Accuracy Check: Which German Polling Institute is Most Reliable?

Historical Accuracy of Pre-Election Polls in Germany
Highly Accurate
Low Accuracy
1

Highly Reliable

1 institutes showed only minor discrepancies between their final polls and the actual election results.

12

Solid Results

12 institutes showed moderate average deviations from election results.

0

Significant Deviations

0 institutes showed significant discrepancies between their pre-election polls and actual results.

0

Major Deviations

0 institutes significantly missed the actual election results.

0

No Data Available

No historical comparison data is currently available for 0 institutes.

Overview of Active Polling Institutes in Germany

Party frequently overestimated
Party frequently underestimated

87
Institut Wahlkreisprognose

Accuracy: 1.1
Highly Accurate
Low Accuracy

Party Deviations

CDU/CSU
Grüne
SPD

87
Forschungsgruppe Wahlen

Accuracy: 1.1
Highly Accurate
Low Accuracy

Party Deviations

CDU/CSU
Grüne

86
GMS

Accuracy: 1.3
Highly Accurate
Low Accuracy

Party Deviations

CDU/CSU
SPD

85
Ipsos

Accuracy: 0.9
Highly Accurate
Low Accuracy

Party Deviations

CDU/CSU
Die Linke
Grüne
SPD

85
Infratest dimap

Accuracy: 1.5
Highly Accurate
Low Accuracy

84
INSA

Accuracy: 1.5
Highly Accurate
Low Accuracy

Party Deviations

AfD
Grüne

83
Civey

Accuracy: 1.7
Highly Accurate
Low Accuracy

Party Deviations

CDU/CSU

82
Verian

Accuracy: 1.4
Highly Accurate
Low Accuracy

Party Deviations

SPD

82
Forsa

Accuracy: 1.4
Highly Accurate
Low Accuracy

Party Deviations

AfD
CDU/CSU
Grüne
SPD

78
Allensbach

Accuracy: 1.1
Highly Accurate
Low Accuracy

Party Deviations

AfD
CDU/CSU
Grüne
SPD

77
YouGov

Accuracy: 1.8
Highly Accurate
Low Accuracy

Party Deviations

AfD
CDU/CSU
Die Linke
Grüne
SPD

76
pollytix

Accuracy: 1.2
Highly Accurate
Low Accuracy

Party Deviations

Grüne

71
Trend Research Hamburg

Accuracy: 1.5
Highly Accurate
Low Accuracy

Party Deviations

CDU/CSU
Grüne
SPD

What is the PolitPro Score?

The PolitPro Score assesses the reliability of polling institutes by comparing their data with actual election results and the calculated trend. A high score reflects an accurate representation of political sentiment without systematic distortion. Significant, repeated deviations for individual parties lead to point deductions. Such discrepancies often indicate "house effects"—methodological peculiarities in weighting that systematically over- or under-represent certain parties. The score provides transparent guidance on which institutes most accurately mirror reality. The maximum score is 100.

How is election accuracy calculated?

Accuracy indicates how closely pre-election polls aligned with actual election results. We compare final surveys from various institutes with official outcomes. To do this, we calculate the average deviation across all parties that received at least 3% of the vote. Most election polls have a standard margin of error of 2-3 percentage points. We categorize average deviations as follows: up to 1 percentage point is "very good" (green); up to 2 points is "good" (yellow); up to 3 points is "acceptable" (orange), though this may indicate significant outliers for specific parties. Deviations exceeding 3 percentage points suggest a lack of predictive power and are rated "poor" (red).

How are party deviations calculated?

Party deviation measures how frequently an institute’s data significantly diverges from the overall trend. Persistent outliers for specific parties can suggest methodological bias or "house effects." We analyze an institute’s deviation by comparing its party values against the PolitPro Election Trend—a weighted average of all current surveys. If a value is within +/- 1 percentage point of the trend, it is classified as "consistent." Beyond that, it is "higher" or "lower." We consider deviations in up to 20% of cases as normal. If deviations exceed 20%, we flag the party with a corresponding arrow. Note: Party deviation should always be analyzed alongside overall election accuracy.

Data Sources and Methodology

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