Footyntel.

Bundesliga 2026/27 — Table & Season Projection

Simulated title, top 4 and relegation / play-off probabilities for every club.

Updated 28 October 2026 · 243 fixtures remaining · model projection, not a prediction

Matchday 8 of 34

Title raceRelegation battleAll fixtures & predictions

⚽ Top scorer Niclas FüllkrugBremen8 goals🅰️ Top assists Antonio NusaRB Leipzig5 assists
⚙️ These percentages come from running the rest of the season 50,000 times with a Poisson goals model. Early in the season the numbers are wide and move a lot — treat them as informed estimates, not forecasts.

After 8 matchdays of the Bundesliga 2026/27 season, Bayern lead on 17 points. Across 50,000 simulated seasons, Bayern are clear favourites for the title. The top three by title probability are Bayern (84.7%), Dortmund (11.2%), RB Leipzig (2%). Relegation risk is highest for Union Berlin (64.1%), M'gladbach (60.7%), HSV (43.6%), 1. FC Köln (27.3%). It is still early in the season, so these probabilities are wide and will sharpen with more matches.

#TeamPPtsGDTitleTop 4Relegation
1– BayernWWDWW 717+19
84.7
99.8
0
2– DortmundWWDDW 717+8
11.2
90.1
<1
3– FreiburgWDWLL 713+7
<1
34.3
0.8
4– LeverkusenDWWWL 713+4
1.3
51.5
<1
5▲2 RB LeipzigWLWLW 712+9
2
59.2
<1
6▲2 BremenDWDDW 712+1
<1
8.5
6.4
7▼2 MainzLWLWL 710+3
<1
8.8
6.1
8▼2 ElversbergLDLWL 710-3
<1
5.7
10
9▲1 AugsburgDLDLD 79+4
<1
9.7
6.2
10▲4 HoffenheimWLLWW 790
<1
14.3
3.8
11▼2 HSVLWWWL 79-10
0
<1
43.6
12– 1. FC KölnDLWLD 78-3
<1
1.2
27.3
13▲3 SC PaderbornLWLDW 78-3
<1
2
19.3
14▼3 FrankfurtWDLWL 78-7
<1
2.4
21.1
15▼2 StuttgartLLWLL 76-3
<1
10.8
6.2
16▼1 SchalkeWDLLD 76-3
0
1.2
23.9
17– Union BerlinLLWDD 76-12
0
<1
64.1
18– M'gladbachLLLLW 73-11
0
<1
60.7
Title %Top 4 %Relegation %
ChampionTop 4Relegation zone

Match predictions all 243 fixtures →

Model win / draw / win probability for the next fixtures — tap any match for the full prediction.

Recent results

Attack & defence strength

Every club's model attack rating (→) vs defence rating (↑). Top-right = strong both ways.

Stronger attack → ↑ Stronger defence FCBBVBSCFB04RBLSVWM05ELVFCATSGHSVKOESCPSGEVFBS04UNBBMG
Most goals scoredBayern (25)
Best defence (fewest conceded)Dortmund (4)
Strongest (projected pts)Bayern (84)

Top scorers

#PlayerClubGA
1Niclas FüllkrugBremen80
2Michael OliseBayern63
3Patrik SchickLeverkusen62
4Younes EbnoutalibFrankfurt51
5Phillip TietzMainz50
6Luis DíazBayern41
7Yuito SuzukiFreiburg40
8Michael GregoritschAugsburg40
9Christopher NkunkuRB Leipzig41
10Harry KaneBayern44
11Antonio NusaRB Leipzig35
12Igor MatanovicFreiburg31

Top assists

#PlayerClubAG
1Antonio NusaRB Leipzig53
2Marco GrüllBremen52
3Harry KaneBayern44
4Sheraldo BeckerMainz42
5Fabian RiederAugsburg42
6Michael OliseBayern36
7Anthony CaciMainz33
8Ismael SaibariBayern32
9Derry ScherhantFreiburg32
10Patrik SchickLeverkusen26
11Tidiam GomisRB Leipzig23
12Lukas PetkovElversberg22

How is the Bundesliga 2026/27 title and relegation race shaping up, and how are Footyntel's predictions made?

The 2026/27 Bundesliga season is set to be an exciting one, with the title race and relegation battle both poised to be highly competitive. Footyntel provides projections based on a statistical model that blends current season performance with last season's form, simulating the remainder of the season thousands of times to estimate probabilities for title win, top four finishes, and relegation. Below, we delve into how the Bundesliga's format influences these races, what our projection table signifies, and how you can utilize our tools to gain deeper insights.

How does the Bundesliga format affect the title race?

The Bundesliga consists of 18 clubs playing a double round-robin format, resulting in 34 matchdays where each team faces every other team both home and away. This structure ensures a balanced schedule and a fair opportunity for all teams to compete for the title.

Who will win the Bundesliga?

Predicting the winner of the Bundesliga involves analyzing multiple factors, including current form, goal difference, and historical performance. Footyntel's model considers:

Based on these factors, our model generates probabilities for each team to win the title, finish in the top four, or face relegation. These probabilities are presented as dynamic bars on our projection table, allowing users to see at a glance the current standing of each team in the race for the championship.

Bundesliga table projection: What does it mean and how to read it?

Our Bundesliga table projection is a visual representation of the current season's progress, combined with statistical modeling to predict future outcomes. Here's how to interpret the key components:

Projection Table Explained

The projection table includes the following columns:

Users can interact with the table by adjusting match results using our on-page simulator, which recalculates the projections in real-time based on the new data. This feature provides a dynamic way to explore "what if" scenarios and see how different outcomes might affect the final standings.

Bundesliga relegation odds: How are they calculated?

The relegation battle in the Bundesliga is often as intense as the title race, with three teams ultimately facing the drop to the 2. Bundesliga. Footyntel calculates relegation odds using the same statistical model that drives our title and top four predictions.

Understanding Relegation Probabilities

Relegation probabilities are determined by simulating the remainder of the season and calculating the percentage of simulations in which each team finishes in the bottom three. Key factors influencing these probabilities include:

Teams with higher relegation probabilities are those that the model predicts are most at risk of finishing in the bottom three. However, it's important to note that the Bundesliga relegation playoff, which involves the team that finishes 16th in the Bundesliga and the third-placed team from the 2. Bundesliga, adds an additional layer of complexity to the relegation battle.

How accurate are the Bundesliga predictions?

While our model is grounded in data and statistical analysis, it's essential to acknowledge the inherent uncertainty in any predictive model, especially early in the season.

Model Uncertainty and Season Progression

Early in the season, predictions are more uncertain due to the limited amount of data available. As the season progresses and more matches are played, the model's accuracy improves as it has more information to base its simulations on. However, unexpected events such as injuries, managerial changes, or significant transfers can still impact team performance and introduce variability into the predictions.

Footyntel's model is designed to adapt to new information, continuously updating projections as the season unfolds. This adaptability helps to mitigate some of the uncertainty, but it's crucial for users to interpret the predictions as probabilistic estimates rather than definitive outcomes.

How does the interactive simulator work and why is it useful?

The interactive simulator is a powerful tool that allows users to engage directly with the projection model. Here's how it works:

Interactive Simulator Features

The simulator enables users to:

This tool is invaluable for fans, analysts, and pundits who want to delve deeper into the potential outcomes of the season. It provides a platform for informed discussion and analysis, allowing users to gain insights into the factors that drive team performance and league dynamics.

How can the free open data (JSON/CSV) be used?

Footyntel offers free access to open data in both JSON and CSV formats, providing a wealth of information for those interested in conducting their own analysis.

Utilizing Open Data

Users can leverage the open data to:

By providing open access to data, Footyntel empowers users to explore the Bundesliga in new and innovative ways, fostering a community of engaged and informed fans.

In conclusion, Footyntel's Bundesliga predictions are a blend of statistical modeling and interactive engagement, offering a comprehensive tool for understanding the dynamics of the 2026/27 season. While the model provides valuable insights, it's important to remember that football is unpredictable, and the beauty of the game lies in its uncertainty.

Frequently asked

Can Bayern win the Bundesliga this season?

In Footyntel's 50,000-run simulation, Bayern win the 2026/27 title in about 84.7% of seasons — the highest of any club — projected to finish on roughly 84 points.

Which teams are most at risk of relegation / play-off?

The highest relegation / play-off probabilities are Union Berlin (64.1%), M'gladbach (60.7%), HSV (43.6%), 1. FC Köln (27.3%). These are model estimates from current form and remaining fixtures, not certainties.

Who is favourite for top 4?

By top 4 probability: Bayern (99.8%), Dortmund (90.1%), RB Leipzig (59.2%), Leverkusen (51.5%).

Who is the Bundesliga top scorer this season?

Niclas Füllkrug of Bremen leads the Bundesliga 2026/27 scoring charts with 8 goals.

How are these Bundesliga projections calculated?

Each team gets an attack and defence strength from goals scored and conceded so far (regressed toward the league average early in the season). Every remaining fixture is simulated with a Poisson goals model 50,000 times, resampling each team's strength each season to reflect uncertainty; the share of simulations a team finishes 1st, in the top 4, or in the bottom 3 gives its probabilities. Order of tied teams uses points, then goal difference, then goals scored (exact head-to-head rules are simplified). Data: football-data.org. A statistical model, not a guarantee.

Are these Bundesliga predictions free?

Yes — every Footyntel Bundesliga projection, league table and match prediction is free with no sign-up, and the underlying data is published under CC BY 4.0.

How often is the Bundesliga table and projection updated?

The Bundesliga 2026/27 projection refreshes every hour from official match data, so the table, title and relegation / play-off probabilities and top-scorer charts stay current.

Open data

Free to use with attribution (CC BY 4.0): projection JSON · projection CSV · standings CSV