Does The Superforecasters Book Include Practical Exercises?

Short practical version: yes and no. 'Superforecasting' mixes stories, research, and clear, actionable habits rather than a formal set of exercises. If you prefer drills on paper, you won't find a section titled "Exercises" with numbered problems, but you'll find plenty of practiceable techniques scattered through the chapters — decomposition of questions, anchoring avoidance tips, and calibration strategies.

A different way to approach it is to treat each chapter as an exercise prompt. After a chapter on decomposition, for instance, try taking five real-world questions (Will X happen by Y date?) and break each into sub-questions, assign probabilities, and update them after new info. Keep a log and calculate Brier scores weekly. If you want more structure, sign up for 'Good Judgment Open' or follow calibration tests online; that gives the real-time feedback the book says is crucial. Also, pairing the book with 'Thinking, Fast and Slow' or 'The Signal and the Noise' gives useful mental models that translate into drills—systematically checking base rates, running simple counterfactuals, or practicing skeptical hypothesis testing. Honestly, the book feels like coaching more than drilling: it tells you what champions do and nudges you to practice it in the messy real world.

I tend to tell people the honest, compact truth: 'Superforecasting' is full of actionable advice but not a formal exercise book. It reads like a mix of inspiring field stories and bite-sized methods you can put into practice immediately. The authors show how top forecasters iterated their way to skill — they made lots of calibrated probability estimates, tracked outcomes, and learned from feedback — and they describe habits you can emulate.

If you want practical exercises, it's easy to convert the book's guidance into a routine: pick daily or weekly forecasting questions, write down probabilities, decompose complex issues, compare your numbers to base rates, and keep score with Brier or log scores. For more hand-holding, join forecasting platforms or seek online calibration tests. I did a month of small daily predictions inspired by the book and felt my updates become less emotional and more evidence-driven — it's surprisingly satisfying to see your calibration slowly improve, and that's where the theory becomes tangible.

Okay, here’s the long, nerdy take I like to give when friends ask me this — 'Superforecasting' is not a workbook full of step-by-step drills in the way a language textbook might be, but it is very practice-oriented. The authors weave lots of concrete techniques through the narrative: how to break questions into smaller parts, how to use base rates, how to update with new information, and how to keep score. Throughout the book you'll find real examples from the Good Judgment Project, mini case studies of forecasting tournaments, and descriptions of specific habits the best forecasters adopt, like keeping a prediction log and measuring calibration.

What I found most useful were the practical recommendations at chapter ends and the repeated emphasis on behaviors you can actually do: make many small, timed predictions, record probabilities rather than binary calls, decompose vague questions, look for relevant base-rate data, and systematically update your beliefs. The book doesn't hand you a checklist called "Do This 1–10 Every Day," but it gives you the scaffolding to build your own training routine. If you want guided practice, combine reading 'Superforecasting' with platforms like 'Good Judgment Open' or with exercises from 'How to Measure Anything' and you'll get the feedback loop the book talks about.

Personally, I treat the book as both inspiration and a playbook: I highlight bits, then run weekend mini-tournaments with friends, track Brier scores, and set tiny goals (like better calibration on 70% predictions). It helped me move from theoretical curiosity to actually improving my probabilistic thinking, and that jump is where the learning happens.