Statistics / Football / Tanzania. Ligi kuu Bara / Pamba Jiji vs Tanzania Prisons

Pamba Jiji vs Tanzania Prisons Statistics & Analysis

May 26, 2026 - 11:00
2 1.45
3 1.25
xG Accuracy: 53%
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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 Over 2.5 (5 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Pamba Jiji Tanzania Prisons ✖ Incorrect
  • Correct Score Insights 1-0, 0-0, 1-1, 0-1, 2-0 2-3 ✖ Incorrect

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Ligi kuu Bara
  • Fixture: Pamba Jiji vs Tanzania Prisons
  • Kickoff: 2026-05-26 11:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Pamba Jiji 1.45 — Tanzania Prisons 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 79.7% · Implied: 60.5% · Probability edge: +19.2 pts · Est. EV: +21.9%
  • BTTS (model): Yes 20.3% · No 79.7%
  • Correct score (top bin): 1-0 (17.3%)

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

Early match state can move realised goals away from pre-kick projections.

Best Bet + Reason

Primary angle highlighted on the page: BTTS No.

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.

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.

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.

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.

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

June 08, 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 25 18 6 1 60
2 Simba 25 17 7 1 58
3 Azam 25 14 10 1 52
4 Singida Black Stars 25 12 5 8 41
5 JKT Tanzania 25 9 11 5 38
6 Tabora United 25 10 7 8 37
7 Pamba Jiji 25 8 9 8 33
8 Dodoma Jiji 25 8 9 8 33
9 Fountain Gate 25 8 5 12 29
10 Coastal Union 25 7 7 11 28
11 Mashujaa 25 5 12 8 27
12 Mtibwa Sugar 25 6 9 10 27
13 Namungo 25 5 10 10 25
14 Mbeya City 25 5 7 13 22
15 Tanzania Prisons 25 5 5 15 20
16 KMC 25 2 3 20 9
# TEAM MP GS GC +/- PTS
1 Young Africans 25 58 9 +49 60
2 Simba 25 45 10 +35 58
3 Azam 25 38 9 +29 52
4 Singida Black Stars 25 34 27 +7 41
5 Tabora United 25 31 24 +7 37
6 JKT Tanzania 25 27 26 +1 38
7 Pamba Jiji 25 25 27 -2 33
8 Coastal Union 25 24 31 -7 28
9 Dodoma Jiji 25 23 25 -2 33
10 Mtibwa Sugar 25 23 36 -13 27
11 Fountain Gate 25 21 36 -15 29
12 Mbeya City 25 20 39 -19 22
13 Namungo 25 19 28 -9 25
14 Tanzania Prisons 25 15 36 -21 20
15 KMC 25 13 43 -30 9
16 Mashujaa 25 12 22 -10 27