Statistics / Football / Tanzania. Ligi kuu Bara / Tanzania Prisons vs Fountain Gate

Tanzania Prisons vs Fountain Gate Statistics & Analysis

May 14, 2026 - 11:00
1 1.45
0 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 Tanzania Prisons Tanzania Prisons ✔ Correct
  • Correct Score Insights 0-1 1-0 ✖ Incorrect

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Ligi kuu Bara
  • Fixture: Tanzania Prisons vs Fountain Gate
  • Kickoff: 2026-05-13 13:15:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Tanzania Prisons 1.45 — Fountain Gate 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 80.2% · Implied: 56.0% · Probability edge: +24.2 pts · Est. EV: +32.3%
  • BTTS (model): Yes 19.8% · No 80.2%
  • Correct score (top bin): 0-1 (13.4%)

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.

Best Bet + Reason

The engine’s headline primary is: BTTS No.

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

No pick is a guarantee; variance is especially large in scoreline markets.

FAQ

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.

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.

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.

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