Survivorship Bias Trap: Why Success Stories Can Mislead
If you think that achieving success in crypto only requires hard work and persistence, think again. You may be experiencing survivorship bias, a cognitive distortion where significant data, either accidentally or intentionally, is left out of sight.
Survivorship bias is a cognitive shortcut where people notice only successful examples ("survivors") and ignore failures. This distortion often skews statistical research, leading to misleading conclusions: data is analyzed solely based on survivors rather than considering all participants or elements.
This cognitive bias can influence not only scientific research but also your everyday decisions. People tend to focus solely on successful examples, often leading to an overestimation of their significance and unrealistic expectations.
For example, when reading biographies of millionaires, we often view their strategies and behaviors as models to emulate. They may indeed have achieved success through hard work and persistence. However, by focusing only on these success stories, we forget about the thousands who failed despite perhaps using the same approaches.
In this article, we explore the origins of “Survivorship Bias” and look at some of its most common examples, from investing to its impact on mental health.
A Classic Case of Survivorship Bias: Abraham Wald in WWII
During World War II, Allied forces faced the issue of damaged planes returning from combat missions. Aviators noticed that damage was most often found on the wings and tail sections, while the fuselage and engines showed fewer signs of damage.
Analyzing this information, military engineers initially decided to reinforce the sections that were frequently hit. However, this approach was flawed because it ignored a critical piece of data: the planes that didn’t make it back.
In reality, the areas most frequently damaged on returning planes were not necessarily the most vulnerable. In fact, the critical damage that led to crashes typically occurred in less-damaged sections—planes hit in these areas simply didn’t make it back to base.
Survivorship Bias: Damage on returning planes. Source: wikimedia.org
Mathematician Abraham Wald proposed this insight: rather than reinforcing the areas frequently damaged on returning planes, efforts should focus on sections with minimal damage.
This is a classic example of survivorship bias. Analyzing only the data from the “surviving” planes can lead to incorrect conclusions. Wald recognized that information about the planes that didn’t return was far more essential for enhancing their safety.
Cats More Likely to Survive Falls from Higher Floors
In 1987, researchers from the University of Pennsylvania conducted a study on domestic cats that had fallen from various heights, examining data on 132 cats treated at a veterinary hospital after their falls. The findings were surprising: cats that fell from higher floors were more likely to survive than those falling from lower heights.
The study considered multiple factors, including the height of the fall, types of injuries, and survival rates, grouping the cats by fall height. Interestingly, cats falling from heights of seven floors or more often sustained less serious injuries, while those falling from just 2–3 floors frequently suffered severe injuries or even death.
Survival rates by floor height. Source: GN Crypto
Based on this data, scientists hypothesized that cats falling from greater heights have more time to adjust and prepare for landing, allowing them to turn onto their feet and reduce their fall speed, thereby decreasing the severity of injuries.
However, this hypothesis turned out to be incorrect, revealing a classic case of survivorship bias.
In reality, cats that fell from very high floors were more likely to die and, as a result, never made it to the hospital. Therefore, the data on cats falling from high floors represented only part of the overall picture, as the most severe cases simply didn’t make it into the sample.
This statistical paradox is a prime example of survivorship bias, where only data from the “survivors” (in this case, cats brought to the hospital) are analyzed, while those that didn’t survive are excluded from the research.
The Bombard Story
Alain Bombard, a French doctor and adventurer, famously crossed the Atlantic Ocean in 1952 in a small boat without any food or water, relying solely on his own resourcefulness and luck. His journey was successful, and in 1953 he published The Bombard Story, sharing his survival techniques.
Alain Bombard setting out on his Atlantic journey in a small boat. Source: lesothers.com
In his book, Bombard provided various survival tips for those stranded at sea. For instance, he suggested catching plankton and fish for sustenance and proposed defending against sharks by striking them on the head with an oar. These suggestions were widely accepted as reliable survival tactics, and his book became a bestseller.
However, Bombard’s success likely resulted more from luck than from reliable survival strategies. Though he survived using these methods, many sailors argue that such actions could be more harmful than helpful. For example, consuming plankton can lead to poisoning, and aggressive behavior toward sharks may provoke attacks.
Bombard’s story is a textbook example of survivorship bias. His experience was taken at face value, while the stories of those who attempted similar methods but perished remain untold. Survivors are celebrated, while the rest remain unseen in the background of history.
You Don’t Need to Drop Out of College to Succeed
Everyone knows the story of Bill Gates, the founder of Microsoft, who famously left Harvard in 1975 and later became one of the world’s wealthiest people. While inspirational, this story can lead to misleading conclusions. It’s easy to assume that dropping out of college ensures success and that following in Gates’ footsteps will bring similar fortune.
In reality, statistics show that people with higher education levels tend to earn more on average than those without a degree.
Higher education level correlates with higher income. Source: politicsthatwork.com
Many people overlook (and thus don’t consider) the countless others who also dropped out of college but didn’t achieve success. These individuals become part of an invisible statistic—left unnoticed because they didn’t make it onto the “survivor” list.
Meanwhile, the “survivors” go on to write books, give interviews, and speak at conferences, sharing what they believe are the keys to their success. They often advise taking risks, working tirelessly, and being persistent, without acknowledging the role of luck.
Statements like “Work around the clock,” “Take bold risks,” or “Follow this path, and you’ll inevitably succeed” create a misleading impression that success is solely a result of hard work and daring choices. This kind of advice ignores the crucial role that luck and other uncontrollable factors play in shaping outcomes.
In Knowledge Commerce, Only Success Stories Get Highlighted
The survivorship bias is also evident in knowledge commerce. Many self-proclaimed experts sell courses and training programs, claiming that their methods have helped people achieve success. However, they often fail to mention that most of their students didn’t reach the promised outcomes.
For example, on the social media pages of various crypto "gurus," you’ll frequently find hundreds of reposted stories showcasing successful students (like green P&L screenshots, completed challenges at prop firms, or received airdrops). In contrast, stories of students who didn’t succeed are far less commonly shared—if they’re shared at all.
We Only Show What We Want to Show
Once, mentalist Derren Brown claimed he could flip a coin to land on “heads” ten times in a row. He achieved this, but later admitted that he filmed for nine hours to capture the exact moment when the coin finally landed on heads ten consecutive times.
In knowledge commerce, users frequently encounter a similar issue: success stories are showcased, concealing the real statistics and the challenges that most clients actually face.
Cryptocurrencies and Meme Coins: We Only See the “Survivors”
Survivorship bias is also common in the investment world. People often focus on the most profitable stocks or cryptocurrencies, ignoring the hundreds of failed projects. This approach can create the illusion that investing is simple: just buy an asset early, and success is virtually guaranteed.
This bias is especially apparent with the rise of meme coins. Many have heard about the returns from DOGE, PEPE, BONK, NEIRO, and similar assets, but few are aware of the thousands of other meme coins that didn’t make it. The question practically answers itself.
In August 2024, a trader known as Adam_Tech published a report on meme coin returns on pupm.fun—a platform for launching such projects. His findings revealed that the chance of profiting from meme coin investments was just 0.12%, even lower than the odds of winning at a casino.
People rarely talk about their failed investments; instead, they prefer to share only their successful experiences on social media. This approach isn’t limited to investments or professional success—survivorship bias can also influence users' mental well-being.
Social Media: Why Other Lives Seem Better Than Our Own
Social media has become a kind of "online showcase," where users highlight the best moments of their lives—travels, new jobs, purchases, relationships, or successful projects. But failures, disappointments, and challenges often remain hidden.
Over time, this can create the feeling that one’s life is somehow less fulfilling than others’, fostering unwarranted insecurities and feelings of inadequacy. In more severe cases, this trend can even contribute to mental health issues like depression, anxiety, and suicidal thoughts.
The rate of diagnosed depression among teenagers began rising in 2011, around the same time social media became widely popular. Source: ifstudies.org
Renowned psychologist Alfred Adler emphasized that people often compare themselves to those in seemingly more favorable circumstances. However, these comparisons are rarely objective: we don’t see the struggles or the effort behind these successes, nor the setbacks that stayed behind the scenes.
For social media users, it’s essential to remember the impact of survivorship bias, understanding that focusing solely on visible successes can distort our perception of reality. The true picture often lies beyond what’s on display.
Other Examples of Survivorship Bias in Everyday Life
Survivorship Bias and Nostalgia. People often admire the durability of old houses and classic cars still functioning today, concluding that they were built better than their modern counterparts. In reality, only the sturdiest examples survived to this day, while those that fell apart disappeared long ago. Furthermore, the surviving items likely received varying degrees of maintenance over time, which also affects their condition.
Survivorship Bias in Driving Safety. Some believe it’s safer not to wear a seatbelt at high speeds, thinking that being ejected from the vehicle during an accident might reduce injuries. This belief often stems from selective cases where unrestrained drivers have been seen walking away from a crash.
This is a skewed perception: missing from view are the countless cases where not wearing a seatbelt led to fatalities. Remember, seatbelts are proven lifesavers, and buckled drivers and passengers are far more likely to survive a crash.
Survivorship Bias with Dolphins. Stories about dolphins guiding people to shore have become a symbol of their “friendliness.” Yet, we don’t hear about incidents where dolphins may have pushed people out to sea, leading to tragic outcomes. Those who drowned simply aren’t around to share their side of the story.
Survivorship Bias in the News. Newsfeeds focus on tragedies and disasters, making it easy to believe the world is in a constant state of crisis. Positive stories rarely make the headlines, as news is tailored to elicit strong emotional responses.
To avoid survivorship bias, it’s essential to remember that what we see is rarely the full picture. When evaluating an event, consider how many similar cases go unreported.
Awareness and a critical eye can help us recognize the hidden sides of reality often left out of view.
