Coaching practices for Superforecasting Practice

Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For Superforecasting Practice, these are the strongest matches in the current practice library.

Does this sound like the set of challenges you might be facing?

  • When a prediction of mine blows up, I either spiral into thinking the whole thing is pointless or I just shrug and forget it
  • I commit to one confident number
  • The question is so big and tangled that I just go with my gut and blurt out a number, and it feels like a guess because it is one
  • Each project wraps up and I move straight on without ever writing down what I’d guessed versus what actually happened
  • I’m guessing how this goal of mine will play out purely from my own picture of it, and it feels sure to work

Practices that may help

  1. Superforecasting
    Philip Tetlock’s forecasting tournament research found that a subset of ordinary people — "superforecasters" — consistently outperform domain experts and intelligence analysts at probabilistic prediction. They share measurable cognitive and behavioral habits: they think in probabilities, update frequently on evidence, and actively seek disconfirming information. These habits are learnable.
  2. Treat forecasting accuracy as a skill that improves with practice
    Take prediction errors as performance feedback, not as proof that forecasting is futile.
    Superforecasting
  3. Reference Class Forecasting
    Reference class forecasting, developed by Daniel Kahneman and Amos Tversky and formalized by Bent Flyvbjerg, improves forecast accuracy by anchoring on the statistical distribution of outcomes for similar past projects rather than on the details of the current one. The method reliably corrects the optimism bias that inflates cost, time, and benefit estimates in planning — the evidence base here is real and specific.
  4. Forecast a distribution, not a point estimate
    Represent your forecast as a range of likely outcomes, not a single predicted number.
    Reference Class Forecasting
  5. Decompose complex questions into sub-questions
    Break a hard forecasting question into smaller, estimable pieces and aggregate them.
    Superforecasting
  6. Conduct post-project debriefs to contribute to the class data
    Record actual vs. forecast outcomes honestly — this builds the reference class that future forecasts depend on.
    Reference Class Forecasting
  7. Use reference classes to ground personal estimates in base rates
    Before estimating how your situation will unfold, find similar past situations and check what happened.
    Bayesian Thinking: How to Update Beliefs Rationally
  8. Update your forecast incrementally as new evidence arrives
    Treat your forecast as a probability that should shift with each new piece of evidence, not a commitment that survives contradiction.
    Reference Class Forecasting
  9. Update beliefs frequently and in small increments
    When new evidence arrives, adjust your probability estimate — even if the change is small.
    Superforecasting
  10. Ask people who’ve been there instead of imagining it
    Other people’s actual experiences predict your future feelings more accurately than your own imagination.
    Affect Forecasting: Why You Mispredicted How You’d Feel

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