Predictions / Football / China. Super League / Wuhan Three Towns vs Tianjin Teda

Prediction Audit: Wuhan Three Towns vs Tianjin Teda Prediction, Odds & AI Betting Tips

Aug 22, 2026 - 11:00
0 1.01
0 1.46
xG Accuracy: 51%

The model missed the final outcome (Draw 0–0).

The model had projected Tianjin Teda at 43.0%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade F

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

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Under 2.5 (0 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Tianjin Teda Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-2, 0-2, 1-0 0-0 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Wuhan Three Towns higher than the statistical model.

Largest probability gap: Wuhan Three Towns -15.6 pp

Outcome Model Closing Market Difference Signal
Wuhan Three Towns 27.6% 43.2% -15.6 pp Market Higher
Draw 29.4% 26.0% +3.5 pp Aligned
Tianjin Teda 43.0% 30.9% +12.1 pp Model Edge

The closing market estimates Wuhan Three Towns's win probability at 43.2%, compared with the model's estimate of 27.6%, a difference of 15.6 percentage points. This highlights a disagreement between the model and market consensus, without indicating which view is ultimately correct.

Model probabilities are generated from the statistical xG model using a Poisson distribution. Closing market probabilities are derived from consensus closing 1X2 odds after margin removal. Values represent implied probabilities rather than betting recommendations. Closing snapshot: PRE1.

After full time, the result was Draw 0–0.

Market Assessment

The market is materially more optimistic about Wuhan Three Towns than the current fair estimate.

  • Investors may be incorporating information not fully reflected in the baseline model.
  • Tournament-specific context can shift market pricing.

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • 1X2: model leaned Tianjin Teda; match finished Draw

Market lesson

The closing market differed from the model on Tianjin Teda by 15.6 percentage points (58.6% vs model 43.0%) — in this case the market view proved closer.

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Prediction Timeline

How this prediction moved from forecast to full-time review.

  1. Aug 22, 2026 · 19:18 UTC Forecast generated
    • Model 1X2 · Wuhan Three Towns 27.6% · Draw 29.4% · Tianjin Teda 42.9%
    • xG · Wuhan Three Towns 1.01 — Tianjin Teda 1.46
  2. Aug 22, 2026 · 10:32 UTC Opening odds snapshot PRE30
    • 1X2 odds · Wuhan Three Towns 2.23 · Draw 3.71 · Tianjin Teda 3.12
    • Implied 1X2 · Wuhan Three Towns 43.2% · Draw 26.0% · Tianjin Teda 30.9%
    • Bookmaker · Pinnacle
  3. Aug 22, 2026 · 11:00 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Wuhan Three Towns 2.23 · Draw 3.71 · Tianjin Teda 3.12
    • Implied 1X2 · Wuhan Three Towns 43.2% · Draw 26.0% · Tianjin Teda 30.9%
    • Bookmaker · Pinnacle
  4. Aug 22, 2026 · 11:00 UTC Kickoff
  5. FT Full-time result Draw · 0–0
  6. FT Prediction missed 1X2 lean did not match full-time result
  7. Archived Prediction review

Historical Snapshot

Frozen at kickoff — the model output as it stood before the match started.

Historical verdict: Monitor
Historical Decision Monitor
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 55/100 · Moderate
  • Validation: Warning
  • Large market gap (16 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 7/100
Monitoring Confidence 19/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 16, 2026 · 01:14 UTC Snapshot ID: dp-4214796

Closing Odds 2.23
AI Fair Odds —
CLV Pending
Final Result Draw · Wuhan Three Towns 0–0 Tianjin Teda
Prediction ✖ Missed
Decision Grade F

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Review FAQ

How accurate was the prediction?
This page grades directional markets (1X2, Over/Under 2.5, BTTS) against the full-time result. The prediction grade reflects how many of those tracked markets matched reality.
What does xG Accuracy measure?
xG Accuracy compares the model's pre-match expected-goals profile to the actual scoreline — not whether every market hit. A strong directional review can coexist with a moderate xG accuracy score.
Why wasn't the exact score predicted?
Correct-score outcomes are low-probability tails even when the model reads the match profile well. We highlight top score bins for context; missing the exact line does not invalidate a directional review.
Does this improve the AI record?
Each finished match is logged in our validation pipeline. Aggregated hit rates and CLV studies are published separately — this page is the per-match audit trail.

Predictions are for informational purposes only. Always gamble responsibly and within your limits. Past performance does not guarantee future results.

AI match briefing

AI Match Summary

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: Super League
  • Fixture: Wuhan Three Towns vs Tianjin Teda
  • Kickoff: 2026-08-22 11:00:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Wuhan Three Towns 1.01 — Tianjin Teda 1.46 (total xG ≈ 2.47)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • Structural leans (not bets): See the Over/Under and BTTS cards for any directional lean text.
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

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: Monitor

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 30, 2026 (UTC)

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Back to Predictions
Super League Super League — Standings
# TEAM MP W D L PTS
1 Chengdu Better City 26 15 7 4 52
2 Dalian Zhixing 26 12 4 10 40
3 Beijing Guoan 26 11 10 5 38
4 Yunnan Yukun 26 11 5 10 38
5 Qingdao Youth Island 26 8 14 4 38
6 Shandong Luneng 26 13 4 9 37
7 SHANGHAI SIPG 26 10 8 8 33
8 Shanghai Shenhua 26 12 5 9 31
9 Chongqing Tongliang Long 26 7 10 9 31
10 Hangzhou Greentown 26 10 6 10 31
11 Sichuan Jiuniu 26 8 4 14 28
12 Henan Jianye 26 8 9 9 27
13 Shenyang Urban 26 7 4 15 25
14 Tianjin Teda 26 9 8 9 25
15 Wuhan Three Towns 26 5 11 10 21
16 Qingdao Jonoon 26 6 3 17 14
# TEAM MP GS GC +/- PTS
1 Yunnan Yukun 26 54 51 +3 38
2 Shanghai Shenhua 26 52 46 +6 31
3 Chengdu Better City 26 51 30 +21 52
4 Beijing Guoan 26 49 33 +16 38
5 Shandong Luneng 26 46 43 +3 37
6 Hangzhou Greentown 26 45 43 +2 31
7 SHANGHAI SIPG 26 40 33 +7 33
8 Wuhan Three Towns 26 39 46 -7 21
9 Dalian Zhixing 26 38 42 -4 40
10 Tianjin Teda 26 36 32 +4 25
11 Sichuan Jiuniu 26 34 45 -11 28
12 Shenyang Urban 26 34 47 -13 25
13 Qingdao Jonoon 26 34 53 -19 14
14 Henan Jianye 26 33 35 -2 27
15 Qingdao Youth Island 26 31 32 -1 38
16 Chongqing Tongliang Long 26 27 32 -5 31
# TEAM MP xG xGC +/- PTS
1 Beijing Guoan 26 4.4 0.1 +4.3 38
2 Shenyang Urban 26 2.8 0.8 +2.0 25
3 Tianjin Teda 26 1.5 0.6 +0.9 25
4 Chengdu Better City 26 2.1 1.5 +0.6 52
5 Qingdao Youth Island 26 1.8 1.2 +0.6 38
6 Yunnan Yukun 26 2.6 2.3 +0.3 38
7 Dalian Zhixing 26 2.3 2.0 +0.3 40
8 Hangzhou Greentown 26 1.7 1.5 +0.2 31
9 Shanghai Shenhua 26 1.5 1.7 -0.2 31
10 Wuhan Three Towns 26 2.0 2.3 -0.3 21
11 Qingdao Jonoon 26 1.5 2.1 -0.6 14
12 SHANGHAI SIPG 26 1.2 1.8 -0.6 33
13 Sichuan Jiuniu 26 0.6 1.5 -0.9 28
14 Chongqing Tongliang Long 26 0.8 2.8 -2.0 31
15 Shandong Luneng 26 2.4 7.0 -4.6 37
16 Henan Jianye 26 — — — 27