CNN's Election Projection Process

CNN's Election Projection Process

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CNN's Election Projection Process

CNN's process for projecting election winners involves multiple levels of review, incorporating various data points and statistical modeling. Some states may not be projected on election night due to slow vote counting.

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United States
Us PoliticsElectionsMediaStatisticsData AnalysisProjections
Cnn
Jennifer AgiestaDonald TrumpKamala Harris
Who is involved in making projections for CNN?
Several levels of personnel are involved. Individual teams analyze states, making recommendations to a supervisory decision desk. Jennifer Agiesta provides final review before release to the control room and broadcast.
How does CNN handle projecting election winners?
CNN projects races, not announces them. A projection is a prediction of the race's outcome based on available data, not a definitive statement.
How does the process progress throughout the election night?
The process evolves throughout the night. Initial focus is on exit polls, then shifts to real vote counts and statistical modeling. Late in the night, it becomes more of an algebraic problem determining if a trailing candidate can mathematically win.
What factors does the decision desk consider when closing polls?
The decision desk uses various data points including vote counts, vote types (mail-in vs. Election Day), geographical distribution, exit polls, and statistical models to assess confidence levels.
Are there any specific thresholds or markers looked for to make a projection?
Some states' vote-counting processes may prevent election-night projections due to factors like late processing of mail-in ballots (Pennsylvania, Arizona, Nevada). States with close margins and slow counting will also take longer to project.