League of Legends Comeback Prediction Dataset

Citation Author(s):
Junhyuk
Lee
Submitted by:
Junhyuk Lee
Last updated:
Tue, 02/18/2025 - 00:41
DOI:
10.21227/aes9-0c53
License:
Creative Commons Attribution
22 Views
Categories:
Artificial Intelligence
Machine Learning
Keywords:
League of Legends, LoL, Game Analytics, MOBA, Esports
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Abstract 

Dataset Description

This dataset is designed for analyzing and predicting comeback victories in Multiplayer Online Battle Arena (MOBA) games. It is derived from match data where an objective bounty mechanism was active, providing features that highlight differences between teams with and without the bounty advantage. The dataset is ideal for machine learning tasks, such as binary classification and feature importance analysis, and it enables researchers and analysts to explore factors influencing comeback scenarios in competitive gaming.

Dataset Contents: 

The dataset includes the following files:

match_data.csv

Contains match-level features derived from differences between teams with and without the objective bounty advantage. Each row represents a single match, labeled with whether a comeback victory occurred.

 

Instructions: 

Variable

Description

Comeback Victory

Whether a comeback victory occurred (1, 0)

Inhibitor

Number of inhibitors destroyed

Jungle Minion

Number of jungle monsters killed

Minion

Number of minions killed

Mountain Drake

Number of Mountain Drakes killed

Chemtech Drake

Number of Chemtech Drakes killed

CloudDrake

Number of Cloud Drakes killed

InfernalDrake

Number of Infernal Drakes killed

OceanDrake

Number of Ocean Drakes killed

HextechDrake

Number of Hextech Drakes killed

Elder Dragon

Number of Elder Dragons killed

Rift Herald

Number of Rift Heralds killed

Baron Nashor

Number of Baron Nashors killed

Champion Kill

Number of champion kills

Champion Assist

Number of champion assists

Ward Place

Number of wards placed

Control Ward Place

Number of control wards placed

Ward Kill

Number of wards killed

Damage Type Ratio

Ratio of physical damage (AD) to magic damage (AP) within the team

Tank Role Count

Number of tanks within the team

Jungle Pressure

Frequency of jungle invades by the jungle player (per minute)

WCM Mean

Weighted average champion mastery of the team's five players, based on recent match records and performance

WCM CV

Weighted coefficient of variation of champion mastery for the team's five players, based on recent match records and performance

CM Top10

A rate quantifying the contribution of skilled players within the team, calculated based on the frequency of selecting the top 10 highest-mastery champions played by team members

Similarity

A metric representing the similarity among team members based on the top 10 highest-mastery champions for each player

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Submitted by Junhyuk Lee on Tue, 02/18/2025 - 00:44

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