MULTI-SPORT MODEL NETWORK
MLB · NFL · NBA + MORE

PROPULATION

Predictive Intelligence Across Every Game

One intelligence layer for baseball, football, basketball, and beyond — combining live market signals, matchup context, player form, and proprietary models into clear, actionable projections.

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Baseball Football Basketball Live market data
PREDICTION NEXUS · LIVE
Baseball model
Football model
Basketball model
+8.4%EDGE
Best live signal
74HIGH
Model confidence
3SYNCED
Sports online
Multi-Sport
Model Network
10K
Simulation Runs
Real-Time
Market Intelligence
MLB · NFL · NBA
Core Sports Coverage
Models

Projection Systems

Purpose-built engines for the way each sport actually works — unified by a shared layer of live context, probability modeling, uncertainty, and market comparison.

● LIVE
NFL · PLAYER PROPS
NFL Model

Top-down player-prop projections — pass, rush, receiving, tackles and PrizePicks fantasy score — built on a Monte Carlo game simulator with measured usage priors and market-line comparison.

Monte Carlo
FULL DISTRIBUTIONS
Vegas Lines
EDGE vs MARKET
Launch NFL Model
 ● MEMBER ACCESS
NBA · PLAYER MARKETS
Basketball Intelligence

Player projections built around role, minutes, pace, opponent context, injuries, and the usage shifts that move basketball markets fastest.

Role Aware
MINUTES + USAGE
Live Context
INJURY ADJUSTED
Access NBA Research
 ● BETA
NBA · ADVANCED RESEARCH CONSOLE
NBA ARC

Live NBA injury intelligence from the official injury report, with projections and research tools rolling out through the season.

Live
INJURY FEED
Beta
EARLY ACCESS
Launch NBA ARC
 ● LIVE
MLB · PITCHER PROJECTIONS
MLB K Model

Per-batter strikeout probability engine with Bayesian H2H blending, platoon splits, pitch mix analysis, and full fantasy scoring.

xFIP/SIERA
ERA BASE
Lineup Intel
MATCHUP ANALYSIS
Launch K Model
 ● LIVE
KBO · PITCHER PROJECTIONS
KBO K Model

Korean Baseball Organization strikeout projections with per-batter handedness splits, KBO park factors, and live lineup import.

Park Adj.
BALLPARK FACTORS
LHB/RHB
PLATOON SPLITS
Launch KBO Model
 ● LIVE
NPB · PITCHER PROJECTIONS
NPB K Model

Nippon Professional Baseball strikeout projections with platoon splits, NPB park factors, live lineup import, and per-batter K probability.

Park Adj.
BALLPARK FACTORS
LHB/RHB
PLATOON SPLITS
Launch NPB Model
How It Works

One System. Every Edge.

Generic averages miss what changes the game. Our models read sport-specific context, quantify uncertainty, and translate the result into one consistent decision layer.

01

Sport-Specific Engines

Every league gets its own feature set, priors, and simulation logic — from pitcher-batter interactions to target share and player usage.

02

Context That Updates

Lineups, injuries, expected minutes, roles, opponent strengths, weather, and venue context continuously reshape each projection.

03

Live Market Comparison

Current prop lines and odds are measured against the model distribution so meaningful gaps surface quickly and consistently.

04

Probability, Not Hype

We show the range, over/under probability, and confidence behind a number — not a single projection without context.

05

Signal Quality Controls

Freshness, sample size, model agreement, and market movement are checked before a signal earns higher confidence.

06

Fast Decision Workflow

Dense, scannable dashboards make it easy to move from a full slate to the strongest researched opportunities.

// interactive sample — tap to preview multi-sport signals
PROPULATION
MULTI-SPORT INTEL
EDGE DROP
3 SPORTS LIVE SAMPLE
✂
CLICK TO REVEAL
👆
NBA SIGNALHIGH
Illustrative
STARTING GUARD
PACE UP · USAGE +4.2%
24.1
PROJ PTS
62%
OVER PROB
74
CONF
+1.6 vs 22.5 line

ROLE-ADJUSTED EDGE
NFL SIGNALWATCH
Illustrative
WR1 TARGETS
SLOT MATCHUP · TARGETS UP
6.8
PROJ REC
58%
OVER PROB
67
CONF
+0.8 vs 6.0 line

MATCHUP-DRIVEN EDGE
MLB SIGNALHIGH
Illustrative
STARTING PITCHER
WHIFF MATCHUP · 6.0 xIP
7.3
PROJ K
68%
OVER PROB
78
CONF
+0.8 vs 6.5 line

LINEUP-ADJUSTED EDGE
tap the signal pack to reveal a cross-sport preview
Methodology

How the Model Network Thinks

A common probability pipeline connects specialized models across every sport, from raw inputs to a transparent range, confidence score, and market edge.

01

Live Inputs

Form, role, matchup, injuries, lineups, pace, venue, and market data are normalized for the sport being modeled.

02

Contextual Matchup Engine

Sport-specific interactions measure how a player's profile meets the exact opponent and game environment in front of them.

03

Probabilistic Blending

Recent evidence is balanced with stable priors so small samples inform the projection without overwhelming it.

04

Simulation + Market Test

Thousands of simulations produce a full outcome distribution, then compare it with the current market to quantify the edge.

// Multi-sport projection output
sport: "NBA"
market: "player_points"
projection: 24.1
range_p10_p90: 18.4 – 29.9
market_line: 22.5
over_probability: 61.8%
edge: +1.6 vs line

// Context + uncertainty
role_signal: "usage_up"
freshness: "live"
confidence: 74 / 100

// Traceability
model_version: "nexus_2.6"
simulation_count: 10,000
Context Intelligence

The Variables That Change the Projection

The strongest models react when the game changes. Propulation evaluates the role, matchup, and market signals that matter most in each sport — then shows how they alter the outcome range.

A projection is never just a season average. An NBA rotation change, an NFL coverage matchup, or an MLB lineup profile can change both the expected result and its uncertainty. The model network measures those changes before it scores an edge.

NBA · Role + Usage Shift
▲ PROJECTION EXPANDING
+4.2usage change
Projected minutes, teammate availability, pace, and on-court usage reveal when a player's opportunity has structurally changed.
NFL · Matchup + Opportunity
▲ TARGET SHARE SIGNAL
27%target share
Route participation, target share, game script, and defensive alignment work together to expose volume the box score alone can miss.
MLB · Lineup + Arsenal Fit
▲ FAVORABLE PROFILE
68%over probability
Pitch mix, handedness, chase, contact quality, park, and the confirmed lineup shape a distribution built for the actual matchup.

The bottom line: One platform, one visual language, and sport-specific intelligence underneath it — so every projection is easier to understand, compare, and act on.