Coaching practices for How to Make Accurate Predictions
Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For How to Make Accurate Predictions, 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’m sure about things constantly and I have no idea if that confidence is earned
- I make calls all the time but I never write them down or check them later, so my confidence is just a feeling that floats free
- I make calls about how things will go all the time, but I never write them down or check them after
- I want to actually know whether my gut is any good — when I feel sure about something, am I right that often, or am I just confident?
Practices that may help
- Treat forecasting accuracy as a skill that improves with practice
Take prediction errors as performance feedback, not as proof that forecasting is futile.
Superforecasting - Practice probabilistic calibration by tracking your predictions
Assign explicit probability estimates to your predictions and track whether they come true at the right rate.
Base-Rate Neglect: Why We Ignore the Odds - Maintain a scored prediction log
Record predictions with explicit probabilities and score them when they resolve.
Calibration Training - Score your own past predictions to calibrate your outside-view use
Keep a forecast log and score it — you cannot improve calibration without feedback on where you were over- or under-confident.
The Outside View - Practice probability calibration
Regularly make probabilistic predictions and track your accuracy across many of them.
Hindsight Bias: Why Everything Seems Obvious in Retrospect - 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. - 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 - Make bold predictions — then check them
State a specific, testable prediction about the future and record it before you see the outcome.
Falsification Thinking - Pre-commit to resolution criteria before making a prediction
Define exactly what counts as "I was right" before the outcome happens.
Calibration Training - Track your estimates and calibrate
Compare your Fermi estimates to actual figures when you can, and use the gap to improve future estimates.
Fermi Estimation
Related concerns
- Bold Predictions Testing
State a specific, testable prediction about the future and record it before you see the outcome.
Make bold predictions — then check them
- How To Improve Predictions
Take prediction errors as performance feedback, not as proof that forecasting is futile.
Treat forecasting accuracy as a skill that improves with practice
- How To Track Your Predictions
Keep a forecast log and score it — you cannot improve calibration without feedback on where you were over- or under-confident.
Score your own past predictions to calibrate your outside-view use
- Past Predictions Accuracy
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.
- Prediction Tracking
Take prediction errors as performance feedback, not as proof that forecasting is futile.
- Confidence Prediction Tracking
Assign explicit probability estimates to your predictions and track whether they come true at the right rate.
Practice probabilistic calibration by tracking your predictions
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