📡 SCORES
🏈 Loading...

⚡ Nex Board

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

Nex Board Record
1D 7D 14D 30D |
← Aug 20 – Sep 18 →
Wins
20
Losses
28
Push
3
Win %
41.7%
Pending
0
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 Fri 9/25
Sport: All NBA MLB NFL WNBA
Stat:
🤖 AI Plays
1
Total Bases 1.5 OVER
49.7 D
  • Heavy minutes projection
  • Stable player role
Raw
56
Clean
21.8
Fit
0
2
Hits 0.5 OVER
46.5 D
  • Heavy minutes projection
  • Stable player role
Raw
52
Clean
20.5
Fit
0
3
Hits 0.5 OVER
44.8 D
  • Heavy minutes projection
  • Stable player role
  • Higher volatility than ideal
Raw
50
Clean
19.9
Fit
0
4
Runs 0.5 OVER
41.5 D
  • Heavy minutes projection
  • Stable player role
  • Higher volatility than ideal
Raw
43
Clean
19.8
Fit
0

📋 Full Board (131 picks · Page 1/6)

#ActionPickMatchupTypeLine ScoreTierCleanFit Result
1 Jackson Merrill SD MIA @ SD Total Bases 1.5 49.7 D 21.8 0 Pending
2 Jackson Merrill SD MIA @ SD Hits 0.5 46.5 D 20.5 0 Pending
3 Griffin Conine MIA MIA @ SD Hits 0.5 44.8 D 19.9 0 Pending
4 Kyle Tucker LAD SF @ LAD Runs 0.5 41.5 D 19.8 0 Pending
5 Cody Bellinger NYY NYY @ ARI Home Runs 0.5 41.5 D 20.2 0 Pending
6 Griffin Conine MIA MIA @ SD Total Bases 1.5 40.6 D 20.1 0 Pending
7 Griffin Conine MIA MIA @ SD Runs 0.5 40 D 19.4 0 Pending
8 Jackson Merrill SD MIA @ SD Runs 0.5 40 D 19.4 0 Pending
9 Kyle Tucker LAD SF @ LAD Total Bases 1.5 37.7 D 17.8 0 Pending
10 Xander Bogaerts SD MIA @ SD Hits 1.5 35.6 D 19.4 0 Pending
11 Javier Sanoja MIA MIA @ SD Runs 0.5 34.2 D 17.8 0 Pending
12 Jonah Cox SF SF @ LAD Runs 0.5 34.2 D 17.8 0 Pending
13 Otto Lopez MIA MIA @ SD Total Bases 1.5 34.2 D 17.8 0 Pending
14 Kyle Tucker LAD SF @ LAD Runs Batted In 0.5 34.1 D 17.2 0 Pending
15 Xander Bogaerts SD MIA @ SD Total Bases 2.5 33.6 D 18.1 0 Pending
16 Christian Koss SF SF @ LAD Hits 0.5 33.5 D 17.4 0 Pending
17 Denzer Guzman LAA MIN @ LAA Runs Batted In 0.5 33.3 D 17.6 0 Pending
18 Jackson Merrill SD MIA @ SD Runs Batted In 0.5 33.3 D 17.6 0 Pending
19 Teoscar Hernandez LAD SF @ LAD Runs 0.5 33.3 D 17.6 0 Pending
20 Xavier Edwards MIA MIA @ SD Hits 0.5 33.3 D 17.6 0 Pending
21 Jakob Marsee MIA MIA @ SD Total Bases 1.5 31.2 D 17.2 0 Pending
22 Enrique Hernandez LAD SF @ LAD Runs Batted In 0.5 30.5 D 17.2 0 Pending
23 Freddie Freeman LAD SF @ LAD Hits 0.5 30.5 D 17.2 0 Pending
24 Jakob Marsee MIA MIA @ SD Runs Batted In 0.5 30.2 D 17.2 0 Pending
25 Javier Sanoja MIA MIA @ SD Runs Batted In 0.5 30.2 D 17.2 0 Pending
Showing 1–25 of 131 picks
← Prev 1 2 3 4 5 6 Next →

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.