Our Aggregation Approach
Weighted Moving Average
Our poll tracker uses a weighted moving average that gives more importance to recent polls and larger sample sizes. Recency weight decays exponentially using a factor of 0.8 per polling period, while sample size weight uses the square root of (sample/1000) to prevent massive polls from completely dominating.
Margin of Error
The shaded bands around trend lines represent the margin of error at each point in time, interpolated between polling dates. This visually represents the uncertainty range of the polling average.
Data Smoothing
Cosine interpolation is applied between polling data points to create smooth transitions, mimicking the S-curve of how public opinion actually changes - slowly at first, then accelerating, then plateauing.
Seat Projection Methodology
Our seat projections use a Monte Carlo simulation with 5,000 iterations. Each simulation adds realistic polling noise (±3% MoE variance), applies historical seat efficiency ratios (how effectively votes convert to seats for each party), and adjusts for PR-STV transfer dynamics. Results show the median outcome with 10th-90th percentile confidence ranges.
Coalition Analysis
Coalition likelihood is assessed by computing seat totals for viable combinations, comparing against the 88-seat majority threshold. "High" likelihood means the coalition consistently reaches majority across simulations, "Medium" means it occasionally reaches majority, and "Low" means it rarely or never does.
Trend Calculations
Short-term trends compare the current weighted average against the average from a specified number of days ago (default 30 days). This provides a clear picture of momentum shifts.
Data Sources: Polling data is collected from Red C (Business Post), Ireland Thinks (Sunday Independent), and Ipsos B&A (The Irish Times). Historical election results from the official Irish election database. All data is publicly available.