Foresportia Elo
1587J1 League rank : 2nd
Kashiwa Reysol
Foresportia analyses Kashiwa Reysol using its match data and proprietary models: Elo level, recent form, probabilities, observed reliability and verifiable market signals.
1X2 entropy
1.54Lower = easier to readPoints volatility
1.20Standard deviation over 5 matchesRecent form
2.40Points per match over 5 matchesModel confidence
45.8%Average over 10 predictions1. How Foresportia evaluates Kashiwa Reysol
Summary of indicators actually available in Foresportia data.
2. Next match
Kashiwa ReysolElo : 1566
Yokohama MarinosElo : 1524
1X2 probabilities (Foresportia model)
Kashiwa Reysol 37%Draw 28%Yokohama Marinos 35%
3. Prediction reliability for Kashiwa Reysol
Data updated on 06 September 2026
Reliability trendCumulative monthly history
Insufficient sample| Cumulative monthly history | Profile | Reliability | Volume |
|---|---|---|---|
| 2025-02 | Risk | Insufficient sample | 3 |
| 2025-03 | Risk | Insufficient sample | 7 |
| 2025-04 | Risk | 30.8% | 13 |
| 2025-05 | Risk | 31.6% | 19 |
| 2025-06 | Risk | 36.4% | 22 |
| 2025-07 | Risk | 37.5% | 24 |
| 2025-08 | Risk | 39.3% | 28 |
| 2025-09 | Risk | 37.5% | 32 |
| 2025-10 | Risk | 38.2% | 34 |
| 2025-11 | Risk | 40.0% | 35 |
| 2025-12 | Risk | 38.9% | 36 |
| 2026-03 | Risk | 37.8% | 37 |
| 2026-04 | Risk | 40.5% | 42 |
| 2026-05 | Risk | 40.4% | 47 |
| 2026-06 | Risk | 39.6% | 48 |
| 2026-08 | Risk | 43.1% | 51 |
| 2026-09 | Risk | 44.2% | 52 |
| 2025-02 | Correct and above | Insufficient sample | 0 |
| 2025-03 | Correct and above | Insufficient sample | 0 |
| 2025-04 | Correct and above | Insufficient sample | 0 |
| 2025-05 | Correct and above | Insufficient sample | 0 |
| 2025-06 | Correct and above | Insufficient sample | 0 |
| 2025-07 | Correct and above | Insufficient sample | 0 |
| 2025-08 | Correct and above | Insufficient sample | 0 |
| 2025-09 | Correct and above | Insufficient sample | 0 |
| 2025-10 | Correct and above | Insufficient sample | 1 |
| 2025-11 | Correct and above | Insufficient sample | 2 |
| 2025-12 | Correct and above | Insufficient sample | 2 |
| 2026-03 | Correct and above | Insufficient sample | 3 |
| 2026-04 | Correct and above | Insufficient sample | 3 |
| 2026-05 | Correct and above | Insufficient sample | 4 |
| 2026-06 | Correct and above | Insufficient sample | 4 |
| 2026-08 | Correct and above | Insufficient sample | 5 |
| 2026-09 | Correct and above | Insufficient sample | 5 |
| 2025-02 | Stable and above | Insufficient sample | 0 |
| 2025-03 | Stable and above | Insufficient sample | 0 |
| 2025-04 | Stable and above | Insufficient sample | 0 |
| 2025-05 | Stable and above | Insufficient sample | 0 |
| 2025-06 | Stable and above | Insufficient sample | 0 |
| 2025-07 | Stable and above | Insufficient sample | 0 |
| 2025-08 | Stable and above | Insufficient sample | 0 |
| 2025-09 | Stable and above | Insufficient sample | 0 |
| 2025-10 | Stable and above | Insufficient sample | 0 |
| 2025-11 | Stable and above | Insufficient sample | 0 |
| 2025-12 | Stable and above | Insufficient sample | 0 |
| 2026-03 | Stable and above | Insufficient sample | 0 |
| 2026-04 | Stable and above | Insufficient sample | 0 |
| 2026-05 | Stable and above | Insufficient sample | 0 |
| 2026-06 | Stable and above | Insufficient sample | 0 |
| 2026-08 | Stable and above | Insufficient sample | 0 |
| 2026-09 | Stable and above | Insufficient sample | 0 |
| 2025-02 | Ultra stable | Insufficient sample | 0 |
| 2025-03 | Ultra stable | Insufficient sample | 0 |
| 2025-04 | Ultra stable | Insufficient sample | 0 |
| 2025-05 | Ultra stable | Insufficient sample | 0 |
| 2025-06 | Ultra stable | Insufficient sample | 0 |
| 2025-07 | Ultra stable | Insufficient sample | 0 |
| 2025-08 | Ultra stable | Insufficient sample | 0 |
| 2025-09 | Ultra stable | Insufficient sample | 0 |
| 2025-10 | Ultra stable | Insufficient sample | 0 |
| 2025-11 | Ultra stable | Insufficient sample | 0 |
| 2025-12 | Ultra stable | Insufficient sample | 0 |
| 2026-03 | Ultra stable | Insufficient sample | 0 |
| 2026-04 | Ultra stable | Insufficient sample | 0 |
| 2026-05 | Ultra stable | Insufficient sample | 0 |
| 2026-06 | Ultra stable | Insufficient sample | 0 |
| 2026-08 | Ultra stable | Insufficient sample | 0 |
| 2026-09 | Ultra stable | Insufficient sample | 0 |
4. Predictive profile for Kashiwa Reysol
ContextObserved measureReading
Home performance2.03 pts/matchHigher observed return
Away performance1.68 pts/matchLower observed return
5. Statistical markers for Kashiwa Reysol
Team values from Foresportia sources, without a reconstructed league average.
History: 57 verified matches
6. Market signals for Kashiwa Reysol
MarketAverage probabilityReliabilityVolumeReading
Double chance 1270.5%95.0%20Major, well-documented signal
Home draw no bet64.2%63.6%11Recurring signal
Double chance 1X67.7%60.0%20Recurring signal
Away draw no bet58.7%55.6%9Promising signal, limited sample
7. Model dynamics & analysis
Foresportia Elo trendTracks the team’s relative level as matches are played.
Kashiwa Reysol
Average model confidenceShows how the model’s average certainty changes across matches.
Kashiwa Reysol
xG differential trendCompares expected goals created and conceded to track the balance of chances.
PositiveNegative
Model calibrationCompares published probabilities with the rates actually observed.
Observed ratePerfect
League-position trendTracks the team’s league position throughout the season.
Kashiwa Reysol
Goals scored / concededCompares goals scored and conceded using a five-match rolling average.
Goals scored / match (5)Goals conceded / match (5)
Points per matchTracks points earned per match using a five-match rolling average.
Kashiwa Reysol
8. Foresportia analysis
For Foresportia, Kashiwa Reysol mainly combines stronger recent control and a more reliable defensive base. This page also tracks ranking, Elo evolution, goal trends and the market signals Foresportia finds most useful.
Kashiwa Reysol is going through a strong control sequence, with 2.40 points per match over the last five matches and an average xG delta of 0.75.
The next detected match is Kashiwa Reysol vs Yokohama Marinos on . The leading 1X2 read currently points to “Home win” around 37%.
Continue exploring
Upcoming matches, competition, other teams and verifiable history.
9. Kashiwa Reysol FAQ
What is the next match for Kashiwa Reysol on Foresportia?
This page shows Kashiwa Reysol's confirmed next match with the enriched prediction probabilities that are currently available.
How should you read Kashiwa Reysol's ranking and Elo?
This page includes dedicated charts for Kashiwa Reysol's ranking and Elo trends, with season separators to make the evolution easier to read.
What does the strongest picks block mean for Kashiwa Reysol?
It highlights the markets that performed best in the available history for Kashiwa Reysol, together with sample size, hit rate and average probability.
Kashiwa Reysol: AI analysis, predictions and Foresportia signals
For Foresportia, Kashiwa Reysol mainly combines stronger recent control and a more reliable defensive base. This page also tracks ranking, Elo evolution, goal trends and the market signals Foresportia finds most useful.
Kashiwa Reysol is going through a strong control sequence, with 2.40 points per match over the last five matches and an average xG delta of 0.75.
The next detected match is Kashiwa Reysol vs Yokohama Marinos on . The leading 1X2 read currently points to “Home win” around 37%.