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La ecuación del éxito: Descubre la proporción que existe entre habilidad y suerte, tanto en los negocios y las inversiones como en los deportes
En toda actividad que desarrollemos los resultados son iguales a las habilidades más la suerte. Hay un componente de previsibilidad y de imprevisibilidad en todo lo que hacemos. El autor busca a través de la ecuación del éxito medir la proporción que la suerte y los elementos imprevisibles tienen en la consecución de un resultado.
Si logramos saber esto, podremos analizar con eficiencia la calidad de las acciones que tomamos en relación a los resultados obtenidos.
De esta forma podemos adoptar mejores decisiones y mejorar nuestra productividad y el retorno de nuestras inversiones, logrando disminuir considerablemente la importancia de la suerte y demás imprevistos en los resultados obtenidos.
Si logramos saber esto, podremos analizar con eficiencia la calidad de las acciones que tomamos en relación a los resultados obtenidos.
De esta forma podemos adoptar mejores decisiones y mejorar nuestra productividad y el retorno de nuestras inversiones, logrando disminuir considerablemente la importancia de la suerte y demás imprevistos en los resultados obtenidos.
416 pages, Kindle Edition
First published October 16, 2012
314 people are currently reading
5801 people want to read
About the author
Michael J. Mauboussin
15 books332 followersMichael J. Mauboussin is Chief Investment Strategist at Legg Mason Capital Management. Prior to joining LMCM in 2004, Michael was a Managing Director and Chief U.S. Investment Strategist at Credit Suisse. Michael joined CS in 1992 as a packaged food industry analyst. He is a former president of the Consumer Analyst Group of New York and was repeatedly named to Institutional Investors All-America Research Team and The Wall Street Journal All-Star survey in the food industry group.
Michael is the author of Think Twice: Harnessing the Power of Counterintuition (Harvard Business Press, 2009) and More Than You Know: Finding Financial Wisdom in Unconventional PlacesUpdated and Expanded (New York: Columbia Business School Publishing, 2008). More Than You Know was named one of The 100 Best Business Books of All Time by 800-CEO-READ, one of the best business books by BusinessWeek (2006) and best economics book by Strategy+Business (2006). He is also co-author, with Alfred Rappaport, of Expectations Investing: Reading Stock Prices for Better Returns (Harvard Business School Press, 2001).
Michael has been an adjunct professor of finance at Columbia Business School since 1993 and is on the faculty of the Heilbrunn Center for Graham and Dodd Investing. In 2009, Michael received the Deans Award for Teaching Excellence. BusinessWeeks Guide to the Best Business Schools (2001) highlighted Michael as one of the schools Outstanding Faculty, a distinction received by only seven professors.
Michael earned an A.B. from Georgetown University. He is also affiliated with the Santa Fe Institute, a leading center for multi-disciplinary research in complex systems theory, and is on the board of directors of Sermo, an online community for physicians."
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Displaying 1 - 30 of 137 reviews
December 18, 2013
This books is about understanding how to disentangle luck and skill when evaluating performance, and the implications of making predictions in different environments. Lots to think about here, and the author does a good job of introducing a few ways to tease out skill from luck. Unfortunately, most of the interesting action happens in academic papers which are merely alluded to, so he gives conclusions and brief summaries of the studies, but doesn't show their inner workings. How do we know that the studies themselves didn't arrive at their conclusions out of pure luck?
This book is a bit of a mish-mash, and tends to wander off into summaries of well known studies related to cognitive biases, even if the relation to the main subject is minimal. It's also repetitive, especially towards the end once the main points have been made. All that said, as a starting point for understanding skill vs luck it's not bad, and the author clearly has a broad knowledge of the field of research.
This book is a bit of a mish-mash, and tends to wander off into summaries of well known studies related to cognitive biases, even if the relation to the main subject is minimal. It's also repetitive, especially towards the end once the main points have been made. All that said, as a starting point for understanding skill vs luck it's not bad, and the author clearly has a broad knowledge of the field of research.
May 1, 2013
As someone interested in each of sports, business, and investing, I had high hopes for this book but ultimately found it lacking. The connections between the three are often tenuous, the chapters frequently repetitive (this book would have been better as a long essay), and the material often regurgitated from other authors (I've read Thinking Fast and Slow, some Taleb, and tons on sports analytics, so a lot in this book was repetitive).
The author does add some of his own analysis, specifically on which sports and games feature more or less luck--but I found his methodology not especially compelling, and the author far too certain that he had figured out exactly where these games sit on the skill-luck spectrum. Additionally, I thought he over-simplified some of the questions he was trying to address (which, granted, are complicated), for the sake of making a point--particularly in an example he gives about the Yankees, which in my view ascribes to luck what is actually variation in skill.
Two anecdotes I wasn't familiar with that seemed on point--Atul Gawande, a noted surgeon, emphasizing the importance of feedback even for expert practitioners; and the value of checklists in minimizing error in medical procedures, airplane navigation, and other fields.
It's not poorly written, but not distinguished on this front, either ("During the summer, personal ambition often lay dormant, like an animal in hibernation").
Trading Bases, another book I read recently, addresses some of the same topics, in a much more compelling fashion, and with much more thought-provoking analysis.
The author does add some of his own analysis, specifically on which sports and games feature more or less luck--but I found his methodology not especially compelling, and the author far too certain that he had figured out exactly where these games sit on the skill-luck spectrum. Additionally, I thought he over-simplified some of the questions he was trying to address (which, granted, are complicated), for the sake of making a point--particularly in an example he gives about the Yankees, which in my view ascribes to luck what is actually variation in skill.
Two anecdotes I wasn't familiar with that seemed on point--Atul Gawande, a noted surgeon, emphasizing the importance of feedback even for expert practitioners; and the value of checklists in minimizing error in medical procedures, airplane navigation, and other fields.
It's not poorly written, but not distinguished on this front, either ("During the summer, personal ambition often lay dormant, like an animal in hibernation").
Trading Bases, another book I read recently, addresses some of the same topics, in a much more compelling fashion, and with much more thought-provoking analysis.
August 13, 2022
Not a book I’d usually read. Campy title sets itself up to over promise and under deliver. But the author was recommended by Phillip Tetlock who’s Superforcasting I really liked.
Super happy I ignored the cover and picked it up. One of the best books on the interaction of luck and randomness in life. Backed with research I approve of. Written in an accessable tone.
Couple of my notes:
Environmental success. Punters vs. Receivers. Take a hard look at success and it's environmental factors. Punters can operate independent of the team to a large extent. Receivers are much more subject to the quality of their team. Really feeling this while working from home currently, I have been getting extremely in my own head and need to find people to bounce ideas off of.
Importance of sample size. With uncertainty, small sample size is extremely detrimental. Errors can be magnified and noexistant correlations can be found in any data set by torturing it enough. Errors are to be expected by using improperly sized data sets for the sample size. Seems simple and common sense, but really feeling the difficulty in practice. Think bigger. Zoom out more. What are we trying to accomplish? Is this representative of the population?
Deliberate practice helps only in linear activities. As we add complexity, deliberate practice can actually become detrimental as we will find connections that don't exist.
Reversion to the mean should be your base assumption. Not sure I fully understand this. More investigation would be helpful. In higher skill events reversion to mean will be less prelevant.
Investing edge
Need to assess real fundamentals. Such as supply and demand, economic profit, and sustainable competitive advantage. If there is a price difference. need to assess why market has priced in that discrepancy. Margin of safety.
Portfolio construction
Weight portfolio based upon the attractiveness of the opportunity. Commonly stated but difficult to follow. A good reminder.
Overall a wonderful read.
Super happy I ignored the cover and picked it up. One of the best books on the interaction of luck and randomness in life. Backed with research I approve of. Written in an accessable tone.
Couple of my notes:
Environmental success. Punters vs. Receivers. Take a hard look at success and it's environmental factors. Punters can operate independent of the team to a large extent. Receivers are much more subject to the quality of their team. Really feeling this while working from home currently, I have been getting extremely in my own head and need to find people to bounce ideas off of.
Importance of sample size. With uncertainty, small sample size is extremely detrimental. Errors can be magnified and noexistant correlations can be found in any data set by torturing it enough. Errors are to be expected by using improperly sized data sets for the sample size. Seems simple and common sense, but really feeling the difficulty in practice. Think bigger. Zoom out more. What are we trying to accomplish? Is this representative of the population?
Deliberate practice helps only in linear activities. As we add complexity, deliberate practice can actually become detrimental as we will find connections that don't exist.
Reversion to the mean should be your base assumption. Not sure I fully understand this. More investigation would be helpful. In higher skill events reversion to mean will be less prelevant.
Investing edge
Need to assess real fundamentals. Such as supply and demand, economic profit, and sustainable competitive advantage. If there is a price difference. need to assess why market has priced in that discrepancy. Margin of safety.
Portfolio construction
Weight portfolio based upon the attractiveness of the opportunity. Commonly stated but difficult to follow. A good reminder.
Overall a wonderful read.
November 19, 2012
After the egotistical musings of Taleb (The Black Swan: The Impact of the Highly Improbable) this book was a breath of fresh air. The author provides clear explanations of how intuition and practice mislead one when skill and luck are mixed, and what understandings from reality one can and cannot rely upon. All of this information is provided at an engaging pace without reverting to the gee-wiz tricks or over-simplification of the TED generation. If something like Taleb built your interest in the topic, this is the book to read to actually understand it.
April 20, 2013
Mike Mauboussin is one of my favorite authors. In THE SUCCESS EQUATION, he takes us on a ride through the math of sabermetricians, case studies of behavioral psychologists, and through his own investigations to show us that success is a product of the interplay between skill and luck.
The book offers a few new (to me) insights that are worth recalling:
The paradox of skill - in fields where skill is more important to the outcome, luck's role in determining the ultimate winner increases. And in fields where luck plays a larger role in the outcome, skill is also very important but difficult to ascertain without a large enough sample set.
IQ vs RQ - identifies that IQ is an overused talent measure for success because RQ (rationality quotient) is more closely associated with decision making. He argues that many people hide behind "good work product", clearly an IQ outcome, rather than evaluating "good decision making" which is much better associated with RQ.
The Matthew Effect - highlights the idea that the most successful individuals tend to grow more successful and the poor grow poorer due to the endowment effect of early success (which may be due to good luck and not just skill).
Favorites should eliminate complexity on the "battlefield" - if you have superior resources, you should try to concentrate your battles in fewer fields than if you are the underdog. Various studies show that increasing complexity increases the role of luck and gives the underdog an advantage in competition.
The fluid mind vs the crystallized mind - the research shows that our fluid mind, the part of our brain useful for creative decisions when facing problem sets we have not seen, decreases with age an accelerating rate. The crystallized mind, our ability to develop mental models for "problems we have seen before" tends to increase well into our old age. The optimal age for investing, it turns out, is in the late 30s to mid 40s.
Clutch performance - perhaps the one topic I wish MM would have spent more time on. He acknowledges that streakiness does have some empirical support but that this topic hasn't been as well studied from a behavioral perspective as it has been from an observation standpoint. Maybe for his next book...
Bottom line: there is both depressing and hopeful conclusions from MM's latest book. First, the good news. Outperformance due to high skill IS statistically supported in the data. However, good luck is required to turn high skill (the prerequisite) into success, but luck plays a heavy hand in outcomes. The only way to reduce the role of luck in games where luck still plays a dominant role is to understand what it means to be a 6'10" basketball player in your chosen field. It would seem like the prerequisites for success in investing (the 6'10" basketball player equivalent are as follows:
1) a high IQ,
2) an elevated RQ, that has a strong system 1 with great pattern recognition and a non-lazy system 2 with excellent logical processing, with
3) a creative (fluid mind) intelligence that allows the investor to think about investing opportunities through unique, differentiated framing,
4) a well tuned crystallized mind that correctly identify patterns and uses well-developed mental models to make decisions with the information, and
5) clutch instincts that allow the investor to make difficult decisions even under pressure when presented with new, adverse, or fortuitous information.
The book offers a few new (to me) insights that are worth recalling:
The paradox of skill - in fields where skill is more important to the outcome, luck's role in determining the ultimate winner increases. And in fields where luck plays a larger role in the outcome, skill is also very important but difficult to ascertain without a large enough sample set.
IQ vs RQ - identifies that IQ is an overused talent measure for success because RQ (rationality quotient) is more closely associated with decision making. He argues that many people hide behind "good work product", clearly an IQ outcome, rather than evaluating "good decision making" which is much better associated with RQ.
The Matthew Effect - highlights the idea that the most successful individuals tend to grow more successful and the poor grow poorer due to the endowment effect of early success (which may be due to good luck and not just skill).
Favorites should eliminate complexity on the "battlefield" - if you have superior resources, you should try to concentrate your battles in fewer fields than if you are the underdog. Various studies show that increasing complexity increases the role of luck and gives the underdog an advantage in competition.
The fluid mind vs the crystallized mind - the research shows that our fluid mind, the part of our brain useful for creative decisions when facing problem sets we have not seen, decreases with age an accelerating rate. The crystallized mind, our ability to develop mental models for "problems we have seen before" tends to increase well into our old age. The optimal age for investing, it turns out, is in the late 30s to mid 40s.
Clutch performance - perhaps the one topic I wish MM would have spent more time on. He acknowledges that streakiness does have some empirical support but that this topic hasn't been as well studied from a behavioral perspective as it has been from an observation standpoint. Maybe for his next book...
Bottom line: there is both depressing and hopeful conclusions from MM's latest book. First, the good news. Outperformance due to high skill IS statistically supported in the data. However, good luck is required to turn high skill (the prerequisite) into success, but luck plays a heavy hand in outcomes. The only way to reduce the role of luck in games where luck still plays a dominant role is to understand what it means to be a 6'10" basketball player in your chosen field. It would seem like the prerequisites for success in investing (the 6'10" basketball player equivalent are as follows:
1) a high IQ,
2) an elevated RQ, that has a strong system 1 with great pattern recognition and a non-lazy system 2 with excellent logical processing, with
3) a creative (fluid mind) intelligence that allows the investor to think about investing opportunities through unique, differentiated framing,
4) a well tuned crystallized mind that correctly identify patterns and uses well-developed mental models to make decisions with the information, and
5) clutch instincts that allow the investor to make difficult decisions even under pressure when presented with new, adverse, or fortuitous information.
February 26, 2016
Some good clear practical takeaways to frame decisions in business/investments and picking fantasy sports teams! The core premise could be summarized well in a typical HBR article, but the book is still relatively short and includes some good examples across sports, business and investments that support the arguments.
February 12, 2018
One thing is certain – author has knowledge about skill and luck to some degree. But that is maximum I’ll give to this book, there are so many problems I’ve encountered.
Empirical data? I would never go that far. The author is citing other people that talked about same thing, or at least aspects of ideas that he is using in this work. Without an explanation of there work, or why is it true for his final work. We have to presume it is. But that is not strange, as we have to presume that whole his work is true. It might be, but there is zero evidence. Graphs with data are here, but how anyone got to that date? Not even a slightest explanation of that.
Repetition didn’t help, and I’m not sure how good it is for investment. But sports part was subpar, populistic, and not even a sign of science. Waste of time.
Empirical data? I would never go that far. The author is citing other people that talked about same thing, or at least aspects of ideas that he is using in this work. Without an explanation of there work, or why is it true for his final work. We have to presume it is. But that is not strange, as we have to presume that whole his work is true. It might be, but there is zero evidence. Graphs with data are here, but how anyone got to that date? Not even a slightest explanation of that.
Repetition didn’t help, and I’m not sure how good it is for investment. But sports part was subpar, populistic, and not even a sign of science. Waste of time.
March 24, 2016
A fantastic book. It's easy to read, it's thoughtful, it's full of knowledge. Every chapter provides great advices – ready to use in business, sports betting, investing and everyday life – even in raising your children. Author presents a source for practically every fact or information in his book – whether it's a book of an economy professor or author's own analysis. This book really gave me a lot of insight into my life, it made me think differently. You'd be surprised how much luck there is to our lives and how much it can change. Thanks to this book, I started to love statistics.
July 27, 2013
Interesting additionally for whose who are obsessed with the theory of "deliberate practice"
November 24, 2021
I have been a fan of Michael Mauboussin's work for many years, and was recommended this book by a friend. While there are a few very powerful insights in the book, I'm not sure I took away a lot of new information from other books I have read on similar topics. The main point Mauboussin is getting across is that we have to separate luck from skill in determining outcomes, and we often overweight skill and discount the impact of luck. A short summary of my takeaways are:
Luck is what is left over after you subtract skill from an outcome, and just about all outcomes involve at least some luck. A quick and easy way to test whether an activity involves skill: ask yourself whether or not you can lose on purpose.
If you have an activity where the results are nearly all skill you don't need a large sample to draw reasonable conclusions. But as you move left on the continuum between skill and luck, you need an even larger sample to understand the contributions of skill and luck.
Post Hoc Fallacy: The need to create stories "after this, therefore because of this" (ie: I played a great round of golf because I wore my lucky belt. We sometimes assume that a favorable outcome was the result of a skillful strategy in overlook the influence of luck. When luck plays a part in determining the consequences of your actions you don't want to study success to learn which strategy to see whether it consistently leads to success. Our minds naturally create cause and effect for every outcome, and we ignore the impact of luck.
The paradox of skill - as skill improves, performance becomes more consistent, and competition increases, therefor luck becomes more important.
There is always a reversion to the mean as the sample size gets larger.
Short checklists and quality feedback are effective ways to improve skill. Deliberate practice is another way to improve expertise over time.
Our minds naturally assign causes to all we see, no matter if the result is skill or luck. People think they are "good" at roulette because of the numbers they pick or how they play, but in reality it is a game of complete luck.
Luck is what is left over after you subtract skill from an outcome, and just about all outcomes involve at least some luck. A quick and easy way to test whether an activity involves skill: ask yourself whether or not you can lose on purpose.
If you have an activity where the results are nearly all skill you don't need a large sample to draw reasonable conclusions. But as you move left on the continuum between skill and luck, you need an even larger sample to understand the contributions of skill and luck.
Post Hoc Fallacy: The need to create stories "after this, therefore because of this" (ie: I played a great round of golf because I wore my lucky belt. We sometimes assume that a favorable outcome was the result of a skillful strategy in overlook the influence of luck. When luck plays a part in determining the consequences of your actions you don't want to study success to learn which strategy to see whether it consistently leads to success. Our minds naturally create cause and effect for every outcome, and we ignore the impact of luck.
The paradox of skill - as skill improves, performance becomes more consistent, and competition increases, therefor luck becomes more important.
There is always a reversion to the mean as the sample size gets larger.
Short checklists and quality feedback are effective ways to improve skill. Deliberate practice is another way to improve expertise over time.
Our minds naturally assign causes to all we see, no matter if the result is skill or luck. People think they are "good" at roulette because of the numbers they pick or how they play, but in reality it is a game of complete luck.
April 28, 2018
Michael Mauboussin's quantitative thoughts on sports and investing may not be everyone's cup of tea. But having seen him speak a couple of times - I even met him once briefly - I know we share a similar mind set. So I was more excited than most when I stumbled onto The Success Equation. Maybe not as excited as I was when I read Murakami on running or Knausgaard on football, but still pretty excited. I did learn many interesting and useful things such as: which sports rely more on luck (hockey) and which are more skill based (basketball); and where investing falls on the luck-skill continuum (it's more random than we'd would believe). And the more luck plays a role in an outcome, the longer it can take for skill to become apparent. In hockey for example, the number of scoring chances are few, so a bad team can often beat a good team with a lucky break or a hot goaltender. But over a best-of-seven series though, the luck averages out and the 'better' team should win. Luck also plays an important role in how quickly results return to normal (regress to the mean). In investing, because luck is so influential, good years usually follow bad years and vice versa, which makes it very difficult for an investor to show any sort of performance persistency. Finally, Mauboussin has some interesting things to say about intelligence and aging. For most people fluid intelligence (i.e. problem solving) peaks at 20 then deteriorates, while crystallized intelligence (i.e. knowledge) improves with age. Apparently peak performance for a financial professional is 53, which gives me hope. Old people are better at refining and improving processes, while the young are better suited for new ideas and experimentation. All good stuff; but the problem with this book is that all these ideas are concentrated in the first 100 pages. In the second half, Mauboussin goes into how to build skill, deal with luck, and develop good guesswork. While these may be worthy topics in themselves, I found these chapters to be mainly reworkings other people's writing (Gawande, Kahneman, Tetlock). All worthy ideas, decently presented, but a bit derivative. Overall, although the content is not always original, there is some thought provoking material here, and it's easy to read.
May 29, 2023
Great book if you want to improve your thinking and mental models.
May 22, 2024
My Libby rental actually ran out, but these kinds of books tend to start with a great idea and then tend to repeat themselves over and over so I feel like I got the gist
August 22, 2018
Michael Mauboussin is a strategist at Legg Mason and previously at CSFB. He is also a teacher at Columbia, a trustee board member of Santa Fe Institute and one of the two persons that have influenced my financial thinking the most. Mauboussins’s new book aims to explain the elements of skill and luck in business, sports and investing. Most activities are a blend of skill and luck and hence the job becomes to place them on the luck-skill continuum. Investing is mainly dominated by luck.
With deeper understanding of luck vs. skill we can design rational operations, do better forecasts and develop skill in ways that fit the activity. “The key to statistical prediction is to figure out how much weight you should assign to the base rate and specific case.” When skill dominates, the specific case should be given higher weight. When luck dominates, the base rate (the probabilities according to evidence from prior similar situations) should be prioritized. The more random a process the stronger the reversal to the mean will be. This means that in areas of skill a few observations can sort out skill from lack of skill. In more random areas the skill that exists will only be observable after a large number of observations.
The greatest misunderstandings occur in the areas where randomness dominates. Humans create stories of cause-and-effect to make sense of the world and hence see developments as more non- random then they really are. One fallacy due to an inability to understand reversal to the mean, in this book called “the dumb money effect” is when capital is allocated to assets, investment managers, investment styles etc. because of recent outperformance the last few years. An effect estimated to have cost investors one yearly percentage point of returns historically.
Mauboussin brings forward useful methods on how to specify and estimate the rate of reversal to the mean and also dissects the most common mean reversion mistakes. One of these, “the illusion of declining variance”, is a mistake you see all too often - for example, as the author points out, when it comes to the reversal to the mean in companies’ return on invested capital. This reversal does not mean that all companies in the future will earn the same returns.
In areas where skill dominates, say basketball, the way to improve is through so called deliberate practice. In more mixed areas checklists is a good tool to improve performance. In more random areas the way to improve is to focus on process.
Even though the author shows that which song (or book) that becomes a smash hit, due to complex social interactions and feedback loops, is close to random, The Success Equation could very well become a best seller. Mauboussin combines the deep knowledge, logical ability, pleasant language and pedagogical skills from previous books with a broadening of scope. This is a book on popular science more than on investments. The origin to the book is four or five reports that made their way to Mauboussin’s two excellent previous books. He has now expanded on these topics mainly by adding material and examples from the world of sports. The topics are vital for investing and a must to understand, but for those who have read the author’s previous texts there is not much new material directly linked to investments.
The topic that occupied my mind after finishing the book was whether I agreed with Mauboussin or not on his definition of investing skill and expertise; “Deliberate practice and the concept of expertise apply only to the skill side of the luck-skill continuum.” It’s true that you can’t make ten thousand investments just like you practice free throws and by time automatize skill by adding myelin onto neural path ways. However, couldn’t expanding your knowledge and understanding of the best processes also be seen as a type of deliberate practice on a higher level? Over time you will internalize what is likely to work and what is not.
With deeper understanding of luck vs. skill we can design rational operations, do better forecasts and develop skill in ways that fit the activity. “The key to statistical prediction is to figure out how much weight you should assign to the base rate and specific case.” When skill dominates, the specific case should be given higher weight. When luck dominates, the base rate (the probabilities according to evidence from prior similar situations) should be prioritized. The more random a process the stronger the reversal to the mean will be. This means that in areas of skill a few observations can sort out skill from lack of skill. In more random areas the skill that exists will only be observable after a large number of observations.
The greatest misunderstandings occur in the areas where randomness dominates. Humans create stories of cause-and-effect to make sense of the world and hence see developments as more non- random then they really are. One fallacy due to an inability to understand reversal to the mean, in this book called “the dumb money effect” is when capital is allocated to assets, investment managers, investment styles etc. because of recent outperformance the last few years. An effect estimated to have cost investors one yearly percentage point of returns historically.
Mauboussin brings forward useful methods on how to specify and estimate the rate of reversal to the mean and also dissects the most common mean reversion mistakes. One of these, “the illusion of declining variance”, is a mistake you see all too often - for example, as the author points out, when it comes to the reversal to the mean in companies’ return on invested capital. This reversal does not mean that all companies in the future will earn the same returns.
In areas where skill dominates, say basketball, the way to improve is through so called deliberate practice. In more mixed areas checklists is a good tool to improve performance. In more random areas the way to improve is to focus on process.
Even though the author shows that which song (or book) that becomes a smash hit, due to complex social interactions and feedback loops, is close to random, The Success Equation could very well become a best seller. Mauboussin combines the deep knowledge, logical ability, pleasant language and pedagogical skills from previous books with a broadening of scope. This is a book on popular science more than on investments. The origin to the book is four or five reports that made their way to Mauboussin’s two excellent previous books. He has now expanded on these topics mainly by adding material and examples from the world of sports. The topics are vital for investing and a must to understand, but for those who have read the author’s previous texts there is not much new material directly linked to investments.
The topic that occupied my mind after finishing the book was whether I agreed with Mauboussin or not on his definition of investing skill and expertise; “Deliberate practice and the concept of expertise apply only to the skill side of the luck-skill continuum.” It’s true that you can’t make ten thousand investments just like you practice free throws and by time automatize skill by adding myelin onto neural path ways. However, couldn’t expanding your knowledge and understanding of the best processes also be seen as a type of deliberate practice on a higher level? Over time you will internalize what is likely to work and what is not.
October 18, 2016
Success (and failure) are the result of both skill AND luck. Successful people (and outcomes) are not just those with the most skill who work the hardest, but they often benefit from good luck too. Different activities are the result of different mixes of skill and luck; e.g., the outcomes of NBA games and chess are highly reliant on skill, while the outcomes of investing and gambling are highly reliant on luck. The author takes a very statistical, but accessible, approach. I'll never think of elite achievers and dismal failures the same.
August 11, 2016
Are you convinced your kids are smarter than their SAT scores indicate? Are you frustrated that your obvious genius at work seems underappreciated? Do you have great 3-year investment returns but still wonder if you’ve “got it”? Then you must, must read this book. Here is a brief interview with some highlights: http://www.wired.com/wiredscience/201...
February 16, 2013
Very interesting book - he kept the math simple but explained how events occur on a continuum of skill and luck, and how various sports and activities can be quantified by their components of skill and luck, and how some statistics are more meaningful (more skill than luck).
Lots of examples and the math is easy... good read for just about anyone interested in sports/investing/etc.
Lots of examples and the math is easy... good read for just about anyone interested in sports/investing/etc.
March 19, 2014
An extremely interesting book trying to break down the role of skill and luck in life and puts a lot of events that happen around us in perspective. Interesting statistics and an innovative method of untangling the relationship between both. Provides insights as to how you could go ahead and try and improve your chances of being lucky.
July 9, 2014
Unsurprisingly I quite enjoyed this book. The writing style is superb and creates an approachable framework for a largely statistical and/or quantitative based exercise. In fact, I wish this type of reading were pre-course required reading for statistics classes in order to provide the student with a useful framework for the educational effort they are about to begin.
July 14, 2015
You will understand what regression to the mean means by the end of this book, that I promise. Good stuff about statistics, data, and business. I liked Naked Statistics better, but this was pretty good.
December 8, 2015
Good read, and if you love some sports stats and want to relate to the concepts introduced by Taleb's in his Fooled by randomness you would enjoy reading this book. Detailed review here : http://www.gehariharan.com/2015/12/su...
January 19, 2015
The Success Equation is exactly what it describes in the subtitle: Untangling Skill and Luck in Business, Sports, and Investing. I thought this was a great topic but was not executed as sharply as it could be. I liked that there were a lot of examples, and that the author pulled from a variety of different places for the information, but I thought he was a little sloppy with the details and had some logical gaps that were a little frustrating. They did not greatly detract from the overall message, but the book could have benefitted from additional editing from people familiar with the topics he covered. He apparently really liked the book Thinking, Fast and Slow by Daniel Kahnamen as well of the writings of Nassim Taleb, and pulls many concepts and examples from them. Like any book that tries to distill things down to a single theme, he does this a little bit and tries to fit everything into either luck or skill. Did you get a lot of strikeouts today because you were unlucky, or because you faced the best pitcher in baseball? Is it luck that you’re scheduled to face a good pitcher?
He begins the book by defining Luck. “Luck is a chance occurrence that affects a person or a group (e.g., a sports team or a company). Luck can be good or bad. Furthermore, if it is reasonable to assume that another outcome was possible, then a certain amount of luck is involved. In this sense, luck is out of one’s control and unpredictable.” (13) He further clarifies the difference between luck and skill. “The consequences of our efforts, both good and bad, reflect an element within our control – skill – and an element outside of our control – luck. In this sense, luck is a residual: it’s what is left over after you’ve subtracted skill from an outcome.” (16) He then talks about skill a little bit (19) and describes the continuum of activities that are lucky, like gambling, versus activities that are very heavily reliant on skill, like running races or playing chess or checkers. “In considering skill, it’s also important to distinguish between experience and expertise. There is an unspoken assumption that someone doing something for a long time is an expert. In activities that depend largely on skill, though, expertise comes only through deliberate practice, and very few individuals are willing to commit the time and effort to go beyond a plateau of performance that’s good enough. The fact is, most of us generally don’t need performance that’s better than good enough.” (22) He then talks about the difference between the necessary sample size for activities that are mostly skill and those that are mostly luck (to differentiate what Nate Silver would call the signal from the noise). “Here’s the main point: if you have an activity where the results are nearly all skill, you don’t need a large sample to draw reasonable conclusions. A world-class sprinter will beat an amateur every time and it doesn’t take a long time to figure that out. But as you move left on the continuum between skill and luck, you need an ever-larger sample to understand the contributions of skill (the causal factors) and luck. In a game of poker, a lucky amateur may beat a pro in a few hands, but the pro’s edge would become clear as they played more hands.” (26) I would probably use different terms, like talking about the true relationship and the randomness that exists about it, but it’s fairly intuitive. He later talks about why it is hard to distinguish luck from skill. He covers creeping determinism. “This is the propensity of individuals to ‘perceive reported outcomes as having been relatively inevitable.’ Even if a fog of uncertainty surrounded an event before it unfolded, once we know the answer, that fog not only melts away, but the path the world followed appears to be the only possible one. Here is how all of this relates to skill and luck: even if we acknowledge ahead of time that an event will combine skill and luck in some measure, once we know how things turned out, we have a tendency to forget about luck. We string together the events into a satisfying narrative, including a clear sense of cause and effect, and we start to believe that what happened was preordained by the existence of our own skill.” (38) This is an important point, and one that definitely relates to investing. He continues to talk about how we focus disproportionally on the things that went well without sufficiently investigating the context and the things that went wrong – the undersampling of failure. “He argues that one of the main ways that companies learn is by observing the performance and characteristics of successful organizations. The problem is that firms with poor performance are unlikely to survive, so they are inconspicuously absent from the group that any one person observes…Since we draw our sample from the outcome, not the strategy, we observe the successful company and assume the strategy was good.” (39) It’s the issues of looking at who did well, and seeing what they had in common as opposed to seeing who did well, and seeing what percentage that is of all the companies that had a similar strategy. He then talks about whether skill in one place is transferable to another. He cites research saying that punters perform just as well when they transfer teams, but it’s not as much the case with wide receivers. This can also be the case in a business environment. “Star analysts who switched employers paid a high price for jumping ship relative to comparable stars who stayed put: overall, their job performance plunged sharply and continued to suffer for at least five years after moving to a new firm. He considered a number of explanations for the deterioration in performance and concluded that the main factor was that they left behind a good fit between their skills and the resources of their employer.” (45) He again talks about the importance of sample size. “We’re naturally inclined to believe that a small sample is representative of a larger sample. In other words, we expect to see what we’ve already seen. This fallacy can run in two directions. In one direction, we observe a small sample and believe, falsely, that we know what all of the possibilities look like. This is the classic problem of induction, drawing general conclusions from specific observations.” (49) He also talks about the gambler’s fallacy, where we think that if things go bad for long enough then they are bound to turn around and be better in the future. He then talks about how the outcome of an event is like the combination of balls from two jars (52): one being luck and the other being skill. Depending on what you pull, you can be skilled, but still have a negative outcome based on the luck number you draw, but as the sample sizes increase, the ones with more skill will tend to do better than those with less skill, as the total impact of luck converges to the mean for everyone involved. He then goes into some detail about how different activities lie in different places across the skill/luck continuum.
The next portion talks about the arc of skill, and how there are optimal ages for different types of decisions. “When we age, we tend to avoid exerting too much cognitive effort and deliberating extensively over a decision that needs to be made. We gradually come to rely more on rules of thumb. This means that we make poorer choices in environments that are complex and unstable. Business and investing are examples of realms where intuition often fails. Researchers who studied people making investments found that decisions about those investments grew less wise as people aged.” (97)
The book then goes into the many shapes of luck. Sometimes there are familiar patters, like trending or mean reversion. He talks a little bit about the hot hand in basketball. “Statisticians have a name for the normal ups and downs that you should expect when the distribution of luck is known: common –cause variation. For example, common-cause variation can explain most of the changes in Adam Jones’s batting average during the season. It also applies to the output of manufacturing processes and to winning the lottery. In economics, common-cause variation is akin to risk.” (115) They also go into power laws a little bit. “One of the key features of distributions that follow a power law is that there are very few large values and lots of small values. As a result, the idea of an “average” has no meaning.” (117) Averages are more meaningful in data that does not have such a wide distribution. They make the point that you can still look at average height if Bill Gates moves into the neighborhood, but average wealth is no longer meaningful. They also talk about cumulative effects of randomness, and call it the Matthew Effect after a verse from the book of Matthew “For whosoever hath, to him shall be given, and he shall have more abundance: but whosoever hath not, from him shall be taken away even that he hath.” (118) They discuss how two similarly skilled people who get slightly different jobs can end up in very different places 10 or 15 years later. “But the Matthew effect explains how two people can start in nearly the same place and end up world apart. In these kinds of systems, initial conditions matter. And as time goes on, they matter more and more.” (118) Small differences can become magnified over time, depending on the environment.
Next, they spend some time talking about what makes a useful statistic. Essentially, a statistic that has little randomness and high predictive power is more useful than the opposite.
When it comes to building skill, they talked about how effort is important to learn new things. “That said, the claim that talent plays no role in how well people do is not supported by the facts. High performance combines a dash of basic ability with lots of perspiration.” (162) Checklists are also useful to ensure that we build skills the right way. “Checklists are highly effective but underutilized in jobs that combine probabilistic tasks with tasks that follow a set of rules or set procedures. Here’s the reason: professionals in these fields think of themselves as practicing a craft and actually find it demeaning to resort to a checklist. They think they have the knowledge to do the job and do not need any aids. They are wrong, and their attitude is costly.” (163) Checklists don’t replace knowledge, but help people focus their attention, especially at times when things are hectic.
The next section discusses how to deal with luck. To help illustrate this, they introduce us to the Colonel Blotto game, and talk about how it’s important for those that have an advantage to simplify the game, and for those who don’t have the advantage to try to make it as complex and on as many fronts as possible to try to make it so that there is a way that they can get an advantage somewhere. For an overmatched opponent to win, it’s imperative that they force the dominant foe to play their game. “Nearly 80 percent of of the losers in asymmetric wars never switch strategies. Part of the reason combatants don’t switch is that when training and equipment are developed for one strategy, it’s often costly to shift to another. Leaders or organizational traditions also stand in the way of adopting new strategies. This type of inertia often prevents an organization from pursuing the strategy that offers the best chance of winning.” (186)
The next part talks about the art of good guesswork, and provides some principles to help focus our efforts. “Once something has occurred and we can put together a story to explain it, it starts to seem like the outcome was predestined. Statistics don’t appear to our need to understand cause and effect, which is why they are so frequently ignored or misinterpreted. Stories, on the other hand, are a rich means to communicate precisely because they emphasize cause and effect.” (214) I would add that it’s important to look at the data, and not just go off of intuition. “Deliberate practice works when skill dominates, while a focus on process and probability is appropriate when luck is the greater force. Further an appreciation for reversion to the mean allows us to make a more thoughtful assessment of what will happen next.” (215) He essentially says that we should focus on the process for noisy outcomes, which sounds good. To a degree, a good process is one that results in good outcomes, though, and if it’s hard to measure whether an outcome was good randomly or because of the steps in the process, how do we know if it is actually good or not?
Overall, this is an ok book, pulling in aspects of Daniel Kahneman, Nassim Taleb, and Nate Silver. I thought their books were a little more rigorous, with examples that had less logical holes in them, and were at a higher, almost more academic, standard. That being said, I think Mauboussin pulled a lot of interesting information together and made some interesting points about the role that skill and luck play in a variety of contexts.
He begins the book by defining Luck. “Luck is a chance occurrence that affects a person or a group (e.g., a sports team or a company). Luck can be good or bad. Furthermore, if it is reasonable to assume that another outcome was possible, then a certain amount of luck is involved. In this sense, luck is out of one’s control and unpredictable.” (13) He further clarifies the difference between luck and skill. “The consequences of our efforts, both good and bad, reflect an element within our control – skill – and an element outside of our control – luck. In this sense, luck is a residual: it’s what is left over after you’ve subtracted skill from an outcome.” (16) He then talks about skill a little bit (19) and describes the continuum of activities that are lucky, like gambling, versus activities that are very heavily reliant on skill, like running races or playing chess or checkers. “In considering skill, it’s also important to distinguish between experience and expertise. There is an unspoken assumption that someone doing something for a long time is an expert. In activities that depend largely on skill, though, expertise comes only through deliberate practice, and very few individuals are willing to commit the time and effort to go beyond a plateau of performance that’s good enough. The fact is, most of us generally don’t need performance that’s better than good enough.” (22) He then talks about the difference between the necessary sample size for activities that are mostly skill and those that are mostly luck (to differentiate what Nate Silver would call the signal from the noise). “Here’s the main point: if you have an activity where the results are nearly all skill, you don’t need a large sample to draw reasonable conclusions. A world-class sprinter will beat an amateur every time and it doesn’t take a long time to figure that out. But as you move left on the continuum between skill and luck, you need an ever-larger sample to understand the contributions of skill (the causal factors) and luck. In a game of poker, a lucky amateur may beat a pro in a few hands, but the pro’s edge would become clear as they played more hands.” (26) I would probably use different terms, like talking about the true relationship and the randomness that exists about it, but it’s fairly intuitive. He later talks about why it is hard to distinguish luck from skill. He covers creeping determinism. “This is the propensity of individuals to ‘perceive reported outcomes as having been relatively inevitable.’ Even if a fog of uncertainty surrounded an event before it unfolded, once we know the answer, that fog not only melts away, but the path the world followed appears to be the only possible one. Here is how all of this relates to skill and luck: even if we acknowledge ahead of time that an event will combine skill and luck in some measure, once we know how things turned out, we have a tendency to forget about luck. We string together the events into a satisfying narrative, including a clear sense of cause and effect, and we start to believe that what happened was preordained by the existence of our own skill.” (38) This is an important point, and one that definitely relates to investing. He continues to talk about how we focus disproportionally on the things that went well without sufficiently investigating the context and the things that went wrong – the undersampling of failure. “He argues that one of the main ways that companies learn is by observing the performance and characteristics of successful organizations. The problem is that firms with poor performance are unlikely to survive, so they are inconspicuously absent from the group that any one person observes…Since we draw our sample from the outcome, not the strategy, we observe the successful company and assume the strategy was good.” (39) It’s the issues of looking at who did well, and seeing what they had in common as opposed to seeing who did well, and seeing what percentage that is of all the companies that had a similar strategy. He then talks about whether skill in one place is transferable to another. He cites research saying that punters perform just as well when they transfer teams, but it’s not as much the case with wide receivers. This can also be the case in a business environment. “Star analysts who switched employers paid a high price for jumping ship relative to comparable stars who stayed put: overall, their job performance plunged sharply and continued to suffer for at least five years after moving to a new firm. He considered a number of explanations for the deterioration in performance and concluded that the main factor was that they left behind a good fit between their skills and the resources of their employer.” (45) He again talks about the importance of sample size. “We’re naturally inclined to believe that a small sample is representative of a larger sample. In other words, we expect to see what we’ve already seen. This fallacy can run in two directions. In one direction, we observe a small sample and believe, falsely, that we know what all of the possibilities look like. This is the classic problem of induction, drawing general conclusions from specific observations.” (49) He also talks about the gambler’s fallacy, where we think that if things go bad for long enough then they are bound to turn around and be better in the future. He then talks about how the outcome of an event is like the combination of balls from two jars (52): one being luck and the other being skill. Depending on what you pull, you can be skilled, but still have a negative outcome based on the luck number you draw, but as the sample sizes increase, the ones with more skill will tend to do better than those with less skill, as the total impact of luck converges to the mean for everyone involved. He then goes into some detail about how different activities lie in different places across the skill/luck continuum.
The next portion talks about the arc of skill, and how there are optimal ages for different types of decisions. “When we age, we tend to avoid exerting too much cognitive effort and deliberating extensively over a decision that needs to be made. We gradually come to rely more on rules of thumb. This means that we make poorer choices in environments that are complex and unstable. Business and investing are examples of realms where intuition often fails. Researchers who studied people making investments found that decisions about those investments grew less wise as people aged.” (97)
The book then goes into the many shapes of luck. Sometimes there are familiar patters, like trending or mean reversion. He talks a little bit about the hot hand in basketball. “Statisticians have a name for the normal ups and downs that you should expect when the distribution of luck is known: common –cause variation. For example, common-cause variation can explain most of the changes in Adam Jones’s batting average during the season. It also applies to the output of manufacturing processes and to winning the lottery. In economics, common-cause variation is akin to risk.” (115) They also go into power laws a little bit. “One of the key features of distributions that follow a power law is that there are very few large values and lots of small values. As a result, the idea of an “average” has no meaning.” (117) Averages are more meaningful in data that does not have such a wide distribution. They make the point that you can still look at average height if Bill Gates moves into the neighborhood, but average wealth is no longer meaningful. They also talk about cumulative effects of randomness, and call it the Matthew Effect after a verse from the book of Matthew “For whosoever hath, to him shall be given, and he shall have more abundance: but whosoever hath not, from him shall be taken away even that he hath.” (118) They discuss how two similarly skilled people who get slightly different jobs can end up in very different places 10 or 15 years later. “But the Matthew effect explains how two people can start in nearly the same place and end up world apart. In these kinds of systems, initial conditions matter. And as time goes on, they matter more and more.” (118) Small differences can become magnified over time, depending on the environment.
Next, they spend some time talking about what makes a useful statistic. Essentially, a statistic that has little randomness and high predictive power is more useful than the opposite.
When it comes to building skill, they talked about how effort is important to learn new things. “That said, the claim that talent plays no role in how well people do is not supported by the facts. High performance combines a dash of basic ability with lots of perspiration.” (162) Checklists are also useful to ensure that we build skills the right way. “Checklists are highly effective but underutilized in jobs that combine probabilistic tasks with tasks that follow a set of rules or set procedures. Here’s the reason: professionals in these fields think of themselves as practicing a craft and actually find it demeaning to resort to a checklist. They think they have the knowledge to do the job and do not need any aids. They are wrong, and their attitude is costly.” (163) Checklists don’t replace knowledge, but help people focus their attention, especially at times when things are hectic.
The next section discusses how to deal with luck. To help illustrate this, they introduce us to the Colonel Blotto game, and talk about how it’s important for those that have an advantage to simplify the game, and for those who don’t have the advantage to try to make it as complex and on as many fronts as possible to try to make it so that there is a way that they can get an advantage somewhere. For an overmatched opponent to win, it’s imperative that they force the dominant foe to play their game. “Nearly 80 percent of of the losers in asymmetric wars never switch strategies. Part of the reason combatants don’t switch is that when training and equipment are developed for one strategy, it’s often costly to shift to another. Leaders or organizational traditions also stand in the way of adopting new strategies. This type of inertia often prevents an organization from pursuing the strategy that offers the best chance of winning.” (186)
The next part talks about the art of good guesswork, and provides some principles to help focus our efforts. “Once something has occurred and we can put together a story to explain it, it starts to seem like the outcome was predestined. Statistics don’t appear to our need to understand cause and effect, which is why they are so frequently ignored or misinterpreted. Stories, on the other hand, are a rich means to communicate precisely because they emphasize cause and effect.” (214) I would add that it’s important to look at the data, and not just go off of intuition. “Deliberate practice works when skill dominates, while a focus on process and probability is appropriate when luck is the greater force. Further an appreciation for reversion to the mean allows us to make a more thoughtful assessment of what will happen next.” (215) He essentially says that we should focus on the process for noisy outcomes, which sounds good. To a degree, a good process is one that results in good outcomes, though, and if it’s hard to measure whether an outcome was good randomly or because of the steps in the process, how do we know if it is actually good or not?
Overall, this is an ok book, pulling in aspects of Daniel Kahneman, Nassim Taleb, and Nate Silver. I thought their books were a little more rigorous, with examples that had less logical holes in them, and were at a higher, almost more academic, standard. That being said, I think Mauboussin pulled a lot of interesting information together and made some interesting points about the role that skill and luck play in a variety of contexts.
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April 2, 2016People with 20-15 vision can see a distance of 20 feet as well as an average person can see a distance of 15 feet. A measure of 20-8 considered the limit of human ability. The average baseball player has 20-13 vision & a couple players have 20-9, approaching the human limit.
You always stand when you have 17, but if you have 16, you take another card only if the dealer has a 7 or higher.
Reversion to the mean is most pronounced at the extremes, so the 1st lesson is to recognize that when you see extremely good or bad results, they are unlikely to continue that way. The next thing that happens will probably be close to the average of all things that happened.
1 way to avoid hindsight bias is to engage in counterfactual thinking, a carful consideration of what could have happened but didn't.
A classic pattern is a long string of small gains punctuated by a huge loss. In trading a strategy may deliver profits that appear to be steady. This consistency may even encourage the trader to borrow $ to enhance his modest gains. A long string of success, however, can lull the trader into thinking they have a foolproof strategy until-thud!-it leads to a large loss.
The basic challenge is that our minds naturally assign causes to all that we see, whether an event is the result of skill or luck. A + outcome on the skill side of the continuum should clearly be chalked up to good skill, but our minds are lazy enough to attribute a good result on the luck side to skill as well.
Recency bias says that we weight recent information more heavily than a body of past evidence. We tend to overrate players who have done well recently even if they did poorly in the past. Sample size bias is related. The natural tendency is to extract more meaning from small samples than the data warrant.
dumb $ effect-buying high & selling low cost investors 1% of their returns each year, a sizeable sum. Institutional investors do the same thing.
When strong & weak nations go toe-to-toe, the weak lose roughly 80% of the time because "there is nothing to medicate or deflect a strong player's power advantage." When weak nations choose a different strategy, + the # of battlefields, they lose less than 40% of the time. Weak nations have been winning more conflicts by refusing to fight on the strong country's terms improves their changes of victory.
When a new company comes along & tries to beat the leading company @ its own game by introducing another version of the same product, the attempt will fail.
Japanese auto-mobile manufacturers, including Toyota & Honda, entered the market in the 1970s with cars that were small & cheap. The 3 big auto makers just laughed. It wasn't a creditable threat. The leading companies tend to leave the low end & aim for the bigger profits @ the high end of the market. They get blindsided when the disruptors gradually improve their product & stealthily move upwards in the marketplace. If successful they will begin the steal market share @ a lower cost.
Loss aversion -we suffer roughly 2 times more from a loss than we gain of the same size. The commination of the reference point & loss aversion leads investors to hold on to losing stocks & sell winners, because it is painful to take losses.
Mutual fund portfolio compared to its benchmark, has fallen from 75% IN 1980 TO ABOUT 60% IN 2010 in the US. Leaders in sports as well as business fear straying too far from convention, even in cases where the convention isn't all that great.
Threshold of intelligence that individuals must reach in order to achieve high performance in cognitive realms (typically an intelligence quotient of 120, roughly the top 10% of the population) but that anything beyond that threshold does not confer any advantage. Children who scored in the 99.9th percentile on the math section of the SAT Reasoning Test @ age 13 were 18 times more likely to earn a PhD in math or science than children who scored in the 99.1 percentile. In activities that are largely a matter of skill, basic ability counts.
A man who runs a marathon in 4 hours when he is 35 can expect to run it in 5 hours & 18 minutes when he is 70, a 32% decline in performance. A man's chess game, in contrast, is projected to only decline 7% between ages 35 & 70. Experts require 10,000 hours of deliberate practice. The amount of practice required to achieve the level of chess master ranged from 3,000 to 23,600 hours. The overall average was 6,700.
Useful statistics are persistent, which means what happens in the present is similar to what happened in the past. Also predictive of the goal you seek.
More skill gives people an edge in attaining success, but like the red marbles that started out in the majority, that edge offers no assurance that they will end up on top.
When the forces of social influence are at work, we get + feedback that makes the strong get stronger & the weak get weaker. Who benefits from the process of amplification has a lot to do with luck.
The fundamental attribution error occurs when we overestimate how much another person's behavior can be explained by dispositional factors. The error is the tendency to base our explanation of what happens on an individual's skill rather than the situation.
For every dollar you put in a slot machine, it returns between .80 & .98 cents.
If luck contributes 48% to the game of football, then models used to predict scores should be accurate about 75% of the time. This is consistent with the performance of various computer models & odds makers.
The contribution of luck in some professional sports leagues; Basketball 12%, Soccer 31%, Baseball 34%, Football 38%, Hockey 53%.
Sports where the players get the ball more have enough changes to exercise that skill & to therefor nullify the effects of luck.
The age of peak performance depends on the sport. The blend of slow-twitch & fast-twitch fibers in muscles is a good way to determine the peak. With aging, the fast-twitch fibers shrink in both size & numbers. Slow-twitch fibers tend to maintain their size & number far longer. Peak performance comes sooner for sports that require power & speed than it does for sports that relay more on endurance & coordination.
When we age, we tend to avoid exerting too much cognitive effort & deliberating extensively over a decision that needs to be made. We gradually come to rely more on rules of thump. This means that we make poorer choices in environments that are complex & unstable. Business & investing are examples of realms where intuition often fails.
Average age of peak performance in matters of finance is 53.
1/2 the population of people ages 80-89 & 3/4 of those 90 & older have dementia or cognitive impairment.
David Laibson calculated that the net worth of Americans 65 & older approaches $20 trillion, so an enormous amount of wealth is controlled by individuals who have deteriorating ability to make good decisions, either as the result of normal aging or because of cognitive impairment.
The peak in Picasso's productivity came when he was 26 years old, & his pieces from that time period are the most valuable of all his work.
Power law comes from the fact that an exponent (or power) determines the slope of the line. Take book sales as an illustration. Of millions of titles available, the top 10 each sell more than a million copies a year, while a million titles each sell fewer than 100.
In sociology, the Matthew effect (or accumulated advantage) is the phenomenon where "the rich get richer and the poor get poorer." Explains how 2 people can start in nearly the same place & end up worlds apart. In these kinds of systems, initial conditions matter. And as time goes on, they matter more & more.
The higher level of persistence tells us that the # of times a player gets on base will tell us more about his skill than his batting average. The A's built a winning team on the cheap by finding players whose skills were underpriced. A's used a refined version of on-base % & slugging % (total # of bases % by at-bats). The persistence & predictive value of OPS is even greater than that of on-base.
Individual investors who do not have access to the sophisticated analytical tools that professionals use tend to rely on rating agencies to guide their decisions. The best known of these agencies is Morningstar, Inc., which rates mutual funds on a 5-star scale. Investors put more $ than normal into funds that receive + ratings or upgrades of their ratings, & withdraw $ from funds with low ratings or downgrades of ratings.
Active Share is a measure of the percentage of stock holdings in a manager\'s portfolio that differ from the benchmark index. The researchers conclude that managers with high Active Share outperform their benchmark indexes and that Active Share significantly predicts fund performance.
Closet indexing is often viewed negatively by investors because they could simply choose an index fund and pay lower fees. Consistently deliver returns below that of the benchmark, but not by a wide margin.
You always stand when you have 17, but if you have 16, you take another card only if the dealer has a 7 or higher.
Reversion to the mean is most pronounced at the extremes, so the 1st lesson is to recognize that when you see extremely good or bad results, they are unlikely to continue that way. The next thing that happens will probably be close to the average of all things that happened.
1 way to avoid hindsight bias is to engage in counterfactual thinking, a carful consideration of what could have happened but didn't.
A classic pattern is a long string of small gains punctuated by a huge loss. In trading a strategy may deliver profits that appear to be steady. This consistency may even encourage the trader to borrow $ to enhance his modest gains. A long string of success, however, can lull the trader into thinking they have a foolproof strategy until-thud!-it leads to a large loss.
The basic challenge is that our minds naturally assign causes to all that we see, whether an event is the result of skill or luck. A + outcome on the skill side of the continuum should clearly be chalked up to good skill, but our minds are lazy enough to attribute a good result on the luck side to skill as well.
Recency bias says that we weight recent information more heavily than a body of past evidence. We tend to overrate players who have done well recently even if they did poorly in the past. Sample size bias is related. The natural tendency is to extract more meaning from small samples than the data warrant.
dumb $ effect-buying high & selling low cost investors 1% of their returns each year, a sizeable sum. Institutional investors do the same thing.
When strong & weak nations go toe-to-toe, the weak lose roughly 80% of the time because "there is nothing to medicate or deflect a strong player's power advantage." When weak nations choose a different strategy, + the # of battlefields, they lose less than 40% of the time. Weak nations have been winning more conflicts by refusing to fight on the strong country's terms improves their changes of victory.
When a new company comes along & tries to beat the leading company @ its own game by introducing another version of the same product, the attempt will fail.
Japanese auto-mobile manufacturers, including Toyota & Honda, entered the market in the 1970s with cars that were small & cheap. The 3 big auto makers just laughed. It wasn't a creditable threat. The leading companies tend to leave the low end & aim for the bigger profits @ the high end of the market. They get blindsided when the disruptors gradually improve their product & stealthily move upwards in the marketplace. If successful they will begin the steal market share @ a lower cost.
Loss aversion -we suffer roughly 2 times more from a loss than we gain of the same size. The commination of the reference point & loss aversion leads investors to hold on to losing stocks & sell winners, because it is painful to take losses.
Mutual fund portfolio compared to its benchmark, has fallen from 75% IN 1980 TO ABOUT 60% IN 2010 in the US. Leaders in sports as well as business fear straying too far from convention, even in cases where the convention isn't all that great.
Threshold of intelligence that individuals must reach in order to achieve high performance in cognitive realms (typically an intelligence quotient of 120, roughly the top 10% of the population) but that anything beyond that threshold does not confer any advantage. Children who scored in the 99.9th percentile on the math section of the SAT Reasoning Test @ age 13 were 18 times more likely to earn a PhD in math or science than children who scored in the 99.1 percentile. In activities that are largely a matter of skill, basic ability counts.
A man who runs a marathon in 4 hours when he is 35 can expect to run it in 5 hours & 18 minutes when he is 70, a 32% decline in performance. A man's chess game, in contrast, is projected to only decline 7% between ages 35 & 70. Experts require 10,000 hours of deliberate practice. The amount of practice required to achieve the level of chess master ranged from 3,000 to 23,600 hours. The overall average was 6,700.
Useful statistics are persistent, which means what happens in the present is similar to what happened in the past. Also predictive of the goal you seek.
More skill gives people an edge in attaining success, but like the red marbles that started out in the majority, that edge offers no assurance that they will end up on top.
When the forces of social influence are at work, we get + feedback that makes the strong get stronger & the weak get weaker. Who benefits from the process of amplification has a lot to do with luck.
The fundamental attribution error occurs when we overestimate how much another person's behavior can be explained by dispositional factors. The error is the tendency to base our explanation of what happens on an individual's skill rather than the situation.
For every dollar you put in a slot machine, it returns between .80 & .98 cents.
If luck contributes 48% to the game of football, then models used to predict scores should be accurate about 75% of the time. This is consistent with the performance of various computer models & odds makers.
The contribution of luck in some professional sports leagues; Basketball 12%, Soccer 31%, Baseball 34%, Football 38%, Hockey 53%.
Sports where the players get the ball more have enough changes to exercise that skill & to therefor nullify the effects of luck.
The age of peak performance depends on the sport. The blend of slow-twitch & fast-twitch fibers in muscles is a good way to determine the peak. With aging, the fast-twitch fibers shrink in both size & numbers. Slow-twitch fibers tend to maintain their size & number far longer. Peak performance comes sooner for sports that require power & speed than it does for sports that relay more on endurance & coordination.
When we age, we tend to avoid exerting too much cognitive effort & deliberating extensively over a decision that needs to be made. We gradually come to rely more on rules of thump. This means that we make poorer choices in environments that are complex & unstable. Business & investing are examples of realms where intuition often fails.
Average age of peak performance in matters of finance is 53.
1/2 the population of people ages 80-89 & 3/4 of those 90 & older have dementia or cognitive impairment.
David Laibson calculated that the net worth of Americans 65 & older approaches $20 trillion, so an enormous amount of wealth is controlled by individuals who have deteriorating ability to make good decisions, either as the result of normal aging or because of cognitive impairment.
The peak in Picasso's productivity came when he was 26 years old, & his pieces from that time period are the most valuable of all his work.
Power law comes from the fact that an exponent (or power) determines the slope of the line. Take book sales as an illustration. Of millions of titles available, the top 10 each sell more than a million copies a year, while a million titles each sell fewer than 100.
In sociology, the Matthew effect (or accumulated advantage) is the phenomenon where "the rich get richer and the poor get poorer." Explains how 2 people can start in nearly the same place & end up worlds apart. In these kinds of systems, initial conditions matter. And as time goes on, they matter more & more.
The higher level of persistence tells us that the # of times a player gets on base will tell us more about his skill than his batting average. The A's built a winning team on the cheap by finding players whose skills were underpriced. A's used a refined version of on-base % & slugging % (total # of bases % by at-bats). The persistence & predictive value of OPS is even greater than that of on-base.
Individual investors who do not have access to the sophisticated analytical tools that professionals use tend to rely on rating agencies to guide their decisions. The best known of these agencies is Morningstar, Inc., which rates mutual funds on a 5-star scale. Investors put more $ than normal into funds that receive + ratings or upgrades of their ratings, & withdraw $ from funds with low ratings or downgrades of ratings.
Active Share is a measure of the percentage of stock holdings in a manager\'s portfolio that differ from the benchmark index. The researchers conclude that managers with high Active Share outperform their benchmark indexes and that Active Share significantly predicts fund performance.
Closet indexing is often viewed negatively by investors because they could simply choose an index fund and pay lower fees. Consistently deliver returns below that of the benchmark, but not by a wide margin.
July 19, 2025
Of the three books I have read by Michael J. Mauboussin -- The Success Equation, Expectations Investing: Reading Stock Prices for Better Returns, Revised and Updated, and More Than You Know: Finding Financial Wisdom in Unconventional Places -- this one is hands down the best. It succeeds where others fall short because it stays on point with a core idea: how to distinguish luck from skill, how to measure skill, and how to build a process for improving skill. Alas, in investing, skill matters, but feedback is inconsistent, slow, and may be misleading. You have to live the mantra of trusting the process, even when it hurts sometimes.
- "When luck has little influence, a good process will always have good outcome. When measure of luck is involved, a good process will have a good outcome but only over time." p.19
- "If history is written by the winners, history is also written about the winners, because we like to see clear cause and effect. Luck is boring as the driving force in a story." p. 59
- "In activities strongly influenced by skill, feedback is generally clear. When luck stands between cause and effect, giving and receiving quality feedback becomes much more difficult." p. 72
- "Fluid intelligence refers to the ability to solve problems that you've never seen before... Crystallized intelligence is the ability to use knowledge accumulated through learning... There is a decline of about one percentage point [in fluid intelligence] each year after the age of twenty... The good news is that crystallized intelligence tens to improve with age... Growing knowledge compensates for a reduction in fluidity, up to a certain age." p. 98-99
- "A path-dependent process is one in which what happens next depends on what happened before. It's a process that, in effect, has memory. These processes are very sensitive to initial conditions and lead to phenomena such as the rich getting richer and the poor getting poorer... [Known as the Matthew effect, it] explains how two people can start in nearly the same place and end up worlds apart... Preferential attachment locks in the result." p. 118-120
- "In investing, as in other activities that are heavily probabilistic, process trumps outcomes." p. 151
- "Sometimes the consensus is right. The goal is to be a contrarian when it allows you to gain an edge, and the calculator helps you ensure a margin of safety." p. 172
- "When competing one-on-one, follow two simple rules: If you are the favorite, simplify the game. If you are the underdog, make it more complicated." p. 178
- "Do not define your ultimate success by the frequency of gains, but rather by how much you make when you are right versus how much you lose when you are wrong." p. 194
- "Where luck plays a strong role, the focus must be on process... where luck has a stronger force, the link between process and outcome is broken... since a good process offers the highest probability of a good outcome over time, the emphasis has to be on process." p. 222
- "When luck has little influence, a good process will always have good outcome. When measure of luck is involved, a good process will have a good outcome but only over time." p.19
- "If history is written by the winners, history is also written about the winners, because we like to see clear cause and effect. Luck is boring as the driving force in a story." p. 59
- "In activities strongly influenced by skill, feedback is generally clear. When luck stands between cause and effect, giving and receiving quality feedback becomes much more difficult." p. 72
- "Fluid intelligence refers to the ability to solve problems that you've never seen before... Crystallized intelligence is the ability to use knowledge accumulated through learning... There is a decline of about one percentage point [in fluid intelligence] each year after the age of twenty... The good news is that crystallized intelligence tens to improve with age... Growing knowledge compensates for a reduction in fluidity, up to a certain age." p. 98-99
- "A path-dependent process is one in which what happens next depends on what happened before. It's a process that, in effect, has memory. These processes are very sensitive to initial conditions and lead to phenomena such as the rich getting richer and the poor getting poorer... [Known as the Matthew effect, it] explains how two people can start in nearly the same place and end up worlds apart... Preferential attachment locks in the result." p. 118-120
- "In investing, as in other activities that are heavily probabilistic, process trumps outcomes." p. 151
- "Sometimes the consensus is right. The goal is to be a contrarian when it allows you to gain an edge, and the calculator helps you ensure a margin of safety." p. 172
- "When competing one-on-one, follow two simple rules: If you are the favorite, simplify the game. If you are the underdog, make it more complicated." p. 178
- "Do not define your ultimate success by the frequency of gains, but rather by how much you make when you are right versus how much you lose when you are wrong." p. 194
- "Where luck plays a strong role, the focus must be on process... where luck has a stronger force, the link between process and outcome is broken... since a good process offers the highest probability of a good outcome over time, the emphasis has to be on process." p. 222
September 18, 2024
This book emphasizes the importance of differentiating between skill and luck in outcomes, and the importance of quantifying the proportion of each in decision making. Most of us don’t consider luck as a factor at all in outcomes, even though in many cases luck is predominant. We like to attribute good outcomes to our skill and bad outcomes to other factors. We like to assign a cause even when the cause is unclear or random. These are normal human biases and tendencies that serve us well sometimes but can lead to bad decision making in some circumstances. Most decision making neglects important aspects of randomization such as reversion to the mean, or applies known biases to means reversion.
I felt like this book had important information and learnings and I tried very hard to connect the concepts presented into practical uses, but had trouble doing so. The writing didn’t connect with me and I found it hard to translate the interesting concepts presented into something I could use in my life to improve decision making. One concept described was that when you have an advantage in skill level over an opponent, you should simplify your strategy. If you’re the underdog, do the opposite and use complex and unorthodox strategies because this introduces more luck (randomness) and gives you the best chance against a stronger opponent. He gave interesting examples of this in the context of war and strategy games, but I think some specific practical examples for individuals would have helped. Most of his examples used sports and how teams could predict their skill level in relation to luck. It’s not too dry of a read even though it’s full of statistical analysis. In the end it felt like a missed opportunity for me to pull much expertise from this author, who clearly has a lot to share.
I felt like this book had important information and learnings and I tried very hard to connect the concepts presented into practical uses, but had trouble doing so. The writing didn’t connect with me and I found it hard to translate the interesting concepts presented into something I could use in my life to improve decision making. One concept described was that when you have an advantage in skill level over an opponent, you should simplify your strategy. If you’re the underdog, do the opposite and use complex and unorthodox strategies because this introduces more luck (randomness) and gives you the best chance against a stronger opponent. He gave interesting examples of this in the context of war and strategy games, but I think some specific practical examples for individuals would have helped. Most of his examples used sports and how teams could predict their skill level in relation to luck. It’s not too dry of a read even though it’s full of statistical analysis. In the end it felt like a missed opportunity for me to pull much expertise from this author, who clearly has a lot to share.
April 2, 2018
I was reading some random thing that led to some random thing that led to someone quoting this book, specifically where certain sports lie on the luck-skill spectrum. I found this intriguing, so I grabbed a copy from the library.
The way luck contributes to success is a fascinating subject and Mauboussin handles it well, carefully explaining not only the math but the psychology that comes into play when people try to understand wins versus losses. A fascinating subject, and a little disheartening, as it seems luck is much more prevalent that one would have guessed.
Luck is nothing more than a word for the unknowns that impact outcome to some benefit or detriment. So really, what Mauboussin does in this book is point out that we know less than we think we do when we say why something occurred. Experts can't earn a living if they say "I don't know," and so entire industries are built around what is essential guessing.
The Success Equation, as a read, was perhaps a little longer than it needed to be, in my opinion, and each chapter ends with a recap of the point made, or a summary, but no real logical conclusion. Mauboussin used plenty of examples to illustrate various statistical phenomena, but I would have liked more.
But, like I said, it was worth reading. If you enjoy books like Moneyball and Thinking Fast, Thinking Slow, you'll enjoy this book too.
The way luck contributes to success is a fascinating subject and Mauboussin handles it well, carefully explaining not only the math but the psychology that comes into play when people try to understand wins versus losses. A fascinating subject, and a little disheartening, as it seems luck is much more prevalent that one would have guessed.
Luck is nothing more than a word for the unknowns that impact outcome to some benefit or detriment. So really, what Mauboussin does in this book is point out that we know less than we think we do when we say why something occurred. Experts can't earn a living if they say "I don't know," and so entire industries are built around what is essential guessing.
The Success Equation, as a read, was perhaps a little longer than it needed to be, in my opinion, and each chapter ends with a recap of the point made, or a summary, but no real logical conclusion. Mauboussin used plenty of examples to illustrate various statistical phenomena, but I would have liked more.
But, like I said, it was worth reading. If you enjoy books like Moneyball and Thinking Fast, Thinking Slow, you'll enjoy this book too.
April 20, 2024
Overall, this book provided a helpful framework for confronting the often intractable problem of causal attribution. Mauboussin approached the issue through the lens of disentangling the impacts of skill and luck in a given instance across the arenas of sports, business and investing. I thought the book was well structured, providing the overall framework and then breaking down different components to drill deeper into the application, supporting evidence, implications and extensions. This book was also firmly grounded in the real world, with a with ranging collection of anecdotes and examples from across the three arenas studied. I felt these were critical in making the general ideas such as a system for comparing what actually happened to what would happen in a luck only world easier to apply in practice and more persuasive, acting as a forced reality check on the ideas of the author. In my view the main flaw was that the book was at times repetitive and likely could have been made more concise. Nonetheless, within the short and easy to read book the author was able to pack a lot of information and ideas that I plan to implement in my everyday life, such as the optimal settings to use checklists, how to practice most efficiently and how to approach resource differentials when competing.
June 14, 2021
Nuggets of statistical of wisdom
More a collection of essays, there are still a number of nuggets in the book on how to use data.
1. The paradox of skill - as the average level of skill in a population increases, the role of luck becomes more importance, because the variance between the actors shrinks.
2. It’s possible to tease out luck and skill by looking at the persistence and predicability of a measure on expected outcomes.
3. If the outcomes of an activity are determined by luck, deliberate practice will be difficult because luck creates a wicked learning environment. Focus on process.
4. Statistics are a bad way to evaluate and predict black swan events, which are rare and have complex payouts.
5. People are designed to look for cause and effect, they will create narratives to explain luck. They will falsely attribute lucky outcomes to their own skill.
6. Basketball is the sport where the outcome is most determined by skill. This is because all basketball players are tall (average height 6’6”) so players are selected from a small proportion of the population. This creates more disparities between the average and top players, so top player’s skills have a bigger impact on success.
More a collection of essays, there are still a number of nuggets in the book on how to use data.
1. The paradox of skill - as the average level of skill in a population increases, the role of luck becomes more importance, because the variance between the actors shrinks.
2. It’s possible to tease out luck and skill by looking at the persistence and predicability of a measure on expected outcomes.
3. If the outcomes of an activity are determined by luck, deliberate practice will be difficult because luck creates a wicked learning environment. Focus on process.
4. Statistics are a bad way to evaluate and predict black swan events, which are rare and have complex payouts.
5. People are designed to look for cause and effect, they will create narratives to explain luck. They will falsely attribute lucky outcomes to their own skill.
6. Basketball is the sport where the outcome is most determined by skill. This is because all basketball players are tall (average height 6’6”) so players are selected from a small proportion of the population. This creates more disparities between the average and top players, so top player’s skills have a bigger impact on success.
June 5, 2023
A good introduction into statistical analysis. It focuses on sports, business, investing, and gambling. I say introduction because it provides a bit of a back story for each section as a way to present the problem before the analysis is provided. For sports specifically, I think the style is a good way to bridge the gap between sports fans and statistical analysis.
I found the luck-skill continuum thought-provoking, and I have brought it up to many of my sports watching friends as a fun conversation on which sports seem to be more or less luck based. Typical of sports fans, it definitely led to some fun arguments when I brought up the results this book provided. Of course, it's important to remember that the results are not gospel.
I loved the persistence and predictive analysis of individual statistics in order to find which statistics are more useful than others. I've used the exact same approach on my own for my own analysis.
Overall, it's a really good book, and it started my journey down the path of statistical analysis in sports. If you are not new to this, you can probably skip over it or skim it at most.
I found the luck-skill continuum thought-provoking, and I have brought it up to many of my sports watching friends as a fun conversation on which sports seem to be more or less luck based. Typical of sports fans, it definitely led to some fun arguments when I brought up the results this book provided. Of course, it's important to remember that the results are not gospel.
I loved the persistence and predictive analysis of individual statistics in order to find which statistics are more useful than others. I've used the exact same approach on my own for my own analysis.
Overall, it's a really good book, and it started my journey down the path of statistical analysis in sports. If you are not new to this, you can probably skip over it or skim it at most.
June 4, 2020
Are you lucky or skillful: Can you tell the difference?
Mauboussin works as a strategist in the financial services industry and has taught at the Columbia Graduate School of Business.
With this in mind, The Success Equation illustrates how simple statistical concepts like standard deviations, base-rate, and weightings, can be parlayed into predicting and analyzing the outcomes and performance of professional sports teams or stock picks.
Traversing the grey area between skill and luck, because "few of us are well versed in statistics," Mauboussin enquires into areas like Lotto numbers. He asks, is picking them a skill, luck, or precision? Drawing on concepts like Daniel Kahneman's seminal paper "The Psychology of Prediction" lends this book credibility and authenticity.
Published by Harvard Business Review Press ensures that the content never strays too far off the beaten track. As a business major, a sometime punter on horses, and investor, I found it an informative and engaging read.
Mauboussin works as a strategist in the financial services industry and has taught at the Columbia Graduate School of Business.
With this in mind, The Success Equation illustrates how simple statistical concepts like standard deviations, base-rate, and weightings, can be parlayed into predicting and analyzing the outcomes and performance of professional sports teams or stock picks.
Traversing the grey area between skill and luck, because "few of us are well versed in statistics," Mauboussin enquires into areas like Lotto numbers. He asks, is picking them a skill, luck, or precision? Drawing on concepts like Daniel Kahneman's seminal paper "The Psychology of Prediction" lends this book credibility and authenticity.
Published by Harvard Business Review Press ensures that the content never strays too far off the beaten track. As a business major, a sometime punter on horses, and investor, I found it an informative and engaging read.
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