josh GiddeyGPoints 19.5++32034%—+42.4%
Bennedict MathurinGRebounds 2.5+-15085%—+41.7%
De'Andre HunterFPoints 15.5++27038%—+40.6%
Onyeka OkongwuFPoints 11.5++10069%47%+38.1%
Tari EasonFPoints 13.5++35030%—+36.9%
Kyle KuzmaFPoints 14.5++21043%—+33.5%
Mikal BridgesGAssists 3.5++17548%—+32.3%
Trey Murphy IIIFRebounds 7.5++32031%—+32.0%
Scottie BarnesFDouble double+26036%—+30.2%
Kyshawn GeorgeFPoints 13.5++11560%—+28.2%
GG JacksonFPoints 16.5++32031%—+28.1%
Alex SarrCRebounds 8.5++22539%—+27.5%
Jabari Smith Jr.FRebounds 7.5++21041%—+26.2%
Stephon CastleGAssists 7.5++21041%—+25.9%
Neemias QuetaCPoints 6.5+-19082%—+25.7%
Luka DoncicGAssists 9.5++27034%—+25.1%
De'Aaron FoxGPoints 19.5++29032%—+24.8%
Grayson AllenGPoints 12.5+-19081%—+24.4%
Jerami GrantFPoints 15.5+-10564%—+24.2%
Desmond BaneGPoints 21.5++19043%—+23.4%
Kevin DurantFAssists 5.5++27033%—+23.3%
Amen ThompsonGAssists 3.5+-17578%—+23.2%
Dyson DanielsGAssists 7.5++34028%—+22.8%
CJ McCollumGPoints 21.5++27033%—+21.9%
Donovan ClinganCRebounds 11.5++11556%—+21.1%
Kawhi LeonardFRebounds 7.5++23037%—+20.8%
Deni AvdijaFRebounds 8.5++26033%—+20.0%
Kawhi LeonardFPoints 21.5+-17576%—+19.5%
Bennedict MathurinGRebounds 1.5+-42597%—+19.4%
Austin ReavesGAssists 6.5++22537%—+19.2%
Max ChristieGPoints 8.5+-22583%—+19.2%
Kawhi LeonardFPoints 22.5+-14069%—+18.3%
Kawhi LeonardFPoints 18.5+-37593%—+17.7%
Tre JonesGPoints 7.5+-22581%—+16.8%
CJ McCollumGAssists 3.5++13051%—+16.4%
Stephen CurryGPoints 26.5++11554%—+16.1%
Neemias QuetaCPoints 5.5+-30087%—+16.1%
Bobby PortisFPoints 9.5+-17573%—+15.1%
Deni AvdijaFPoints 19.5+-17573%—+14.8%
Jabari Smith Jr.FPoints 10.5+-30086%—+14.7%
Tre JonesGPoints 5.5+-55097%—+14.7%
Deni AvdijaFPoints 17.5+-30086%—+14.5%
Grayson AllenGPoints 10.5+-35089%—+14.3%
Desmond BaneGAssists 4.5++19039%—+14.1%
Jalen SuggsGAssists 3.5+-27582%—+12.3%
Kyshawn GeorgeFPoints 11.5+-15067%—+12.2%
Desmond BaneGPoints 16.5+-15067%—+11.7%
Max ChristieGPoints 7.5+-30084%—+11.7%
Andrew WigginsFPoints 9.5+-40089%—+11.3%
Donovan ClinganCRebounds 9.5+-19072%—+10.5%
Kawhi LeonardFPoints 16.5+-65096%—+10.5%
Alex SarrCPoints 10.5+-21075%—+10.0%
Toumani CamaraFPoints 9.5+-16568%—+10.0%
Jerami GrantFPoints 13.5+-17570%—+9.5%
Lauri MarkkanenFPoints 14.5+-70096%—+9.2%
Cedric CowardFPoints 11.5+-14064%—+9.1%
Donovan ClinganCRebounds 8.5+-32583%—+8.2%
Grayson AllenGPoints 8.5+-70094%—+7.9%
Tre JonesGPoints 4.5+-90097%—+7.8%
Luka DoncicGAssists 6.5+-19071%—+7.7%
Jerami GrantFPoints 7.5+-45088%—+7.4%
Kris DunnGPoints 6.5+-14564%—+7.3%
Cedric CowardFPoints 10.5+-19070%—+6.4%
GG JacksonFPoints 9.5+-19069%—+6.1%
Stephen CurryGAssists 4.5++13046%—+5.8%
Deni AvdijaFThrees 1.5+-11556%50%+5.5%
Andrew WigginsFPoints 7.5+-90095%—+5.0%
Scottie BarnesFPoints 23.5++24031%—+4.9%
Payton PritchardGRebounds 1.5+-80093%—+4.8%
Onyeka OkongwuFPoints 5.5+-90094%—+4.5%
Derrick Jones Jr.FPoints 10.5+-11556%50%+3.9%
Bennedict MathurinGPoints 6.5+-65090%—+3.8%
Kris DunnGPoints 5.5+-22572%—+3.7%
P.J. WashingtonFRebounds 3.5+-65090%—+3.6%
Jalen SuggsGAssists 5.5++15041%—+3.0%
Stephen CurryGPoints 23.5+-16564%—+2.8%
Jaylen WellsFPoints 16.5++24030%—+2.5%
Deni AvdijaFRebounds 3.5+-80091%—+2.4%
Cooper FlaggFRebounds 3.5+-90092%—+2.0%
Cedric CowardFPoints 6.5+-100092%—+1.7%
Toumani CamaraFPoints 5.5+-80090%—+1.5%
RJ BarrettFPoints 12.5+-80090%—+0.9%
Jerami GrantFPoints 6.5+-70088%—+0.4%
Luka DoncicGAssists 5.5+-37578%—-1.3%
Luka DoncicGRebounds 4.5+-70085%—-2.5%
Luka DoncicGRebounds 8.5++15038%—-4.4%

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 this one is a multiply

Legs from different games don't move together. What a guard scores in Boston has nothing to do with the rebounds a centre pulls down in Phoenix, so there's no correlation to measure and the price is the plain product of the legs.

That's the difference between the two tiles. An SGP is simulated — one game, over and over, and the chance a slip lands is the share of runs where every leg hit at once. An SGPx is arithmetic.

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. 9 of the 13 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.