Stalemate again as Shimizu S-pulse and Tokyo tie for the 2nd consecutive match. Conversely, Solid: FC Tokyo haven't dropped all points in 4 outings.
Wed, Sep 2, 2026 10:00 (UTC)
Last 10 games
Home team Side
Away team Side
These symbols () are Sorted by Newest.
Shimizu S-pulse (Fact Index 3.45):
Expected Win % is 29%, compared to a 27% actual win rate for identical index values.
Nevertheless, they maintain an actual win rate of 34% in this event.
Tokyo (Fact Index 2.13):
Expected Win % is 47%, compared to a 33% actual win rate for identical index values.
However, they are currently recording a 33% actual win rate in this tournament.
Shimizu S-pulse:
T : 0.250 (0.193 / ▲0.057)
P : 0.250 (0.193 / ▲0.057)
Tokyo:
T : 0.500 (0.543 / ▼0.043)
P : 0.500 (0.543 / ▼0.043)
* Note Abbr. : Season Win% ( Expected Win% / Season W% - Expected Win%)
** Abbr. T: Season, H: Home, A: Away, P: Power Ranking (Last 6)
Note that the limited sample size makes it difficult to establish this as a definitive long-term trend.
Results of the same FACT INDEX : 6 Game(s) In real-time
The Favorite vs Underdog of the same FACT INDEX : 3 Game(s) in Average Odds
Results of the same FACT INDEX : 30 Game(s) In real-time
The Favorite vs Underdog of the same FACT INDEX : 24 Game(s) in Average Odds
Model B is an experimental predictive simulation.
Current: ver. B.4 / Data Completion Rate : 52.4%
Fact Index - Prediction Variance
Data Source: Oddsportal
Please feel free to research player deployments or other detailed matters on your own; a brief search will yield a wealth of information.
Fact Index - Average Odds Variance
Odds Trend: 3 game(s)
Based on Away team = 2.0 (46%) Trend: 18 game(s)
Odds Trend: 30 game(s)
Based on Away team = 2.0 (46%) Trend: 30 game(s)
Voting has closed.
Last 3:
J1 League 2026-09-12 Gamba Osaka 0 - 2 Tokyo
J1 League 2026-09-06 Tokyo 2 - 0 Kyoto Sanga
J1 League 2026-08-29 Nagasaki 0 - 3 Tokyo
Next 3:
J1 League 2026-09-19 Tokyo - Nagoya Grampus
Last 20 games
HOME :
AWAY :
WaveFlow Sports Lab's FactIndex and metrics are built on real-time match data. But remember, we do not account for starting lineups, injuries, player absences, or weather. Since we track data by specific years and leagues, you might find less data at the beginning of a season. Please use this guide as a supporting tool for your predictions—after all, anything can happen in sports!
WaveFlow SportsLab assumes no responsibility or liability for the accuracy of any statistics or predictions provided, and offers no warranties of any kind.
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Disclaimer: Metrics are based on historical match data but exclude lineups, injuries, and weather. Data may be limited early in the season. All content is for reference only. In sports, the outcome is always unpredictable.
WaveFlow SportsLab assumes no responsibility or liability for the accuracy of any statistics or predictions provided, and offers no warranties of any kind.
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