Predictions / Football / Japan. J1 League / Tokyo Verdy vs Kashiwa Reysol

Prediction Audit: Tokyo Verdy vs Kashiwa Reysol Prediction, Odds & AI Betting Tips

Tokyo Verdy Tokyo Verdy
Aug 14, 2026 - 10:00
1 0.72
3 1.28
xG Accuracy: 58%
Kashiwa Reysol Kashiwa Reysol

AI correctly predicted the Kashiwa Reysol win.

The match finished 1–3, validating the model's directional assessment.

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 Over 2.5 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Kashiwa Reysol Kashiwa Reysol ✔ Correct
  • Correct Score Insights 0-1, 0-0, 1-1, 0-2, 1-0 1-3 ✖ Incorrect

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: Tokyo Verdy -3.9 pp

Outcome Model Closing Market Difference Signal
Tokyo Verdy 19.3% 23.2% -3.9 pp Aligned
Draw 32.4% 28.7% +3.7 pp Aligned
Kashiwa Reysol 48.2% 48.0% +0.2 pp Aligned

The model and closing market are broadly aligned, with probability differences below 5 percentage points.

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 model's directional lean matched the result (Kashiwa Reysol win 1–3).

Market Assessment

The market and model are broadly aligned. Any small pricing gap likely reflects rounding or bookmaker margin, not a structural disagreement.

  • Current pricing remains close to the model baseline.

Post Match Insights

What worked

  • Kashiwa Reysol attacking xG significantly stronger (1.28 vs 0.72)

What failed

  • Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (4 goals)

Market lesson

The model's directional lean matched the full-time result (Kashiwa Reysol win 1–3).

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Prediction Timeline

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

  1. Aug 14, 2026 · 09:59 UTC Forecast generated
    • Model 1X2 · Tokyo Verdy 19.3% · Draw 32.4% · Kashiwa Reysol 48.2%
    • xG · Tokyo Verdy 0.72 — Kashiwa Reysol 1.28
  2. Aug 14, 2026 · 09:30 UTC Opening odds snapshot PRE30
    • 1X2 odds · Tokyo Verdy 4.16 · Draw 3.36 · Kashiwa Reysol 2.01
    • Implied 1X2 · Tokyo Verdy 23.2% · Draw 28.7% · Kashiwa Reysol 48.0%
    • Bookmaker · Pinnacle
  3. Aug 14, 2026 · 09:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Tokyo Verdy 4.16 · Draw 3.36 · Kashiwa Reysol 2.01
    • Implied 1X2 · Tokyo Verdy 23.2% · Draw 28.7% · Kashiwa Reysol 48.0%
    • Bookmaker · Pinnacle
  4. Aug 14, 2026 · 10:00 UTC Kickoff
  5. FT Full-time result Kashiwa Reysol win · 1–3
  6. FT Prediction validated Directional lean matched full-time result
  7. Archived Prediction review

Historical Snapshot

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

Historical verdict: Observe
Historical Decision No Primary Bet
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 77/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 80/100
Betting Confidence 80/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 08, 2026 · 01:02 UTC Snapshot ID: dp-3225554

Closing Odds 4.16
AI Fair Odds —
CLV Pending
Final Result Kashiwa Reysol win · Tokyo Verdy 1–3 Kashiwa Reysol
Prediction ✔ Correct
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: J1 League
  • Fixture: Tokyo Verdy vs Kashiwa Reysol
  • Kickoff: 2026-08-14 10:00:00
  • 1X2 (model): Home 19.3% · Draw 32.4% · Away 48.2%
  • xG (showing): Tokyo Verdy 0.72 — Kashiwa Reysol 1.28 (total xG ≈ 2.0)
  • Value headline: None (actionable) — best tracked EV is about +0.1%, still below the +2.0% minimum for a headline / default stake (no default bet).
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 67.7% · Over 2.5 32.3%); BTTS No (Yes 38.7% · No 61.3%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
  • BTTS (model): Yes 38.7% · No 61.3%
  • Correct score (top bin): 0-1 (17.3%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

Historical Recommendation

Historical Decision: No Primary Bet

Outcome: Validated — Pre-match lean validated against 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 29, 2026 (UTC)

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J1 League J1 League — Standings
# TEAM MP W D L PTS
1 Vissel Kobe 8 6 1 1 19
2 Kashiwa Reysol 8 6 0 2 18
3 Sanfrecce Hiroshima 8 5 2 1 17
4 Machida Zelvia 8 5 2 1 17
5 FC Tokyo 8 5 2 1 17
6 Yokohama F. Marinos 8 4 2 2 14
7 Kawasaki Frontale 8 3 4 1 13
8 Kashima 8 4 1 3 13
9 Fagiano Okayama 8 4 1 3 13
10 Urawa 8 4 0 4 12
11 Cerezo Osaka 8 3 2 3 11
12 Shimizu S-pulse 8 3 1 4 10
13 Mito Hollyhock 8 2 3 3 9
14 Kyoto Sanga 8 2 2 4 8
15 V-varen Nagasaki 8 2 2 4 8
16 Gamba Osaka 8 1 3 4 6
17 Nagoya Grampus 8 2 0 6 6
18 Avispa Fukuoka 8 1 1 6 4
19 Tokyo Verdy 8 0 4 4 4
20 JEF United Chiba 8 1 1 6 4
# TEAM MP GS GC +/- PTS
1 Machida Zelvia 8 21 10 +11 17
2 Sanfrecce Hiroshima 8 20 6 +14 17
3 Kashiwa Reysol 8 17 12 +5 18
4 Kashima 8 17 16 +1 13
5 Kawasaki Frontale 8 16 12 +4 13
6 Urawa 8 16 18 -2 12
7 FC Tokyo 8 14 8 +6 17
8 Yokohama F. Marinos 8 13 9 +4 14
9 Vissel Kobe 8 12 5 +7 19
10 Fagiano Okayama 8 11 10 +1 13
11 Mito Hollyhock 8 11 11 0 9
12 Kyoto Sanga 8 11 15 -4 8
13 V-varen Nagasaki 8 10 15 -5 8
14 Avispa Fukuoka 8 9 12 -3 4
15 Gamba Osaka 8 8 14 -6 6
16 Cerezo Osaka 8 7 12 -5 11
17 Nagoya Grampus 8 7 14 -7 6
18 JEF United Chiba 8 7 18 -11 4
19 Shimizu S-pulse 8 6 8 -2 10
20 Tokyo Verdy 8 4 12 -8 4
# TEAM MP xG xGC +/- PTS
1 V-varen Nagasaki 8 3.7 1.7 +2.0 8
2 Sanfrecce Hiroshima 8 2.2 0.6 +1.6 17
3 Yokohama F. Marinos 8 3.0 1.5 +1.5 14
4 Vissel Kobe 8 2.3 0.9 +1.4 19
5 FC Tokyo 8 3.0 1.7 +1.3 17
6 Cerezo Osaka 8 1.8 1.1 +0.7 11
7 Urawa 8 1.9 1.4 +0.5 12
8 Fagiano Okayama 8 1.3 0.8 +0.5 13
9 Mito Hollyhock 8 1.6 1.3 +0.3 9
10 Kashima 8 1.3 1.6 -0.3 13
11 Avispa Fukuoka 8 1.4 1.9 -0.5 4
12 JEF United Chiba 8 0.8 1.3 -0.5 4
13 Kashiwa Reysol 8 1.1 1.8 -0.7 18
14 Shimizu S-pulse 8 1.7 3.0 -1.3 10
15 Tokyo Verdy 8 0.9 2.3 -1.4 4
16 Kyoto Sanga 8 1.5 3.0 -1.5 8
17 Nagoya Grampus 8 0.6 2.2 -1.6 6
18 Gamba Osaka 8 1.7 3.7 -2.0 6
19 Machida Zelvia 8 — — — 17
20 Kawasaki Frontale 8 — — — 13