📡 SCORES
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⚡ Nex Board

Mixed ranking engine — sides + props scored, ranked, and graded. Top 4 daily picks.

Nex Board Record
1D 7D 14D 30D |
← Jul 5 – Jul 11 →
Wins
13
Losses
11
Win %
54.2%
Pending
0
Thu 10/22 Wed 10/21 Tue 10/20 Mon 10/19 Sun 10/18 Sat 10/17 Fri 10/16 Thu 10/15 Wed 10/14 Tue 10/13 Mon 10/12 Sun 10/11 Sat 10/10 Fri 10/9
Sport: All NBA MLB NFL WNBA
Stat:
🤖 AI Plays
1
NY @ MIN WNBA
Points 15.5 OVER
78.4 B+
  • Projected edge vs line
  • Heavy minutes projection
  • Stable player role
Raw
78
Clean
29
Fit
4
2
PHX @ LV WNBA
Points 20.5 OVER
73.3 B
  • Projected edge vs line
  • Heavy minutes projection
  • Stable player role
Raw
77
Clean
23.7
Fit
4
3
PHX @ LV WNBA
Points 17.5 OVER
69.1 B
  • Projected edge vs line
  • Heavy minutes projection
  • Stable player role
Raw
62
Clean
27.9
Fit
4
4
PHX @ LV WNBA
Rebounds 6.5 OVER
68.4 B-
  • Heavy minutes projection
  • Stable player role
Raw
60
Clean
22.7
Fit
5

📋 Full Board (1465 picks · Page 54/59)

#ActionPickMatchupTypeLine ScoreTierCleanFit Result
1326 Jake McCarthy COL COL @ SF Home Runs 0.5 3.2 D 9.2 -5 Pending
1327 Jakob Marsee MIA CLE @ MIA Home Runs 0.5 3.2 D 9.2 -5 Pending
1328 Jared Triolo PIT MIL @ PIT Home Runs 0.5 3.2 D 9.2 -5 Pending
1329 Jared Triolo PIT MIL @ PIT Runs Batted In 0.5 3.2 D 9.2 -5 Pending
1330 Javier Sanoja MIA CLE @ MIA Home Runs 0.5 3.2 D 9.2 -5 Pending
1331 Javier Sanoja MIA CLE @ MIA Runs Batted In 0.5 3.2 D 9.2 -5 Pending
1332 Jeremy Pena HOU HOU @ TEX Home Runs 0.5 3.2 D 9.2 -5 Pending
1333 JJ Wetherholt STL ATL @ STL Home Runs 0.5 3.2 D 9.2 -5 Pending
1334 JJ Wetherholt STL ATL @ STL Runs Batted In 0.5 3.2 D 9.2 -5 Pending
1335 Jonathan Aranda TB SEA @ TB Home Runs 0.5 3.2 D 9.2 -5 Pending
1336 Jorge Mateo ATL ATL @ STL Home Runs 0.5 3.2 D 9.2 -5 Pending
1337 Jorge Mateo ATL ATL @ STL Runs 0.5 3.2 D 9.2 -5 Pending
1338 Jorge Mateo ATL ATL @ STL Runs Batted In 0.5 3.2 D 9.2 -5 Pending
1339 Jorge Polanco NYM BOS @ NYM Home Runs 0.5 3.2 D 9.2 -5 Pending
1340 Jorge Soler LAA LAA @ MIN Home Runs 0.5 3.2 D 9.2 -5 Pending
1341 Josh Bell MIN LAA @ MIN Home Runs 0.5 3.2 D 9.2 -5 Pending
1342 Josh Jung TEX HOU @ TEX Home Runs 0.5 3.2 D 9.2 -5 Pending
1343 Josh Lowe LAA LAA @ MIN Home Runs 0.5 3.2 D 9.2 -5 Pending
1344 Josh Naylor SEA SEA @ TB Home Runs 0.5 3.2 D 9.2 -5 Pending
1345 Jung Hoo Lee SF COL @ SF Home Runs 0.5 3.2 D 9.2 -5 Pending
1346 Jung Hoo Lee SF COL @ SF Runs Batted In 0.5 3.2 D 9.2 -5 Pending
1347 Junior Perez CWS CWS @ ATHLETICS@ Home Runs 0.5 3.2 D 9.2 -5 Pending
1348 Junior Perez CWS CWS @ ATHLETICS@ Runs Batted In 0.5 3.2 D 9.2 -5 Pending
1349 Kahlil Watson CLE CLE @ MIA Home Runs 0.5 3.2 D 9.2 -5 Pending
1350 Kahlil Watson CLE CLE @ MIA Runs Batted In 0.5 3.2 D 9.2 -5 Pending
Showing 1326–1350 of 1465 picks

Methodology

A unified ranking engine that scores every pick on a 0–100 scale — props, sides, and totals on one board.

The Nex Engine doesn't just find edges — it ranks them. Every candidate pick runs through a four-layer scoring system that weighs the raw data, the play type's historical reliability, role stability, and how well it fits a winning daily card. The result is a single number that tells you exactly where each play stands relative to every other play on the board.

The 4 Scoring Dimensions

Raw Edge (50% weight) — The foundation. For props, this measures hit rate vs. the line, projected stat edge, minutes security, role stability, and usage opportunity. For sides, it factors injury edge, home court advantage, team strength gaps, recent form, and market alignment. This is where the pure data advantage lives.

Play-Type Trust — Not all play types are created equal. Moneylines on home favorites, star player rebounds, and small spreads have historically higher conversion rates — so they score higher. Role-player 3PM props and large spreads get docked because the variance is too high. This layer filters out plays that look good on paper but don't cash consistently.

Cleanliness — A stability check. Star players with locked-in minutes and defined roles score higher. Bench players, blowout-risk games, injury-dependent usage bumps, and hot-shooting reliance all get penalized. Clean plays are repeatable plays.

Card Fit — Built for daily card construction. This layer favors the pick types that historically perform on daily cards — moneylines, star rebounds and assists, tight spreads. It deprioritizes picks that might have edge in isolation but don't build well into a cohesive card.

Reading the Board

Score 75+ — Elite territory. These plays have strong edge across all four dimensions. The engine's highest conviction picks.

Score 65–74 — Strong plays with solid fundamentals. Multiple dimensions are firing and the overall profile is clean.

Score 55–64 — Above average. The edge is there, but one or two dimensions may be weaker. Still viable, especially in combination with other signals.

Below 55 — Below the recommended threshold. The engine sees some edge but not enough to rank it as a confident play.

The Nex Board rebuilds automatically as new odds and stats flow in. Scores and rankings can shift throughout the day as the market moves.