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Last updated Nov 29, 2025
Prediction
Sacks
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Sacks @ 01:38:57Ambiguous
politics
For the 2024 U.S. presidential election: (1) If Joe Biden runs as the Democratic nominee, the Republican nominee—whoever it is—will win; (2) If the matchup is Ron DeSantis vs. Gavin Newsom, DeSantis will win; (3) If the matchup is Gavin Newsom vs. Donald Trump, Republicans are likely to lose (i.e., Newsom would probably defeat Trump).
I think the configurations that win for the Republicans, I think if Biden is on the ticket, I think any Republican wins. I think if it's DeSantis versus Newsom, I think DeSantis wins. I think, however, and this is sort of the nightmare scenario. I think if it's something like Newsom versus Trump, I think Republicans could lose that just because, you know, the people.View on YouTube
Explanation

There are three conditional predictions here, and only one of the conditions actually occurred; the others never happened, so we cannot strictly mark them right or wrong.

  1. If Biden runs as the Democratic nominee, any Republican wins.
    In reality, the 2024 general election was Joe Biden (D) vs. Donald Trump (R), and Biden won the presidency (Democrats retained the White House).
    Under the condition that did happen (Biden as the nominee), Sacks’s prediction that “any Republican wins” is wrong.

  2. If it’s DeSantis vs. Newsom, DeSantis wins.
    This matchup never occurred: Ron DeSantis did not become the GOP nominee, and Gavin Newsom was not the Democratic nominee. Because the underlying condition failed, this part of the prediction cannot be evaluated against reality and remains counterfactual.

  3. If it’s Newsom vs. Trump, Republicans could lose (Newsom probably defeats Trump).
    This matchup also never occurred: Newsom did not run as the Democratic nominee, so this too is counterfactual and not testable.

Overall: Part (1) is clearly falsified by the 2024 result, but parts (2) and (3) are untestable counterfactuals. Because the user bundled all three into a single prediction, the combined evaluation is ambiguous: one tested component is wrong, while the others never faced real-world verification. If we evaluated only the scenario that actually occurred, it would be wrong, but as a set of branching scenarios, the overall judgment is best labeled "ambiguous".