Mtibwa Sugar vs Dodoma Jiji Statistics & Analysis

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

• League: Ligi kuu Bara
• Fixture: Mtibwa Sugar vs Dodoma Jiji
• Kickoff: 2026-05-06 13:00:00
• 1X2 (model): Home 35.0% · Draw 35.0% · Away 30.0%
• xG (showing): Mtibwa Sugar 1.45 — Dodoma Jiji 1.25 (total xG ≈ 2.7)
• Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
• Model: 69.0% · Implied: 60.4% · Probability edge: +8.6 pts · Est. EV: +15.2%
• BTTS (model): Yes 36.0% · No 64.0%
• Correct score (top bin): 0-1 (15.7%)

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

1X2 can look balanced even when side markets show clearer structure.

Primary pick from the decision engine: Under 2.5 goals.

Model probability is compared to implied probability from odds to highlight a probability edge; EV uses the same model probability with the best decimal price tracked.

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

Is the most likely correct score a good bet?

Usually no as a standalone bet: the “most likely” scoreline is still a low absolute probability tail event (often single digits, sometimes low teens). Use it as context; keep any correct-score stake in the “fun / small” bucket.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

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.

What changes first if odds move?

Implied probabilities and EV move immediately with price; model probabilities in this snapshot do not update until the pipeline is re-run. Refresh after material line moves.

• 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)