Statistics / Football / Mexico. Liga MX Femenil / Tijuana W vs Pachuca W

Tijuana W vs Pachuca W Statistics & Analysis

Tijuana W Tijuana W
Sep 06, 2026 - 01:06
3 1.18
1 1.42
xG Accuracy: 54%
Pachuca W Pachuca W
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Tracked markets vs full-time result

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Over 2.5 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Pachuca W Tijuana W ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-2, 1-0, 0-2 3-1 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Aug 31, 2026 · 06:37 UTC Snapshot ID: dp-6351421

Closing Odds 1.61
AI Fair Odds —
CLV +0.0%
Final Result Tijuana W win · Tijuana W 3–1 Pachuca W
Prediction ✖ Missed
Decision Grade F

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Market intelligence

Supporting read on how the prioritized closing feed moved versus the model — use after the Primary pick above.

Market briefing

Market remained largely stable before kickoff. No meaningful late implied-price shift was detected between PRE30 and PRE1 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Tijuana W (1X2), Draw (1X2), Under 2.5 goals meaningfully above what those closing snapshots implied — that gap is a static “model vs. price” read, not a late steam or chase story.

The model still exceeds closing implied on Under 2.5 goals by about 14.5 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Tijuana W (1X2) 29.6 18.8 +10.8
Draw (1X2) 29.4 23.6 +5.8
Pachuca W (1X2) 41.0 57.6 -16.7
Over 2.5 goals 48.2 62.7 -14.5
Under 2.5 goals 51.8 37.3 +14.5
What this means

In plain terms: the model lands near 51.8% on Under 2.5 goals, while the closing snapshot implied about 37.3%. The difference — about 14.5 percentage points — is the largest model-vs.-market gap highlighted on this page.

Quick definitions: “closing implied” is the probability for that outcome implied by the final captured odds (after a simple de-vig). “Gap (pp)” is the model percentage minus that implied value, in percentage points (pp).

Closing-window line move

Single prioritized bookmaker per snapshot (not all books). Capture path: PRE30 → PRE1 · Book: Pinnacle

Column tags in parentheses: Closing uses the first available snapshot in PRE1→PRE5→PRE10→PRE30; Early uses the first available in PRE30→PRE10→PRE5 that is not the same capture as Closing.

Detailed capture odds are folded below — movement was negligible on de-vig implied prices.

View full line-by-line capture table
Market Early (PRE30) Closing (PRE1) Implied Δ (pp)
Tijuana W (1X2) 4.93 4.93 0.0
Draw (1X2) 3.94 3.94 0.0
Pachuca W (1X2) 1.61 1.61 0.0
Over 2.5 goals 1.49 1.49 0.0
Under 2.5 goals 2.5 2.5 0.0

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Liga MX Femenil
  • Fixture: Tijuana W vs Pachuca W
  • Kickoff: 2026-09-06 01:06:00
  • 1X2 (model): Home 29.6% · Draw 29.4% · Away 41.0%
  • xG (showing): Tijuana W 1.18 — Pachuca W 1.42 (total xG ≈ 2.6)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.1% · No 45.9%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
  • BTTS (model): Yes 54.1% · No 45.9%
  • Correct score (top bin): 1-1 (12.4%)

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Prefer skipping to over-staking when the engine is honest about missing edge.

Historical Recommendation

Historical Decision: AI Value Alert - No Primary Bet

Outcome: Missed — Pre-match 1X2 lean did not match the full-time result.

Risk Factors Considered Before Kickoff

  • 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%).

Last Updated

September 28, 2026 (UTC)

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Liga MX Femenil Liga MX Femenil — Standings
# TEAM MP W D L PTS
1 Monterrey W 9 8 0 1 24
2 América W 8 7 1 0 22
3 Tigres UANL W 8 7 0 1 21
4 Juárez W 9 7 0 2 21
5 Guadalajara W 9 6 0 3 18
6 Toluca W 8 5 1 2 16
7 Atlético San Luis W 8 5 0 3 15
8 Pumas UNAM W 8 4 0 4 12
9 León W 8 4 0 4 12
10 Atlas W 9 3 3 3 12
11 Santos Laguna W 9 4 0 5 12
12 Cruz Azul W 9 4 0 5 12
13 Pachuca W 9 3 1 5 10
14 Atlante W 8 2 0 6 6
15 Querétaro W 9 2 0 7 6
16 Tijuana W 9 2 0 7 6
17 Puebla W 9 1 0 8 3
18 Necaxa W 8 0 0 8 0
# TEAM MP GS GC +/- PTS
1 América W 8 37 7 +30 22
2 Monterrey W 9 35 10 +25 24
3 Tigres UANL W 8 28 8 +20 21
4 Atlético San Luis W 8 21 15 +6 15
5 Guadalajara W 9 20 11 +9 18
6 Toluca W 8 19 15 +4 16
7 Pumas UNAM W 8 17 14 +3 12
8 León W 8 15 12 +3 12
9 Juárez W 9 14 6 +8 21
10 Pachuca W 9 13 13 0 10
11 Puebla W 9 13 38 -25 3
12 Santos Laguna W 9 12 20 -8 12
13 Tijuana W 9 12 24 -12 6
14 Cruz Azul W 9 11 21 -10 12
15 Atlas W 9 10 17 -7 12
16 Querétaro W 9 10 21 -11 6
17 Atlante W 8 6 12 -6 6
18 Necaxa W 8 3 32 -29 0
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