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N.E. Toksoy
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Dota 2 is one of the most popular MOBA (Multiplayer Online Battle Arena) games being played today. A Dota 2 match is played by two teams of 5 players. The main goal of the game is to destroy the opposing team’s Ancient tower, the team that manages to do so, wins the game. An essential part of a match is the hero selection phase before it starts. There are different ways to select heroes in different game modes, but the game mode that is used for this research is the Captain’s mode where each team is assigned a captain and the captains take turns picking and banning heroes. The main question that this research aims to answer is: “What is the effect of the Pudge hero being picked in a team on the outcome of a Dota 2 game?” Causal inference, a discipline that is concerned with discovering causal relationships using data analysis under certain assumptions about the data is used in this research to measure this effect. More specifically, the g-formula is the causal inference method of choice for this research. The data that is used for this research is gathered through the OpenDota API. After running the correctly formatted data through the g-formula implementation, the effect of the Pudge hero being picked in a team on the game outcome was estimated as -0.2848%. Meaning that, on average, there is a 0.2848% less chance of a team winning the game, if the Pudge hero is in that team.
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Dota 2 is one of the most popular MOBA (Multiplayer Online Battle Arena) games being played today. A Dota 2 match is played by two teams of 5 players. The main goal of the game is to destroy the opposing team’s Ancient tower, the team that manages to do so, wins the game. An essential part of a match is the hero selection phase before it starts. There are different ways to select heroes in different game modes, but the game mode that is used for this research is the Captain’s mode where each team is assigned a captain and the captains take turns picking and banning heroes. The main question that this research aims to answer is: “What is the effect of the Pudge hero being picked in a team on the outcome of a Dota 2 game?” Causal inference, a discipline that is concerned with discovering causal relationships using data analysis under certain assumptions about the data is used in this research to measure this effect. More specifically, the g-formula is the causal inference method of choice for this research. The data that is used for this research is gathered through the OpenDota API. After running the correctly formatted data through the g-formula implementation, the effect of the Pudge hero being picked in a team on the game outcome was estimated as -0.2848%. Meaning that, on average, there is a 0.2848% less chance of a team winning the game, if the Pudge hero is in that team.