NoticeMadDataScientist Ultimate Sports Analytics is currently in free public testing. Features may require a periodic or one-time payment upon full production launch on MadDataScientist.net.
SEC Conference | Baseline Power Rating: 93.8 | National Championship Contender
93.8
Power Score
?
Power Score: Composite 0-100 rating combining offensive efficiency, defensive EPA, strength of schedule, and player power ratings.
92.5
Offense
?
Offense Index: Expected Points Added (EPA) per play, passing efficiency, and red zone touchdown conversion rate.
94.2
Defense
?
Defense Index: Opponent EPA per play allowed, third-down stop rate, and sack/pressure rate.
+0.82
Agent Sentiment
?
Agent Sentiment: Daily multi-agent NLP sentiment score (-1.0 to +1.0) scoured from news, press conferences, and social feeds.
2026 Season Win Totals (O/U)
?
Season Win Totals: Comparison of expected regular season wins across the MadData Model, Vegas Lines, and ESPN FPI.3 SOURCES
CHART: SCORE DENSITY DISTRIBUTIONS#scoreDistributionChart
Score Probability Distributions
?
Score Distributions: Gaussian kernel density estimates showing probability of final team scores over 10,000 Monte Carlo runs.
CHART: BOX PLOT DISTRIBUTIONS#boxPlotChart
Horizontal Score Prediction Box Plots (Stacked Team Comparisons)
?
Horizontal Box Plots: Stacked median, interquartile range (IQR 25%-75%), and score boundary ranges for both teams.
CHART: TEAM EFFICIENCY RADAR#efficiencyRadarChart
Team Efficiency Radar
?
Efficiency Radar: Multi-axis comparison across Passing EPA, Rushing Power, Red Zone Defense, Turnover Margin, Special Teams, and Sentiment. Tweak sliders below to shift the live model!
CHART: KEY WIN PROBABILITY DRIVERS#keyDriversChart
Win Probability Key Model Drivers
?
Model Drivers: Impact weight of individual variables (+/- win probability %) shifting the final simulation outcome. Tweak sliders to recalculate!
Net Power Rating Diff ?Core rating gap impact on win probability (+/- %).+12.5%
Home Field Advantage ?Crowd & stadium impact shifting win probability (+%).+5.0%
Environmental & Sentiment Simulation Controls
?
What-If Simulator: Test sensitivity variations by adjusting weather parameters and sentiment weighting to see real-time shifts in point spreads and win odds.
Temperature Offset (°F)0°F
Wind Speed Offset (mph)0 mph
Precipitation Risk (%)10%
Sentiment Influence Weight1.0x
Simulation Output Results:
Recalculated Spread: -
Home Win %: -
Total Score: -
PANEL: LIVE INTELLIGENCE STREAM#tab-agents
Live Intelligence Stream (YouTube, Twitter/X, Weather, News)
PANEL: MOCK BETTING SLIP & HISTORY#tab-bets
WAGER FORM #betForm
Place Mock Bet
SETTLEMENT HISTORY #betHistoryBody
Wager Settlement History
Type
Selection
Stake
Payout
Status
PANEL: ADMIN CONTROL ROOM#tab-admin
Platform Registered Users
ID
Username
Email
Role
Bankroll
Joined
Real-Time Audit Activity Log
Time
User
Action
Description
MODAL: AUTHENTICATION#authModal
Welcome to MadDataScientist
Access Autonomous Sports Analytics, Custom Simulations, and Mock Betting.
Monte Carlo engine executes 10,000 game runs by sampling scores from Gaussian kernel distributions centered around Expected Score medians with positional volatility scaling.
Home Wins: 7,240 (72.4%)
Cover %: 53.1%
Over %: 51.2%
Sim Run #
Winner
Home Score
Away Score
Total PTS
Margin
Cover Spread?
Over Total?
Showing first 500 rows out of 10,000 Monte Carlo runs (Use search to query specific runs)500 Rows Displayed
Sentiment NLP Calculation Methodology
Multi-Source VADER & Transformer Sentiment Architecture
The MadDataScientist AI engine continuously ingests unstructured text feeds across 6 sports intelligence vectors. Sentiment polarity scores range from -1.00 (Extremely Negative / Heavy Risk) to +1.00 (Extremely Positive / High Confidence).
Step-by-Step Scoring Pipeline:
Text Ingestion & Parsing: Extracts transcripts from YouTube press conferences, beat writer news articles, Twitter/X posts, and betting consensus reports.
Composite Net Index: Weighted average shifts team baseline expected points by up to ± 2.5 Points in the Monte Carlo simulation engine.
Media & Analyst Source Articles Review
Review individual scoured articles, videos, and feeds with AI sentiment scores. Toggle items to include or exclude from model calculations.
Add Custom Feed, Video, or Article Source
YouTube AI Video Summary Breakdown
Inference Engine: LM Studio (Local)•YouTube Transcript Analysis
Gemini-Style Executive AI Summary
Analyzing video transcript...
Extracted Sentiment:+0.82 Positive
Key Tactical Takeaways & Film Breakdown
Timestamped Chapter Highlights & Key Moments
Timestamp
Chapter Focus
AI Insight & Note
AI Engine Configuration
Select and configure the AI engine powering your MadDataScientist AI Chat Assistant and Autonomous Video Film Breakdowns. You can connect to leading foundational cloud models or run local private LLMs.
Google Gemini
OpenAI (GPT-4o)
Claude (Sonnet)
Ollama (Local)
LM Studio (Local)
MadData Local
Groq (Fast)
DeepSeek
Keys are securely stored in your local browser session and never shared.
Default: http://localhost:11434 for Ollama, http://localhost:1234/v1 for LM Studio.