Match Analyzer — Statistical Predictions for KBO/MLB/Soccer

Combines market data + news evidence + Monte Carlo simulation
(50,000+ runs) into one structured match outcome prediction. Built
for sports fans, analysts, and content creators who want a data-backed
read on a game — not a bare gut feeling.

What makes this different

Most prediction tools just spit out a win percentage. Match Analyzer
shows its work:

• Evidence-driven inputs — starting pitcher form, bullpen state,
  injuries, lineup news, and head-to-head splits are pulled from
  current sources, not assumed.
• Calibration rules from real backtests — e.g., when a home
  underdog starts an ace-level pitcher, the model weights a "dominant
  win" outcome heavier than a naive read would, based on documented
  historical misses.
• Model vs. market comparison — shows where the model's
  probability diverges from the market's implied probability, and
  explains why (which piece of evidence is driving the difference).
• Confidence-aware output — when data is thin or the model
  essentially agrees with the market consensus, it says so plainly
  instead of forcing a confident-sounding pick.

Coverage

• Baseball: KBO, MLB
• Soccer: World Cup, EPL, and other major leagues

Example output

Input: LG Twins (home) vs Doosan Bears — Aug 5

■ Market Data
- Moneyline (implied): LG 54% / Doosan 51% (raw, pre-devig)
- Run line: LG -1.5
- Total: 8.5

■ Key Evidence
- LG starter: 2.1 ERA last 5 starts, well-rested
- Doosan: bullpen used heavily last 3 games
- Park factor: hitter-friendly

■ Simulation (sims=50,000)
- Expected runs: LG 5.1 | Doosan 4.0
- Win%: LG 61% | Doosan 39%
- Run line cover: LG -1.5 → 47%
- Over/Under 8.5: Over 54%

■ Model vs Market Probability
- Model probability vs market fair probability: 61% vs 54%
- Probability gap: +7pp — driven mainly by the starter's rested workload
  and recent bullpen fatigue on the Doosan side

■ Final Prediction
- Outcome: LG win (confidence 3/5)
- Key reasoning: rested ace-level starter + tired opposing bullpen
- Note: lineup news should be reconfirmed close to first pitch

Statistical prediction based on a probability model — not betting
advice. This tool does not calculate stake sizing or place bets.

Who this is for

• Sports fans who want a data-backed second opinion on a matchup
• Content creators writing daily match preview posts
• Analysts who want a transparent, evidence-linked prediction instead
  of a black-box percentage

FAQ

Does this guarantee outcomes?
No. This is a probability-model prediction tool, not a certainty
machine. Markets and models both get it wrong — the tool is built to
show its confidence level honestly rather than force a strong-sounding
pick every time.

Does this help with betting decisions?
No — this tool does not calculate stake sizing, parlays, or any
betting-related output. It produces a statistical outcome prediction
with supporting evidence, intended for analysis and content, not
wagering.

What if odds/market data aren't available for a match?
The simulation still runs on team stats and evidence alone; the
"model vs market" section is simply omitted.

Which language does it output in?
Follows the language of your input automatically.

How is the simulation validated?
Calibration rules are adjusted based on documented backtest misses —
re-checked against edge cases like ace-pitcher matchups and
small-sample statistics, not just overall win rate.

⚠️ Statistical analysis tool only. Not betting advice, not affiliated
with any sportsbook, league, or team.