Statistics / Football / Tanzania. Ligi kuu Bara / KMC vs Young Africans

KMC vs Young Africans Statistics & Analysis

May 06, 2026 - 13:00
0 1.45
1 1.25
xG Accuracy: 63%
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Tracked markets vs full-time result

Each row compares the model’s highlighted side (or lean) to what happened at full time.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 KMC Young Africans ✖ Incorrect
  • Correct Score Insights 0-1 0-1 ✔ Correct

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Ligi kuu Bara
  • Fixture: KMC vs Young Africans
  • Kickoff: 2026-05-06 13:00:00
  • 1X2 (model): Home 0.0% · Draw 50.0% · Away 50.0%
  • xG (showing): KMC 1.45 — Young Africans 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 59.6% · Implied: 40.4% · Probability edge: +19.2 pts · Est. EV: +36.5%
  • BTTS (model): Yes 28.0% · No 72.0%
  • Correct score (top bin): 0-1 (19.6%)

Totals and BTTS are evaluated against current market prices where available.

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

Best Bet + Reason

The engine’s headline primary is: 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.

Only one modest +EV edge is highlighted here; size cautiously and re-check if odds move.

FAQ

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.

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.

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.

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.

Risk Factors

  • 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%).

Methodology

  • 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.

Last Updated

May 17, 2026 (UTC)

How to use this
  • Focus on the Primary line when you want one actionable idea.
  • Do not parlay many thin-edge picks together; edges do not add reliably.
  • Treat longshots as optional, high-stake-sizing plays only.

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Back to Statistics
Ligi kuu Bara Ligi kuu BaraStandings
# TEAM MP W D L PTS
1 Young Africans 23 16 6 1 54
2 Simba 23 15 7 1 52
3 Azam 23 12 10 1 46
4 Singida Black Stars 23 11 5 7 38
5 JKT Tanzania 23 9 9 5 36
6 Tabora United 23 9 7 7 34
7 Dodoma Jiji 23 8 8 7 32
8 Pamba Jiji 23 7 9 7 30
9 Mashujaa 23 5 11 7 26
10 Mtibwa Sugar 23 6 8 9 26
11 Coastal Union 23 6 7 10 25
12 Fountain Gate 23 7 4 12 25
13 Namungo 23 5 9 9 24
14 Mbeya City 23 5 6 12 21
15 Tanzania Prisons 23 4 5 14 17
16 KMC 23 2 3 18 9
# TEAM MP GS GC +/- PTS
1 Young Africans 23 52 8 +44 54
2 Simba 23 42 9 +33 52
3 Azam 23 33 9 +24 46
4 Singida Black Stars 23 30 23 +7 38
5 Tabora United 23 28 21 +7 34
6 JKT Tanzania 23 23 22 +1 36
7 Dodoma Jiji 23 22 23 -1 32
8 Pamba Jiji 23 22 24 -2 30
9 Coastal Union 23 22 29 -7 25
10 Mtibwa Sugar 23 20 32 -12 26
11 Mbeya City 23 18 34 -16 21
12 Namungo 23 17 24 -7 24
13 Fountain Gate 23 17 33 -16 25
14 KMC 23 13 39 -26 9
15 Tanzania Prisons 23 12 32 -20 17
16 Mashujaa 23 11 20 -9 26