📡 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 |
← Sep 7 →
Wins
2
Losses
2
Push
2
Win %
50%
Pending
0
Record based on top 6 Nex Board prop picks daily (all sports), ranked by card score.
Sat 10/10 Fri 10/9 Thu 10/8 Wed 10/7 Tue 10/6 Mon 10/5 Sun 10/4 Sat 10/3 Fri 10/2 Thu 10/1 Wed 9/30 Tue 9/29 Sun 9/27 Sat 9/26
Sport: All NBA MLB NFL WNBA
Stat:
🤖 AI Plays
1
Mookie Betts
LAD LAD @ CIN MLB
Runs 0.5 OVER
64.8 B-
  • Heavy minutes projection
  • Stable player role
  • Strong matchup profile
Raw
84
Clean
23.2
Fit
0
2
Chase Burns
LAD LAD @ CIN MLB
Strikeouts 4.5 OVER
60.9 C+
  • Heavy minutes projection
  • Stable player role
Raw
78
Clean
22.2
Fit
0
3
Teoscar Hernandez
LAD LAD @ CIN MLB
Hits 0.5 OVER
59 C+
  • Heavy minutes projection
  • Stable player role
  • Strong matchup profile
Raw
78
Clean
20.2
Fit
0
4
Thomas Saggese
SF SF @ STL MLB
Hits 0.5 OVER
57.9 C+
  • Heavy minutes projection
  • Stable player role
  • Strong matchup profile
Raw
73
Clean
21.4
Fit
0

📋 Full Board (976 picks · Page 1/40)

#ActionPickMatchupTypeLine ScoreTierCleanFit Result
1 Mookie Betts LAD LAD @ CIN Runs 0.5 64.8 B- 23.2 0 Pending
2 Chase Burns LAD LAD @ CIN Strikeouts 4.5 60.9 C+ 22.2 0 Pending
3 Teoscar Hernandez LAD LAD @ CIN Hits 0.5 59 C+ 20.2 0 Pending
4 Thomas Saggese SF SF @ STL Hits 0.5 57.9 C+ 21.4 0 Pending
5 Grayson Rodriguez BOS BOS @ LAA Strikeouts 4.5 57.7 C+ 21.8 0 Pending
6 Cooper Pratt MIL MIL @ CHC Runs Batted In 0.5 57.3 C+ 19.3 0 Pending
7 Joshua Baez SF SF @ STL Hits 0.5 57 C 21.1 0 Pending
8 Nathan Church SF SF @ STL Hits 0.5 56.9 C 21.2 0 Pending
9 Ozzie Albies PHI PHI @ ATL Hits 0.5 56.6 C 23.2 0 Pending
10 Mookie Betts LAD LAD @ CIN Total Bases 1.5 55.9 C 19.4 0 Pending
11 Mookie Betts LAD LAD @ CIN Hits 0.5 55.4 C 19.8 0 Pending
12 Tommy Edman LAD LAD @ CIN Runs 0.5 55.4 C 19.8 0 Pending
13 Andrew Vaughn MIL MIL @ CHC Runs Batted In 0.5 55.4 C 20.2 0 Pending
14 Carlos Jorge LAD LAD @ CIN Hits 0.5 55.4 C 20.2 0 Pending
15 Elly De La Cruz LAD LAD @ CIN Runs 0.5 55.4 C 20.2 0 Pending
16 Elly De La Cruz LAD LAD @ CIN Hits 0.5 54.9 C 19.4 0 Pending
17 Thomas Saggese SF SF @ STL Runs 0.5 54.9 C 19.4 0 Pending
18 Jackson Chourio MIL MIL @ CHC Runs 0.5 54.7 C 19.8 0 Pending
19 Alex Bregman MIL MIL @ CHC Runs 0.5 54.6 C 20.2 0 Pending
20 Mookie Betts LAD LAD @ CIN Runs Batted In 0.5 54.6 C 18.8 0 Pending
21 Tommy Edman LAD LAD @ CIN Hits 0.5 54.6 C 19 0 Pending
22 Ivan Herrera SF SF @ STL Runs 0.5 54.4 C 19.5 0 Pending
23 Turner Hill SF SF @ STL Runs Batted In 0.5 54.4 C 19.5 0 Pending
24 Eugenio Suarez LAD LAD @ CIN Runs 0.5 53.9 C 19.4 0 Pending
25 Joshua Baez SF SF @ STL Runs 0.5 53.9 C 19.4 0 Pending
Showing 1–25 of 976 picks
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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.