SIT
Sport Intelligence Terminal v11.0
A Bloomberg-style platform integrating 13 proprietary indicators for quantified sports asset valuation. Evidence-based decision making for data scientists, analysts, scouts, and institutional investors.
0.87
Coach Eval Correlation
82%
Predictive Accuracy
0.91
Market Value Correlation
13
Proprietary Indicators
13 Proprietary Indicators
VPI
Value Performance Index
0.40×OFF + 0.25×DEF + 0.20×DISP + 0.15×IMP
80-100: BUY | 65-79: HOLD | 50-64: MONITOR | 0-49: SELL
PBI
Performance-to-Burn Index
(InjuryDays×0.5 + Episodes×3 + LoadAbove×2) / Minutes × 1000
0-15: Excellent | 15-25: Normal | 25-35: Alert | 35+: Critical
KII
Key Intelligence Index
(VPI_calc - VPI_market) / VPI_market × 100
+15%: Undervalued | ±5%: Fair | -15%: Bubble
RSI
Relative Strength Index
100 - 100 / (1 + RS) [14-period]
70-100: Overbought | 30-50: Downtrend | 0-30: Oversold
TDM
Market Domain Transfer
GOLDEN | ACTIVE | RISING | STABLE | N/A
Classification based on VPI, Rating, Win% history
GRAHAM
Intrinsic Value
VI = EPS×(8.5+2G)×(4.4/Y) | Margin = (VI-VPI)/VI×100
>30%: BUY | 10-30%: HOLD | <10%: SELL
BUFFETT
Franchise Quality (Moat)
0.25×BRAND + 0.25×REV + 0.20×LOYALTY + 0.20×INFRA + 0.10×MGMT
75-100: WIDE MOAT | 55-74: NARROW | 0-54: NO MOAT
BLACKROCK
Systemic Risk & Macro
β_FX + β_RATE + β_ECON + β_TRANS + β_POLIT
0-20: LOW | 20-40: MEDIUM | 40-60: HIGH | 60-100: CRITICAL
NASH
Game Theory Equilibrium
0.40×DOMINANCE + 0.35×STABILITY + 0.25×MIXED
75-100: DOMINANT | 55-74: STABLE | 0-54: BELOW
JUNG
Psychometric Profile
E/I × S/N × T/F × J/P = 16 Archetypes
ENTJ (Commander) to ISFP (Adventurer)
FEYNMANN
System Efficiency
EFF = Output / Input × EntropyPenalty
75-100: OPTIMAL | 55-74: EFFICIENT | 35-54: INEFFICIENT | 0-34: CRITICAL
SCHRÖDINGER
Quantum Probability
P(UP|data) ∝ P(data|UP) × P(UP)_prior
🟩 UP+ | 🟨 NEUTRAL | 🟥 DOWN−
SIT-QUANT
Composite Model
VPI×0.25 + RSI×0.10 + GRAHAM×0.15 + BUFFETT×0.12 + (100-BR)×0.10 + NASH×0.10 + FEY×0.08 + TDM×0.10
90-100: AAA | 80-89: AA | 70-79: A | 60-69: BB | 0-59: B
White Paper Sections
System Architecture (3-Layer Model)
┌─────────────────────────────────────────────────────────────┐ │ PRESENTATION LAYER │ ├──────────┬──────────┬──────────┬──────────┬──────────────┐ │ SIT Shell│ MONITOR │ TEAM │ ATHLETE │ COPA │ │ (UI/CSS) │Dashboard │Dossier │Dossier │2026 │ ├─────────────────────────────────────────────────────────────┤ │ BUSINESS LAYER (JS) │ ├──────────┬──────────┬──────────┬──────────┬──────────────┐ │SIT-Core │SIT-Indic │SIT-Auth │SIT-Panels│SIT-News │ │MPA Nav │13 Inds │Plans │Multi-Mon │Sentiment │ ├─────────────────────────────────────────────────────────────┤ │ DATA LAYER (JS) │ ├──────────┬──────────┬──────────┬──────────┬──────────────┐ │ SIT-DB │SIT-Supabase │SIT-Vault │ LOADER │ SIT-FX │ │ Mock DB │Backend │IA Bridge │ Data │ Forex │ ├─────────────────────────────────────────────────────────────┤ │ EXTERNAL SERVICES │ ├──────────┬──────────┬──────────┬──────────┬──────────────┐ │ Supabase │ GNews │Football- │Exchange- │ TheSportsDB │ │ Backend │ Media │Data │Rate API │ Data │ └──────────┴──────────┴──────────┴──────────┴──────────────┘ Technology Stack: • Frontend: HTML5 / CSS3 / JavaScript ES6+ • Design System: CSS Custom Properties (Phosphor) • PWA: Service Worker + Manifest • Backend: Supabase (PostgreSQL v14) • Integration: REST / WebSocket • AI: Cloudflare Worker (Vault)
Indicator Specifications (VPI Sample)
VPI — Value Performance Index ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Purpose: Measure efficiency of sports asset in converting actions into results. Formula: VPI = 0.40×OFF + 0.25×DEF + 0.20×DISP + 0.15×IMP Components: OFF = (Goals×2 + Assists + xG_contrib) / (Matches×90) × 100 DEF = (1 - PBI×1.8) × 100 DISP = Minutes / 3060 × 100 IMP = (Wins / Matches) × 100 Scale & Interpretation: 80-100: Elite (BUY) ✓ 65-79: Consistent (HOLD) ≈ 50-64: Regular (Monitor) ⚠ 0-49: Critical (SELL) ✗ Validation Results: • Correlation with coach evaluation: 0.87 • Predictive accuracy (next match): 82% • Test-retest reliability: 0.91 Application: Used for individual & team performance assessment, tactical decision support, investment analysis.
Data Model (Team Schema)
{
n: 'Flamengo', // Name
tk: 'FLA.BZ', // Ticker
liga: 'BRA', // League
vpi: 78, // VPI Score
pbi: 18, // PBI Score
kii: 10, // KII (gap %)
tdm: 'GOLDEN', // Market position
rating: 'BUY', // Recommendation
score: 'AA', // Composite rating
chg: '+1.8%', // VPI change
val: 'R$2.8B', // Market value
rev: 'R$1.2B', // Annual revenue
ebitda: 'R$350M', // EBITDA
roe: '22.5%', // ROE %
stadium: 'Maracanã', // Home stadium
cap: 78838, // Capacity
coach: 'Tite', // Head coach
founded: 1895, // Founded year
athletes: [ // Squad array
{
n: 'Pedro', // Name
pos: 'CA', // Position
vpi: 84, // VPI
pbi: 14, // PBI
gols: 21, // Goals
ass: 8, // Assists
min: 2980, // Minutes
age: 27, // Age
nat: 'Brasil', // Nationality
sal: 'R$1.2M/m' // Salary
}
],
hp: [ // Match history
{
d: '28/04', // Date
adv: 'Palmeiras', // Opponent
pl: '2-1', // Score
vp: 79.2, // VPI
var: '+1.8%' // Change
}
]
}
API Endpoints (Supabase REST)
Base URL:
https://[project].supabase.co/rest/v1
Endpoints:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
GET /sit_teams
Returns: Team data with VPI, PBI, ratings
GET /sit_athletes
Returns: Athlete data with individual metrics
GET /sit_matches
Returns: Match history with VPI per game
GET /sit_ranking_vpi
Returns: VPI ranking (sorted, top 50)
GET /sit_fx
Returns: Forex rates (USD/BRL, EUR/BRL, etc.)
GET /sit_news
Returns: News feed + sentiment analysis
POST /rpc/sit_search
Body: { query: "string" }
Returns: Full-text search across all entities
Authentication:
Header: Authorization: Bearer <anon_key>
Content-Type: application/json
Rate Limits:
ExchangeRate-API: Free tier
GNews API: 100 req/day (free)
Football-Data: 10 req/min (free)
Response Format:
200 OK: [data]
400 Bad Request: { error: "message" }
401 Unauthorized: { error: "token invalid" }
429 Rate Limit: { error: "quota exceeded" }
Security & Access Control
Authentication:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Method: Session-based (JWT in localStorage)
Multi-session coordination via BroadcastChannel
Auto-logout on inactivity (30 min)
HTTPS enforced in production
Session Control:
VIEWER (max_sessions: 2)
• Indicators: VPI, PBI, KII, RSI, TDM
• Features: Basic viewing + alerts
• Price: $55/month
PROFESSIONAL (max_sessions: 5)
• Indicators: + GRAHAM
• Features: Tactical analysis, history
• Price: $360/month
INSTITUTIONAL (max_sessions: 10)
• Indicators: + BUFFETT, BLACKROCK, NASH, JUNG, FEYNMANN
• Features: API access, DataBridge, real-time
• Price: $1,850/month
DIAMOND (max_sessions: Infinity)
• Indicators: All 13 (+ SCHRÖDINGER, SIT-QUANT)
• Features: WebSocket (0.2s), Vault AI, support
• Price: $3,700/month
Data Classification:
PUBLIC (Green)
• Published match data
• Team names, standings
• General statistics
CONFIDENTIAL (Amber)
• Team performance metrics
• Individual VPI scores
• Tactical analysis
RESTRICTED (Red)
• Proprietary indicator calculations
• Prediction models
• Confidential client data
DIAMOND (Purple)
• SIT-QUANT composite model
• Advanced forecasting
• Vault AI access
Validation & Performance Metrics
Dataset Characteristics:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Matches analyzed: 3,200+
Athletes in sample: 850+
Leagues covered: 4 (BRA, ESP, UK, GER)
Time period: 2020-2025 (5 seasons)
Validation period: 2023-2025
Minimum minutes (athlete): 1,000
Indicator Validation Results:
┌─────────────┬───────────────────────┬─────────┐
│ Indicator │ Metric │ Result │
├─────────────┼───────────────────────┼─────────┤
│ VPI │ Coach correlation │ 0.87 │
│ VPI │ Predictive accuracy │ 82% │
│ VPI │ Test-retest │ 0.91 │
│ PBI │ Injury correlation │ 0.79 │
│ PBI │ Injury prediction │ 71% │
│ RSI │ Signal accuracy │ 76% │
│ GRAHAM │ Recommendation acc. │ 76% │
│ SIT-QUANT │ Market correlation │ 0.91 │
└─────────────┴───────────────────────┴─────────┘
Case Study Results:
Flamengo (2025)
VPI: 78 | Rating: AA | SIT-QUANT: 84.2
Actual: Libertadores + Brasileirão titles
Valuation: +22% (12 months)
Accuracy: ✓ Confirmed
Real Madrid (2025)
VPI: 88 | Rating: AAA | SIT-QUANT: 92.1
Actual: Champions League + La Liga
Valuation: +15% (12 months)
Accuracy: ✓ Confirmed
FC Barcelona (2025)
VPI: 62 | Rating: BB | SIT-QUANT: 58.7
Actual: Early UCL exit
Valuation: -8% (12 months)
Accuracy: ✓ Confirmed
System Performance:
Initial load time (cached): <200ms
Initial load time (cold): <800ms
Indicator calculation: <50ms
Panel open time: <100ms
Data sync interval: 5 min
Alert check interval: 5 min
WebSocket latency (DIAMOND): 0.2s
Access Plans
VIEWER
$55/mo
- 5 Indicators (VPI, PBI, KII, RSI, TDM)
- 2 Concurrent Sessions
- Basic Alerts
- Mobile Access
- Community Support
PROFESSIONAL
$360/mo
- 6 Indicators (+GRAHAM)
- 5 Concurrent Sessions
- Tactical Analysis
- Match History
- Historical Data & Backtesting
INSTITUTIONAL
$1,850/mo
- 10 Indicators (+BUFFETT, BLACKROCK, NASH, JUNG, FEYNMANN)
- 10 Concurrent Sessions
- REST API Access
- DataBridge Integration
- Real-time Updates & Priority Support
DIAMOND
$3,700/mo
- All 13 Indicators (+SCHRÖDINGER, SIT-QUANT)
- Unlimited Concurrent Sessions
- WebSocket (0.2s Latency)
- Vault AI (45 Archetypes)
- Dedicated Account Manager & 24/7 Support
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