Competition overview
Bundesliga
Explore this season's standings, upcoming fixtures and published pre-match analysis.
Season
2026
On this page
Fixtures & standings
Tracked matches
697
Fixtures captured inside the current competition scope.
Prediction accuracy
40%
Settled hit rate from the verified archive only.
Active predictions
6
Upcoming or live league fixtures currently covered by logged outputs.
Featured fixtures
Active competition fixtures ranked by confidence, edge, and current market interpretation.
Regular Season - 9
2026-11-07 03:30
Upcoming
Hamburger SV
Borussia MönchengladbachModel output
Borussia Mönchengladbach to win
38%
Low convictionMarket aligned
Regular Season - 9
2026-11-07 22:30
Upcoming
Borussia Dortmund
SV ElversbergModel output
Borussia Dortmund to win
83%
Strong confidenceMarket aligned
Regular Season - 9
2026-11-07 22:30
Upcoming
RB Leipzig
FC AugsburgModel output
RB Leipzig to win
81%
Strong confidenceMarket aligned
Bundesliga intelligence snapshot
SportXG ranks current league signals using verified standings data and stored prediction-market gaps. xG-only layers stay hidden until a stable league feed is available.
113 logged predictions40 settled
League environment
These league-wide signals describe the scoring climate, confidence climate, and disagreement profile around the current competition feed.
xG trend status
Expected goals environment
2.67 projected goals per fixture
Stable league-wide xG feeds are not available here, so SportXG uses stored projected scorelines as a proxy. Current projected goals sit at 2.67 per fixture versus — actual goals per match, a — goal gap.
Historical scoring tendencies
Scoring environment
—
Draws land at —, over-2.5 outcomes at 60%, and clean-sheet finishes at — across the currently stored competition record.
Model confidence environment
Model confidence environment
65%
The average selected probability is 65%, while 44% of tracked fixtures currently fall into the high-confidence bucket.
Market disagreement environment
Market disagreement environment
—
Average model-vs-market disagreement currently runs at —, with 0% of tracked fixtures clearing the strong-disagreement threshold.
Attack and defense leaders
These table-driven leaders help frame which clubs are shaping the league's scoring environment most aggressively right now.
Strongest attack
Unavailable
—
Not enough stable league evidence is available to rank this signal yet.
Strongest defense
Unavailable
—
Not enough stable league evidence is available to rank this signal yet.
Match of the week
Market aligned
Borussia Dortmund vs SV Elversberg
Highest conviction active fixture in the current league feed.
Strong confidenceLow volatility
Home83%
Draw13%
Away4%
Model vs market
Model
83%
Market
—
Edge
—
No odds snapshot
Borussia Dortmund to win
Biggest model disagreement
No fixtures in this editorial bucket for the current filters.
High volatility fixture
Market aligned
Hamburger SV vs Borussia Mönchengladbach
Tight probability separation with elevated uncertainty.
Low convictionHigh volatility
Home35%
Draw27%
Away38%
Model vs market
Model
38%
Market
—
Edge
—
No odds snapshot
Borussia Mönchengladbach to win
Key model insights
League-level watchlists and narratives prioritize what matters most, rather than stacking generic standings and fixtures equally.
Watchlist team
Bayern München
No recent watchlist signal is available from the current table and prediction archive.
Strongest home edge
RB Leipzig
2.25 point home-vs-away pace gap.
Editorial framing
RB Leipzig currently shows the strongest home advantage in the table data, outperforming its away points pace by 2.25 points per game.
Intelligence standings
This table stays grounded in official standings while layering model strength, volatility, and home-edge signals on top.
| # | Team | Played | GF | GA | GD | Points | Form | Model strength | Volatility | Avg edge | Home edge |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility32/100 | — | +0.50 | |
| 2 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility29/100 | — | +0.50 | |
| 3 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility30/100 | — | +2.25 | |
| 4 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility56/100 | — | -0.20 | |
| 5 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility— | — | +0.75 | |
| 6 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility— | — | +1.25 | |
| 7 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility— | — | +0.50 | |
| 8 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility96/100 | — | +0.75 | |
| 9 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility30/100 | — | +0.20 | |
| 10 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility32/100 | — | -2.00 | |
| 11 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility— | — | +0.87 | |
| 12 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility97/100 | — | -0.50 | |
| 13 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility97/100 | — | +1.40 | |
| 14 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility— | — | +1.75 | |
| 15 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility56/100 | — | +1.25 | |
| 16 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility— | — | -0.50 | |
| 17 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility29/100 | — | +1.25 | |
| 18 | 0 | 0 | 0 | 0 | 0 | WDL | Strength36/100 | Volatility96/100 | — | +0.75 |
