Statistics / Football / Rwanda. National Soccer League / Gorilla vs AS Kigali

Gorilla vs AS Kigali Statistics & Analysis

Gorilla Gorilla
May 06, 2026 - 13:00
2 1.45
1 1.25
xG Accuracy: 80%
AS Kigali AS Kigali
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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 (0 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 Gorilla Draw ✖ Incorrect
  • Correct Score Insights 0-0 0-0 ✔ Correct

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: National Soccer League
  • Fixture: Gorilla vs AS Kigali
  • Kickoff: 2026-05-06 13:00:00
  • 1X2 (model): Home 35.0% · Draw 35.0% · Away 30.0%
  • xG (showing): Gorilla 1.45 — AS Kigali 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 71.7% · Implied: 62.4% · Probability edge: +9.3 pts · Est. EV: +7.5%
  • BTTS (model): Yes 36.1% · No 63.9%
  • Correct score (top bin): 0-0 (15.7%)

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

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

Best Bet + Reason

The engine’s headline primary is: Under 2.5 goals.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

When several markets sit near +EV, keep stakes small — correlation means edges do not add cleanly.

FAQ

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.

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.

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.

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
National Soccer League National Soccer League — Standings
# TEAM MP W D L PTS
1 Al Hilal Omdurman 32 23 5 4 74
2 APR 31 16 11 4 59
3 Al Merreikh 30 16 10 4 58
4 Rayon Sports 32 13 13 6 52
5 Kiyovu Sports 32 13 12 7 51
6 Police 32 11 15 6 48
7 Mukura 32 12 10 10 46
8 Marines 32 11 8 13 41
9 Bugesera 32 11 8 13 41
10 Musanze 31 10 9 12 39
11 Gorilla 32 9 10 13 37
12 Gasogi United 32 8 11 13 35
13 Gicumbi 32 9 8 15 35
14 AS Kigali 32 7 11 14 32
15 Etincelles 32 5 16 11 31
16 Amagaju 31 8 7 16 31
17 Muhanga 32 7 7 18 28
18 Rutsiro 31 5 11 15 26
# TEAM MP GS GC +/- PTS
1 Al Hilal Omdurman 32 72 22 +50 74
2 APR 31 43 27 +16 59
3 Marines 32 43 40 +3 41
4 Al Merreikh 30 38 17 +21 58
5 Rayon Sports 32 37 29 +8 52
6 Gicumbi 32 35 50 -15 35
7 Mukura 32 34 35 -1 46
8 Kiyovu Sports 32 33 20 +13 51
9 Musanze 31 33 32 +1 39
10 Bugesera 32 32 37 -5 41
11 Police 32 28 19 +9 48
12 Gorilla 32 28 37 -9 37
13 Rutsiro 31 28 41 -13 26
14 Gasogi United 32 27 40 -13 35
15 Etincelles 32 26 39 -13 31
16 AS Kigali 32 24 36 -12 32
17 Muhanga 32 21 43 -22 28
18 Amagaju 31 18 36 -18 31
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