Game of Thrones

Game of Thrones : An algorithm has predicted who’s most likely to die in Game of Thrones’ final season, After a 20-month absence, “Game of Thrones” stormed back on Sunday night, setting a new ratings record.

The season premiere of the show’s eighth — and final — season had 17.4 million viewers, including viewership through its digital channels, HBO said. The previous record for a single episode of the series was 16.9 million, for the seventh-season finale in August 2017.

HBO had 11.8 million viewers watching it the old-fashioned way on regular television, according to Nielsen. That narrowly missed the record of 12.1 million who watched the seventh-season finale on television.

Death in Game of Thrones has always been gloriously unpredictable. Just when you’re getting to like a character (or, at least, grudgingly respect them), they end up beheaded, impaled, barbecued, or exploded, leaving you wondering: who’s next?

With the final season of the show underway, a team at the Technical University of Munich (TUM) has attempted to answer this question using basic data science and some fancy machine learning.

Their top prediction to survive season 8? None other than the Mother of Dragons herself, Daenerys Targaryen, with a slim 0.9 percent probability of dying. The character most likely to kick the medieval bucket, meanwhile, is everyone’s favorite sellsword: Ser Bronn of the Blackwater, with a 93.5 percent chance of dying.

Game of Thrones Watch Online Full Season


Warning: Spoilers ahead for the previous seasons of Game of Thrones.
Will Bronn ever get his castle? The algorithm says outlook not so good. Image: HBO

To make their predictions, the team at TUM used approaches familiar to medicine and life insurance. They mined statistical information about how long people lived, along with biographical data that might correlate to when they die. In real life, that might include information like whether someone is a smoker or how frequently they exercise. But in the world of Game of Thrones, the more relevant information is what house a particular character belongs to, whether they’re married, and who their allies are.
“The house a character belongs to affects how likely they are to die”

With the help of fan-maintained Wikis, TUM’s data scientists combed through the lives of hundreds of characters. Along with collecting in-universe data like their gender and location, they also included what we might call metadata: information like whether someone is a major or minor character and how often they’re cited in fan Wikipedias.

This data revealed some basic truths about mortality and the Game of Thrones universe, such as the fact that being male is more dangerous than being female. (Men have a 22 percent death rate, compared to 11 percent for women.) Certain houses are more long-lived than others, reflecting their ascendancy in Westeros. Being a Baratheon, for example, makes you 5 percent more likely to die than the average character, while being a Lannister makes you 45 percent more likely to survive.

To turn these trends into predictions for individual characters, the team analyzed this data using two separate models: the first used a fairly straightforward statistical approach known as Bayesian inference, and the second relied on fancier techniques involving machine learning and neural networks.