# CUPID: Improving Battle Fairness and Position Satisfaction in Online MOBA Games with a Re-matchmaking System

arXiv: https://arxiv.org/abs/2406.19720 · HTML: https://mlsanity.com/paper/2406.19720/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 117 references that are in the map.
- First posted on arXiv 28 Jun 2024.

## Builds on (most cited first, 28 of 28)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Densely Connected Convolutional Networks](https://mlsanity.com/paper/1608.06993/) (2016)
- [Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting](https://mlsanity.com/paper/2012.07436/) (2020)
- [Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting](https://mlsanity.com/paper/1907.00235/) (2019)
- [A Transformer-based Framework for Multivariate Time Series Representation Learning](https://mlsanity.com/paper/2010.02803/) (2020)
- [Minimizing Finite Sums with the Stochastic Average Gradient](https://mlsanity.com/paper/1309.2388/) (2013)
- [Mastering Complex Control in MOBA Games with Deep Reinforcement Learning](https://mlsanity.com/paper/1912.09729/) (2019)
- [UFO: A UI-Focused Agent for Windows OS Interaction](https://mlsanity.com/paper/2402.07939/) (2024)
- [Deep Learning in Mobile and Wireless Networking: A Survey](https://mlsanity.com/paper/1803.04311/) (2018)
- [Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation](https://mlsanity.com/paper/2311.04254/) (2023)
- [Sequence-to-point learning with neural networks for nonintrusive load monitoring](https://mlsanity.com/paper/1612.09106/) (2016)
- [ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection](https://mlsanity.com/paper/2307.00754/) (2023)
- [Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection](https://mlsanity.com/paper/2405.15370/) (2024)
- [Spatio-Temporal Urban Knowledge Graph Enabled Mobility Prediction](https://mlsanity.com/paper/2111.03465/) (2021)
- [OmniNet: Omnidirectional Representations from Transformers](https://mlsanity.com/paper/2103.01075/) (2021)
- [Xpert: Empowering Incident Management with Query Recommendations via Large Language Models](https://mlsanity.com/paper/2312.11988/) (2023)
- [CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting](https://mlsanity.com/paper/1907.12410/) (2019)
- [Exploring Cyberbullying and Other Toxic Behavior in Team Competition Online Games](https://mlsanity.com/paper/1504.02305/) (2015)
- [Using Machine Learning to Predict Game Outcomes Based on Player-Champion Experience in League of Legends](https://mlsanity.com/paper/2108.02799/) (2021)
- [DraftRec: Personalized Draft Recommendation for Winning in Multi-Player Online Battle Arena Games](https://mlsanity.com/paper/2204.12750/) (2022)
- [AllHands: Ask Me Anything on Large-scale Verbatim Feedback via Large Language Models](https://mlsanity.com/paper/2403.15157/) (2024)
- [QuickSkill: Novice Skill Estimation in Online Multiplayer Games](https://mlsanity.com/paper/2208.07704/) (2022)
- [MV-HAN: A Hybrid Attentive Networks based Multi-View Learning Model for Large-scale Contents Recommendation](https://mlsanity.com/paper/2210.07660/) (2022)
- [The Proficiency-Congruency Dilemma: Virtual Team Design and Performance in Multiplayer Online Games](https://mlsanity.com/paper/1512.08321/) (2015)
- [Preference Modeling by Exploiting Latent Components of Ratings](https://mlsanity.com/paper/1710.07072/) (2017)
- [Action2Score: An Embedding Approach To Score Player Action](https://mlsanity.com/paper/2207.10297/) (2022)
- [RoleSeer: Understanding Informal Social Role Changes in MMORPGs via Visual Analytics](https://mlsanity.com/paper/2210.10698/) (2022)
- [ActorLens: Visual Analytics for High-level Actor Identification in MOBA Games](https://mlsanity.com/paper/2307.09699/) (2023)

## Built on by (most cited first, 2 of 2)

- [Identify As A Human Does: A Pathfinder of Next-Generation Anti-Cheat Framework for First-Person Shooter Games](https://mlsanity.com/paper/2409.14830/) (2024)
- [CHAMP: Cross-domain Hybrid Architecture for Matchmaking and Prediction in Online Multi-Player Games](https://mlsanity.com/paper/2609.04870/) (2026)

## Abstract (arXiv)

The multiplayer online battle arena (MOBA) genre has gained significant popularity and economic success, attracting considerable research interest within the Human-Computer Interaction community. Enhancing the gaming experience requires a deep understanding of player behavior, and a crucial aspect of MOBA games is matchmaking, which aims to assemble teams of comparable skill levels. However, existing matchmaking systems often neglect important factors such as players' position preferences and team assignment, resulting in imbalanced matches and reduced player satisfaction. To address these limitations, this paper proposes a novel framework called CUPID, which introduces a novel process called ``re-matchmaking'' to optimize team and position assignments to improve both fairness and player satisfaction. CUPID incorporates a pre-filtering step to ensure a minimum level of matchmaking quality, followed by a pre-match win-rate prediction model that evaluates the fairness of potential assignments. By simultaneously considering players' position satisfaction and game fairness, CUPID aims to provide an enhanced matchmaking experience. Extensive experiments were conducted on two large-scale, real-world MOBA datasets to validate the effectiveness of CUPID. The results surpass all existing state-of-the-art baselines, with an average relative improvement of 7.18% in terms of win prediction accuracy. Furthermore, CUPID has been successfully deployed in a popular online mobile MOBA game. The deployment resulted in significant improvements in match fairness and player satisfaction, as evidenced by critical Human-Computer Interaction (HCI) metrics covering usability, accessibility, and engagement, observed through A/B testing. To the best of our knowledge, CUPID is the first re-matchmaking system designed specifically for large-scale MOBA games.