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Sports Analysis with AI

Sports Analysis with AI

Welcome back to this weekly series on AI. As we advance further in our exploration, we shift our gaze this week to the exhilarating field of sports analysis. In this edition, we will delve into how AI, specifically LLMs, can be employed for insightful basketball analysis and generating hypothetical game predictions. Although LLMs are trained on data up until a certain time (for example, GPT 3.5 is trained up till September 2021 as of now), it can still offer us a treasure trove of insights and predictions based on past data, enabling us to theorize and speculate about a multitude of intriguing scenarios.

This week, our journey with AI takes us courtside as we investigate three key areas—individual player performance analysis, team performance analysis, and hypothetical game predictions. Each area promises to unlock new ways of appreciating the complexity and strategic depth of basketball, harnessing the potential of AI to enhance our understanding of the sport.

To illustrate these concepts, we will use specific prompts that you, as a sports analyst, spectator, or enthusiast, can deploy to engage with AI for comprehensive basketball analysis. You will be guided step by step, just like in previous articles, and will be shown how to interpret chatbot responses, with examples peppered throughout the article.

Decoding AI and Hypothetical Predictions in Basketball

Understanding the interface between AI and basketball involves delving into the intricacies of predictive analysis. How do AI models like ChatGPT make these predictions, you may wonder? Unlike real-time prediction systems that utilize live data, ChatGPT relies on historical data up to 2021 to create hypothetical scenarios. It's like a seasoned basketball pundit, with years of experience and knowledge, who uses this extensive background to speculate on various situations. However, unlike human pundits, ChatGPT's predictions are devoid of personal biases, making them purely data-driven. While it can't predict real-world future outcomes, it can give us a theoretical play-by-play based on historical information.

Deploying AI for Player Performance Analysis

One of the most exciting applications of ChatGPT in basketball is analyzing player performance. By feeding the AI model information about a player's historical performance, we can probe deeper into their capabilities and how they might perform under various hypothetical scenarios.

This tool allows you to input a player’s name and a team they are playing against and quickly retrieve their statistics.

For instance, if we want to know how LeBron James would perform against the Warriors:

Remember, the output will always be a data-informed speculation, not a surefire prediction. It's akin to an educated guess, informed by a wealth of past data, but a guess nonetheless. A key point to remember is that due to this data-based prediction, AI will never make exceptional predictions - it will only help in leveraging data to compare with current stats to analyze performance.

Leveraging AI for Team Performance Analysis

It's not just individual players that AI can analyze; entire teams can be placed under its discerning digital gaze. By understanding a team's past performance, AI can help us imagine how a team might fare under various circumstances. For example, if we're curious to know how the 2016 Golden State Warriors would perform if they maintained a three-point shooting accuracy of 40% throughout an entire season, we might ask:

"Based on the Golden State Warriors' stats up until 2021, predict their performance in a season where they maintain a three-point shooting accuracy of 40%, stating any assumptions made"

The response:

Using AI to Predict Cross-Era NBA Scenarios

In addition to analyzing individual players and entire teams, AI can be utilized to predict the outcome of hypothetical basketball games based on historical performance data. Say we're curious about how a match between the 1996 Chicago Bulls and the 2016 Golden State Warriors might pan out, we can use this tool to input both these teams and receive a hypothetical game scenario.

Here are the results:

The Future of AI in Sports Analysis and Predictions

Looking to the future, it's fascinating to ponder the possible advancements in AI that could enhance models like ChatGPT. For instance, future models may be able to handle real-time data, further improving their predictive abilities. This opens up a world of potential applications in sports journalism, coaching, and management, among others.


Our exploration of using AI for basketball analysis has taken us from player to team to hypothetical match predictions. While these AI-driven analyses are purely speculative, they offer a unique way to engage with the sport of basketball, allowing us to explore a multitude of intriguing "what if" scenarios. As we continue our series on AI and fitness, we look forward to introducing you to more fascinating applications of AI. Until then, enjoy brainstorming hypothetical basketball scenarios with AI!

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