survivor_contestants.csv
785 rows104.32 KB
Rowboat Guide
Easily spot subsets you want to explore.
What makes a winner on Survivor?
We’ll investigate over 40 seasons of contestant
demographic data from different angles.
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Ellory
Jeff Probst’s Protégé
Survivor is a last-person-standing competition show involving social manipulation, endurance challenges, and a $1,000,000 cash prize—it’s basically the perfect show.
One of my favorite things about Survivor is that it draws in contestants from a wide range of backgrounds, professions, and personalities. This, combined with the largely unchanged format of the show over its 20+ year run, makes it the perfect candidate to explore if there are any common trends among those who play the game and those who win.
To start the search, let’s look at Survivor champions from this dataset containing contestant demographic information from 43 seasons of the show.
In the header of the finish column, we can click on the first bar in the histogram to filter to just the rows with a value of 1—narrowing the view to show only the contestants who finished in first place.
With only the winners now in view, we can check out the profession column and see that many of them have socially-oriented jobs, such as first responders, teachers, and hospitality workers.
We can undo our finish: 1 filter by clicking the ← arrow to the left of it.
Looking back at our original view of all the contestants, we can see that attorneys are one of the most highly represented professions, with law students not far behind.
But, if we switch back to our filtered list of winners by clicking the → arrow in the header, it’s a different story.
Searching the profession column for key words like ‘law’, ‘attorney’ and ‘legal’ reveals that there there has been only a single winner working in the legal world—and they were a Harvard law student.
Returning to our view of all contestants by clicking the ← arrow, we can compare other demographic cues such as age and gender.
Looking at those two columns, we can see that there is a nearly 50/50 split between male and female contestants across the 43 seasons in this dataset.
There is also a clear peak in contestant age around their late 20’s.
By selecting the More chart types option in the age column header, we can see that it’s possible to create a stacked histogram by linking together the age and gender columns.
From our stacked histogram, it looks like the ratio of male and female contestants is relatively balanced until age 50, at which point the majority of contestants are male.
Clicking the → arrow to jump to our view of the winning contestants, we can see that this trend is reflected among them as well.
There’s a relatively even gender balance until their late 40’s where we see exclusively male winners—though it is worth noting that women in the 28-30 range are crushing it.
Let’s pivot to a new investigation.
There is one Survivor contestant who has participated in more seasons than any other: Rob Mariano.
Filtering contestant_name to ‘Rob Mariano’, we can get a picture of what’s changed in his life across the five seasons in which he appeared.
Though true fans still know him as “Boston Rob”, at some point between his second and third appearances on the show, he moved from Massachusetts to Florida (and he never actually lived in Boston!).
He has been playing this game on and off for nearly two decades of his life—from age 26 up to his most recent appearance at age 43.
Despite winning one season and coming in second on another, it can’t be said from the data alone that he got better at the game over time.
He initially finished in the middle of the pack, rose to the top two, dropped back down, finally won, and most recently placed near the bottom.
This illustrates what I love about Survivor.
Refining a single strategy will rarely get you far because winning is about being flexible enough to adapt to the unpredictable assortment of people on each season.
Returning to the show over and over again as a fan favorite (like Rob) gives you more experience, but it also puts a target on your back no matter how well you play the game.
People with high emotional intelligence also tend to fare well because they are better suited to the necessary work of navigating complex social relationships to form and maintain alliances within a wide range of personalities.
…It also doesn’t hurt to be young and fit given the intensity of the physical challenges and limited resources for food and shelter.
A large part of data exploration in Rowboat comes from applying (and removing) filters to look at slices of your data.
Even without a deep familiarity with the show, just a few minutes spent comparing subsets of the dataset starts to paint a picture of the people who make Survivor what it is.
survivor_contestants.csv
785 rows104.32 KB
Open in Rowboat