Mashujaa vs Simba Statistics & Analysis

Pre-match snapshot for this fixture.

• League: Ligi kuu Bara
• Fixture: Mashujaa vs Simba
• Kickoff: 2026-05-14 13:15:00
• 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
• xG (showing): Mashujaa 1.45 — Simba 1.25 (total xG ≈ 2.7)
• Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
• Model: 74.4% · Implied: 59.1% · Probability edge: +15.3 pts · Est. EV: +29.5%
• BTTS (model): Yes 31.6% · No 68.4%
• Correct score (top bin): 0-1 (22.6%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

Correct score remains high-variance even when a line is most likely on paper.

Primary angle highlighted on the page: Under 2.5 goals.

If 1X2 looks tight, the engine may still find clearer structure in totals or BTTS — that is intentional.

Edges shrink quickly if prices move; always re-check the number on your book.

How should I read EV versus a probability gap?

Probability edge = model probability minus implied probability (reported here in percentage points). EV ≈ model probability × best tracked decimal odds − 1, shown as return per unit stake. They are related but not interchangeable labels.

Who has the edge in the match-winner market?

Use the 1X2 model percentages in the summary and the 1X2 market card: the side with the highest model % is the model lean, but check EV — a lean can still be -EV after prices.

What is the best-supported line in this snapshot?

Match the hero card above: if it says “Betting Primary Pick”, that leg cleared primary rules; if it says “Best +EV (tracked markets)”, it is the strongest +EV line that did not meet stricter Primary thresholds. The bullets below repeat the same model %, implied %, edge (pts), and EV % as that card.

Safer market than correct score?

Markets with more liquidity and smoother prices (often 1X2 or O/U 2.5 from many books) are usually easier to reason about than long-tail correct-score prices; still read EV on each leg.

• Price movement: implied probabilities and EV move with odds.
• Sample / data gaps: low-information leagues widen forecast bands.
• In-play state: goals and red cards are not modelled here.
• Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

• Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
• Compliance: Educational framing only; not personalised advice.

May 17, 2026 (UTC)