Number Cruncher Politics achieved a PolitPro Score of 82 out of 100.
On average, Number Cruncher Politics's figures deviate by 0.6 percentage points between their final pre-election polls and actual election results.
In 29% of polls, Number Cruncher Politics rated Green Party higher than the PolitPro Election Trend (average of all institutes).
In 21% of polls, Number Cruncher Politics rated Labour higher than the PolitPro Election Trend (average of all institutes).
In 30% of polls, Number Cruncher Politics rated Reform UK higher than the PolitPro Election Trend (average of all institutes).
In 36% of polls, Number Cruncher Politics rated Tories higher than the PolitPro Election Trend (average of all institutes).
In 29% of polls, Number Cruncher Politics rated Labour lower than the PolitPro Election Trend (average of all institutes).
In 71% of polls, Number Cruncher Politics rated Liberal Democrats lower than the PolitPro Election Trend (average of all institutes).
The PolitPro Election Trend serves as the benchmark, using a time-weighted average of all current surveys. A poll value is flagged if it deviates by more than one percentage point from this trend.
On average, Number Cruncher Politics's figures deviate by 0.6 percentage points between their final pre-election polls and actual election results.
With an average deviation of 0.55 percentage points per party, Number Cruncher Politics ranks 2 out of 12.
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).
