Patches vs Data – esports betting
Patching in esports goes beyond simple software updates; it revolutionizes gameplay and betting dynamics.
Written by Dr. Darina Goldin
Patches serve a crucial role in esports, acting as catalysts for change that can transform the gaming landscape. Whether it’s removing a building type, introducing new heroes, or making significant alterations to existing ones, a single patch has the power to reshape entire strategies. Moreover, minute adjustments—like a 5% reduction in ability cooldowns or slight shifts in item pricing—can have profound implications.
Impact of Patches on Gameplay
The immediate effects of these patches on gameplay are often unclear. Companies like Bayes Esports meticulously monitor how professional teams adapt to shifting game rules, ultimately establishing a new “meta” until the next patch arrives. This continual evolution keeps the game enticing for players and spectators alike but poses a notable challenge for those involved in setting betting odds.
The Challenge of Betting Odds in a Dynamic Environment
In multiplayer online battle arenas (MOBAs), side markets frequently focus on objectives such as defeating specific monsters, whose attributes and importance can change dramatically following patches. If you maintain outdated models, you risk falling behind savvy bettors who might exploit these discrepancies.
Time Hurdles in Model Adjustments
Adjusting betting models in response to patches requires time to gather and analyze fresh data. Understanding the full impact of a patch on the meta is challenging. Although expert analysts offer insights and predictions, human error is inevitable. Consequently, it can take several weeks to accumulate sufficient data to ensure model accuracy for side markets. This period of uncertainty can result in temporarily higher risks or the inability to provide odds at all.
Envisioning an AI-Driven Solution
Imagine a revolutionary software that could rapidly analyze patch notes and predict subsequent meta shifts. Self-play simulations could be invaluable here: envision a computer-controlled matchup of two League of Legends or Dota 2 teams, iterating strategies until a new meta emerges. By capturing and analyzing these simulated games, we could generate relevant statistics and refine our predictive models in a fraction of the time it currently takes—potentially just hours instead of weeks.
Current Advancements in AI
This concept isn’t as far-fetched as it appears. OpenAI has already demonstrated the capability of training machines to play Dota 2 at a professional level. Today’s advanced AI systems can learn strategies, coordinate teams, and optimize for long-term objectives. While translating this to patch prediction remains a significant challenge, it’s a hurdle worth pursuing. With access to high-quality data, such as that provided by Bayes Esports, a dedicated team could effectively bridge this gap. Who knows? Within a year, we may rely on AI assessments of patch notes rather than traditional expert opinions.
As a data scientist passionate about sports and research, Dr. Darina Goldin leads the research team at Bayes Esports, where a data-driven approach informs the future of esports. In her upcoming columns, she will explore innovative ideas she envisions for the esports ecosystem. Though none are easy—some could fill entire dissertations—each concept presents significant potential benefits for the community and serves as an engaging thought exercise for the present.
