📡 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 4 – Jul 10 →
Wins
11
Losses
7
Win %
61.1%
Pending
0
Fri 10/23 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
Sport: All NBA MLB NFL WNBA
Stat:
🤖 AI Plays
1
DAL @ TORONT WNBA
Points 21.5 OVER
67.2 B-
  • Heavy minutes projection
  • Stable player role
Raw
57
Clean
28.6
Fit
4
2
DAL @ TORONT WNBA
Points 21.5 OVER
63.6 B-
  • Projected edge vs line
  • Heavy minutes projection
  • Stable player role
Raw
63
Clean
21
Fit
4
3
DAL @ TORONT WNBA
Assists 6.5 OVER
63.1 B-
  • Heavy minutes projection
  • Stable player role
Raw
43
Clean
28.6
Fit
5
4
DAL @ TORONT WNBA
Rebounds 4.5 OVER
62.8 C+
  • Heavy minutes projection
  • Stable player role
Raw
48
Clean
23
Fit
5

📋 Full Board (1471 picks · Page 34/59)

#ActionPickMatchupTypeLine ScoreTierCleanFit Result
826 Gavin Sheets SD TOR @ SD Runs 0.5 7.5 D 9.2 -5 Pending
827 Jake Cronenworth SD TOR @ SD Home Runs 0.5 7.5 D 9.2 -5 Pending
828 Jorge Polanco NYM BOS @ NYM Runs 0.5 7.5 D 9.2 -5 Pending
829 Jorge Polanco NYM BOS @ NYM Runs Batted In 0.5 7.5 D 9.2 -5 Pending
830 Luis Campusano SD TOR @ SD Home Runs 0.5 7.5 D 9.2 -5 Pending
831 Luis Campusano SD TOR @ SD Runs Batted In 0.5 7.5 D 9.2 -5 Pending
832 Miguel Andujar SD TOR @ SD Total Bases 1.5 7.5 D 9.2 -5 Pending
833 Sung-Mun Song SD TOR @ SD Runs Batted In 0.5 7.5 D 9.2 -5 Pending
834 Daniel Schneemann CLE CLE @ MIA Total Bases 1.5 7.3 D 9.2 -5 Pending
835 Luis Urias TOR TOR @ SD Total Bases 1.5 7.3 D 9.2 -5 Pending
836 Sal Frelick MIL MIL @ PIT Total Bases 1.5 7.3 D 9.2 -5 Pending
837 Tyler Soderstrom OAK OAK @ ATHLETICS@ Total Bases 1.5 7.3 D 9.2 -5 Pending
838 Chandler Simpson TB SEA @ TB Total Bases 1.5 6.8 D 9.2 -5 Pending
839 Ernie Clement TOR TOR @ SD Total Bases 1.5 6.5 D 9.4 -5 Pending
840 TJ Rumfield COL COL @ SF Total Bases 1.5 6.5 D 9.4 -5 Pending
841 Willi Castro COL COL @ SF Total Bases 1.5 6.5 D 9.4 -5 Pending
842 Shane Bieber TOR TOR @ SD Strikeouts 4.5 6.5 D 11.8 -5 Pending
843 Alec Burleson STL ATL @ STL Runs Batted In 0.5 6.5 D 9.2 -5 Pending
844 Blaze Jordan STL ATL @ STL Runs 0.5 6.5 D 9.2 -5 Pending
845 Curtis Mead WSH NYY @ WSH Runs Batted In 0.5 6.5 D 9.2 -5 Pending
846 Elly De La Cruz CIN CHC @ CIN Runs 0.5 6.5 D 9.2 -5 Pending
847 JJ Bleday CIN CHC @ CIN Total Bases 1.5 6.5 D 9.2 -5 Pending
848 Jo Adell LAA LAA @ MIN Runs 0.5 6.5 D 9.2 -5 Pending
849 Jonathan Aranda TB SEA @ TB Runs Batted In 0.5 6.5 D 9.2 -5 Pending
850 Myles Straw TOR TOR @ SD Runs Batted In 0.5 6.5 D 9.2 -5 Pending
Showing 826–850 of 1471 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.