Top AI Tools for March Madness Brackets 2026
- Greg Kajewski
- Jan 15
- 15 min read
AI is changing how we fill out March Madness brackets. Tools like Rithmm, ESPN AI Bracket Predictor, and KenPom now analyze massive datasets to predict outcomes with precision. In 2025, AI-driven brackets consistently outperformed traditional picks, with some tools correctly predicting up to 87.5% of first-round games and ranking in the top 1.8% of ESPN Tournament Challenge entries.
Here’s a quick rundown of what these tools offer:
Rithmm: Generates up to three custom brackets using over 1 billion data points, real-time updates, and proprietary models.
ESPN AI Bracket Predictor: Offers risk-based strategies (Conservative, Balanced, Boom-or-Bust) with real-time updates.
KenPom Metrics: Focuses on team efficiency stats like adjusted offensive/defensive performance.
FiveThirtyEight-Style Simulations: Runs thousands of simulations using advanced stats and betting data.
Custom AI Models (e.g., ChatGPT): Allows for tailored predictions by training AI with specific datasets.
BettorEdge: Combines AI insights with a social betting marketplace bracket experience.
Key Takeaway: Whether you’re aiming for accuracy or a social experience, these tools give you data-driven insights to improve your bracket strategy.
Quick Comparison
Tool | Key Feature | Accuracy Highlight | Cost |
Rithmm | AI-powered custom brackets | 34% winning bracket rate in 2024 | $29.99/month |
ESPN AI Predictor | Risk-based strategies | Correctly predicted UConn in 2024 | Free with ESPN app |
KenPom Metrics | Advanced team efficiency stats | Used to train top-performing AI models | Subscription-based |
FiveThirtyEight Sim | Monte Carlo tournament simulations | Ranked top 1.2% in ESPN Tournament | Free |
Custom AI Models | Tailored predictions via prompting | 87.5% first-round accuracy in 2025 | Variable (depends on tool) |
BettorEdge | Community-driven bracket challenges | Real-time leaderboards and social tools | Free and paid tiers |
AI tools are reshaping March Madness predictions - whether you’re in it for fun or serious competition, there’s a tool for you.
I Let AI Fill Out My March Madness Bracket: Will it Beat the Experts?
What to Look for in an AI March Madness Bracket Tool
AI bracket tools can differ a lot in how they work and what they offer. The key differences between a basic chatbot and a specialized tournament predictor often boil down to the depth of their data, the level of customization they allow, and how well they adapt to real-time changes.
Start by checking the data sources the tool uses. For example, tools that incorporate metrics like KenPom's efficiency ratings are a solid choice. These tools often also track critical updates like injury reports, roster changes, and shifts in betting markets - details that can make or break predictions. In fact, advanced models in 2024 accurately identified upsets by analyzing massive amounts of team data. A strong data foundation is essential for any tool aiming to give you a competitive edge.
Next, look for customization options tailored to your specific pool. A strategy for a small 10-person office pool will differ significantly from one designed for a massive 300-person national contest. Pool-specific customization allows you to adjust strategies based on unique pool rules, helping you maximize your chances of success.
Another important feature is the ability to analyze public sentiment. Some tools track public pick trends from major hosting platforms, helping you spot teams that are being overhyped. This insight creates opportunities to make contrarian picks that can set your bracket apart. For instance, in 2025, ChatGPT's "Deep Research" feature combined with KenPom data to correctly predict 28 out of 32 first-round games, ultimately achieving a top 1.8% ranking in the ESPN Tournament Challenge by the Elite Eight.
Lastly, convenience matters. Choose tools that can generate brackets instantly, work seamlessly on mobile devices, and even provide printable PDFs for those physical pool submissions. Platforms powered by advanced AI, like GPT-4o, highlight the importance of using up-to-date data, often relying on live-search capabilities to ensure accuracy in real-time bracket generation.
1. Rithmm
Rithmm is a cutting-edge tool designed for creating AI-powered March Madness brackets. With its AI March Madness Bracket Generator, you can instantly generate complete tournament brackets and even diversify your entries by requesting up to three unique bracket predictions.
Data Sources and Modeling Approach
Rithmm taps into over 1 billion data points to craft its predictions. It evaluates team performance trends, matchup-specific strengths and weaknesses, and betting market shifts to simulate the outcome of every game. The platform also features a Custom Model Builder, a no-code tool that allows users to create predictive models by tweaking specific data inputs. Meyers Ames, a user of the platform, shared their experience:
"I found this app after trying to build my own betting models. The time I would spend, the spreadsheets I had, the money I would spend on data...this is so much easier."
Rithmm's brackets have a proven track record, with 34% of its entries resulting in wins, compared to ESPN's 24.7%. Impressively, 93% of Rithmm's NCAA brackets still had their predicted national champion intact after the first two rounds.
Real-Time Updates and Adjustments
One standout feature of Rithmm is its ability to incorporate real-time updates. From injury reports and roster changes to shifts in betting markets, the platform continuously refines its predictions throughout the tournament. Its Smart Signals, marked with a lightning bolt icon, highlight high-confidence picks by analyzing historical patterns and market conditions. These signals are updated around the clock to ensure accuracy. Premium users also gain access to advanced tools that show how specific roster changes could affect game outcomes.
March Madness-Specific Features
Rithmm takes the excitement of March Madness to the next level by teaming up with NBA star Kyle Kuzma for a special bracket challenge. Participants can win prizes like courtside NBA tickets, signed jerseys, and free subscriptions. The platform offers a 7-day free trial, with the Core tier priced at $29.99 per month or $19.99 per month when billed annually. This tier includes AI game predictions, "Bolt" picks, and access to the custom model builder.
For those entering multiple pools, requesting the maximum three brackets and focusing on "Bolt" picks for critical decisions can greatly improve your chances of success.
The ESPN AI Bracket Predictor is seamlessly integrated into the ESPN Tournament Challenge, offering a quick and efficient way to create tournament brackets. With the Instant Bracket feature, you can skip the manual work and let AI generate an optimized bracket for you. This tool provides a streamlined approach to crafting smart bracket strategies.
Bracket Generation and Customization
The predictor offers three distinct risk profiles to match your strategy: Conservative, Balanced, and Boom-or-Bust.
Conservative: Prioritizes safe picks by focusing on teams with the highest probability of winning.
Balanced: Combines a mix of likely winners with a few calculated upsets for a more versatile approach.
Boom-or-Bust: A high-risk, high-reward strategy aimed at maximizing potential gains in competitive pools.
If your pool allows multiple entries, consider creating one bracket for each risk profile to cover all your bases.
Data Sources and Modeling Approach
ESPN's AI leverages a combination of historical and current data to make well-informed picks. It evaluates key metrics such as offensive and defensive efficiency, as well as a team's momentum late in the season. For example, in March 2024, ESPN's AI brackets correctly predicted the national champion, UConn, 24.7% of the time within the ESPN Tournament Challenge.
Real-Time Updates and Adjustments
One of the standout features of this tool is its ability to adapt in real time. The models update after each round, factoring in game results, injury reports, and emerging trends. This makes it especially useful for mid-tournament adjustments or even live betting decisions.
For improved accuracy, compare ESPN's AI picks with other advanced analytics platforms like KenPom or FiveThirtyEight to identify consensus selections for high-stakes pools. Keep an eye out for AI-flagged "Cinderella teams" - those with strong three-point shooting and low turnover rates - as these traits often signal upset potential.
3. KenPom Advanced Metrics
KenPom provides possession-based metrics that focus on team efficiency rather than relying solely on win-loss records. These metrics are especially useful for AI tools designed to predict NCAA tournament outcomes. At the heart of KenPom's analysis is the Adjusted Efficiency Margin (AdjEM) - the difference between points scored and allowed per 100 possessions, adjusted for the quality of opponents. By stripping away the influence of pace and schedule strength, this system offers a clearer view of team quality, helping identify top contenders.
Data Sources and Modeling Approach
KenPom's advanced analytics revolve around four main metrics:
Adjusted Offensive Efficiency: Points scored per 100 possessions.
Adjusted Defensive Efficiency: Points allowed per 100 possessions.
Adjusted Efficiency Margin: The difference between offensive and defensive efficiency.
Tempo: The number of possessions per 40 minutes.
These metrics are adjusted for the strength of opponents, making direct team comparisons more meaningful. For example, in 2025, Texas Tech ranked 7th overall with the 6th-best offensive efficiency, while Houston boasted the 2nd-ranked defense nationally. These rankings often highlight teams whose tournament seeds don't align with their true strength, offering valuable insights for predicting under-the-radar contenders.
March Madness-Specific Features
KenPom's data plays a pivotal role in training AI models for bracket predictions. In April 2025, C Jackson Cowart and the Sportsbook Review team used KenPom metrics to train ChatGPT-4o. By importing a spreadsheet of data that included adjusted offensive and defensive efficiency, tempo, and efficiency margins, they created an AI-driven bracket that achieved impressive results. This bracket ranked in the top 12% of the ESPN Tournament Challenge heading into the Final Four, correctly predicting 28 out of 32 first-round winners (87.5% accuracy) and all eight Elite Eight teams.
"We imported a spreadsheet of KenPom data for every team in the NCAA Tournament field, including how each team ranks in tempo, adjusted offensive and defensive efficiency, and adjusted efficiency margin." - C Jackson Cowart, Senior Publishing Editor, Sportsbook Review
KenPom's Tempo metric can also be a game-changer when evaluating matchups. For instance, if a fast-paced team faces a slower, defensive-minded opponent, the advantage often shifts to the team that thrives in a grind-it-out, low-scoring game. Additionally, teams that rank highly in both offensive and defensive efficiency tend to have better chances of making deep tournament runs, as one-dimensional squads rarely succeed. Before betting on a double-digit seed upset, check their adjusted efficiency margin to ensure their regular-season success wasn't inflated by weaker competition.
This data-driven methodology, combined with AI tools, offers a powerful way to refine bracket predictions for March Madness 2026.
4. FiveThirtyEight-Style Tournament Simulations
FiveThirtyEight-style simulations use Monte Carlo methods to simulate tournaments thousands of times. These simulations rely on statistical data to calculate probabilities for each team's progression through the rounds, creating detailed probability distributions. Let’s explore the data and techniques that drive these simulations.
Data Sources and Modeling Approach
These simulations draw from a mix of data sources to make their predictions. At the core are KenPom efficiency metrics, which assess team quality through adjusted offensive and defensive efficiency, tempo, and efficiency margin. These metrics ensure that predictions account for team performance without bias from pace or schedule difficulty.
Betting market data - including point spreads, over/under totals, and odds for making the Final Four - provides insights from professional oddsmakers, who factor in both statistics and public sentiment. To capture the unpredictable nature of March Madness, historical tournament trends are also integrated into the models. These trends include patterns like the frequent success of 12-seeds over 5-seeds. Additionally, modern simulations use "Deep Research" to adjust probabilities in real time, incorporating last-minute data like injuries or lineup changes.
Data Category | Specific Metrics Used in Simulations |
Advanced Metrics | Adjusted Offensive/Defensive Efficiency, Tempo, Efficiency Margin |
Team Performance | Win-Loss Records, Points Per Game (PPG), Opponent PPG, Recent Momentum (Last 10 Games) |
Market Data | Betting Spreads, Over/Under Totals, Final Four Odds |
Personnel Data | Key Player Stats (Scoring/Rebounding), Injury Reports, Coach Experience |
Historical Data | Past Tournament Performance, Common Upset Trends, Seed-Based Probability |
Bracket Generation and Customization
One of the standout features of these simulations is their ability to tailor predictions based on user preferences. Users can set their risk tolerance - low, medium, or high upset - allowing them to align predictions with their strategy. For example, in a recent test, a medium-risk simulation nailed nearly all first-round predictions and went 8-for-8 in the Sweet Sixteen, ultimately securing second place in a personal pool.
Similarly, Sportsbook Review utilized ChatGPT alongside KenPom data, using "Deep Research" to refine predictions. This model accurately selected all eight Elite Eight teams and ranked in the top 1.2% of the ESPN Tournament Challenge heading into the Final Four.
These tools provide a way to adapt predictions to the unique chaos of March Madness, giving users a competitive edge.
March Madness-Specific Features
What makes these simulations especially effective is their ability to spot potential upsets. They analyze factors often linked to "Cinderella" teams, such as high three-point shooting efficiency, low turnover rates, strong late-season momentum, and experienced rosters with upperclassmen. For instance, in 2024, Rithmm's AI-generated brackets correctly predicted UConn as the national champion in 1 out of every 3 brackets and produced 39% more winning brackets than the average ESPN pool (34% vs. 24.7%).
Another advantage is the ability to update predictions round by round. By inputting actual results from completed rounds, users can generate fresh probabilities for the remaining teams. When customizing a model, including a team's "last 10 games" record can help capture late-season momentum that broader season-long stats might miss.
"ChatGPT can excel at spotting trends or other data points that humans might overlook, so use these AI picks at your own discretion!" - C Jackson Cowart, Senior Publishing Editor, Sportsbook Review
These simulation-driven methods highlight the growing role of AI in refining March Madness predictions, making them more precise and adaptable than ever before.
5. Custom AI Models and Chatbot-Assisted Brackets
Custom AI models and chatbot tools like ChatGPT, Perplexity, and Microsoft Copilot can help you create bracket predictions tailored to your strategy. Unlike pre-built simulators, these tools allow you to "train" the AI with specific datasets, enabling it to generate brackets that align closely with your approach.
Data Sources and Modeling Approach
To build a strong model, incorporate metrics from KenPom, betting spreads, and key player stats. KenPom metrics - such as adjusted efficiencies, tempo, and efficiency margins - provide a solid foundation for evaluating team quality. Betting market data, like point spreads and totals, can establish baseline expectations for matchups. Include additional factors like tournament coaching records, key player statistics (points, rebounds, assists per game), and real-time injury updates to refine the model further.
In March 2025, the Action Network staff trained ChatGPT using nine specific data categories, including coaching experience and recent momentum (performance over the last 10 games). This process produced an 85-page document with 18,000 words of detailed matchup analysis, ultimately predicting Duke as the national champion. Similarly, C. Jackson Cowart from Sportsbook Review trained a GPT-4o model with KenPom data and betting spreads. His AI-driven bracket correctly predicted 28 of 32 first-round games and all eight Elite Eight teams, landing in the top 1.8% of the ESPN Tournament Challenge.
Once the data foundation is set, you can fine-tune the bracket by establishing clear rules for evaluating matchups.
Bracket Generation and Customization
By leveraging the data, you can customize your AI’s parameters to identify potential upsets. Custom models remove human bias by focusing solely on matchup-specific metrics. For example, you can program the AI to pinpoint "Cinderella" teams by analyzing traits like high three-point shooting accuracy, low turnover rates, and strong late-season momentum. Tools like Rithmm allow users to input their preferred data points and generate up to three unique AI-driven brackets.
These custom models excel at spotting potential upsets by zeroing in on critical factors like shooting efficiency, ball security, and end-of-season performance.
Real-Time Updates and Adjustments
Advanced models, such as GPT-4o, can perform real-time searches for injury updates and roster changes, ensuring your bracket stays current. Chatbots can also provide round-by-round analysis, offering fresh predictions for stages like the Sweet 16 or Final Four after earlier rounds conclude. However, it’s important to verify AI-generated player health updates, as some bots provided conflicting information during the 2025 tournament.
March Madness-Specific Features
Custom AI models excel at identifying upset opportunities when trained with tournament-specific instructions. For example, you can direct the AI to focus on double-digit seeds with traits often linked to success, such as high turnover-forcing defenses or experienced, upperclassmen-heavy rosters. In 2024, Rithmm’s AI-generated brackets correctly predicted the national champion (UConn) in 33.3% of cases and produced 39% more winning brackets compared to the average ESPN user (34% vs. 24.7%). Impressively, 93% of Rithmm’s AI brackets still had their national champion pick intact after the first two rounds.
6. BettorEdge
BettorEdge takes March Madness to a new level by combining AI-powered tools with a strong sense of community. Through its Bracket Battle competitions, this platform offers a fresh, social spin on the tournament experience. Whether you're squaring off against friends, coworkers, or the entire BettorEdge community, the mix of social betting features and bracket challenges makes it a standout choice.
Bracket Creation and Personalization
BettorEdge makes bracket-building interactive and insightful by tapping into real-time community input. With the platform’s Groups feature, you can easily organize custom office pools or private challenges. Tailor them with personalized scoring systems and flexible entry options - whether you want to keep it free or add a paid element.
Features Tailored for March Madness
Stay updated with live leaderboards that track every bracket’s progress in real time. Engage in head-to-head matchups or try your hand at parlay and pick'em contests. The platform also includes a social feed where users can share bold upset predictions, Cinderella team picks, and championship forecasts.
For those who like to dig deeper, advanced analytics provide insights into past performances, helping to fine-tune strategies. Premium users can access even more detailed charts and data, giving them an edge in their predictions.
Comparison Table
Here’s a breakdown of what each tool brings to the table when it comes to building winning brackets:
Tool | Bracket Generation | Data Richness | Real-Time Updates | Upset Identification | Community Features |
Rithmm | Instant via app (up to 3 custom brackets) | High (thousands of data points, proprietary models) | Yes (accounts for injuries, roster changes, and betting markets) | High (34% winning bracket rate in 2024, 39% higher than ESPN) | High (Kyle Kuzma Challenge and social sharing) |
ESPN AI Bracket Predictor | Automated using historical trends | Medium (tournament history and current stats) | Yes | Medium (provides strategic upset suggestions) | Medium |
KenPom Advanced Metrics | Manual – user interprets efficiency data | Very High (adjusted offensive/defensive efficiency, tempo) | Yes | High (spots under-seeded teams) | Low (data-focused with limited social features) |
FiveThirtyEight-Style Simulations | Monte Carlo simulations (thousands of runs) | High (probability-based modeling) | Yes | Medium to High (emphasizes low-probability upsets) | Low (analysis-focused) |
Custom AI Models (ChatGPT, Perplexity) | Manual via prompting | Variable (depends on input like KenPom stats and betting odds) | Yes with GPT-4o Deep Research; variable with others | Moderate (ChatGPT correctly predicted 28 of 32 first-round games in 2025) | Low (lacks built-in social features) |
BettorEdge | Interactive via community input | Medium to High (real-time community insights and analytics) | Yes (live leaderboards and social feed updates) | Medium (community-driven predictions) | Very High (custom groups, head-to-head challenges, social feed, competitions) |
Each tool has its strengths and trade-offs, depending on what you're looking for.
If you're after data-driven accuracy, Rithmm and KenPom are top picks. Rithmm’s proprietary sports betting models and its impressive track record - like achieving a 34% winning bracket rate in 2024 - make it a standout option. KenPom, on the other hand, is ideal for those who prefer digging into advanced stats like offensive and defensive efficiency.
For a community-focused experience, BettorEdge shines. It allows users to create custom groups, engage in head-to-head challenges, and stay connected with live leaderboards and social feeds throughout the tournament.
Meanwhile, tools like ChatGPT have also proven their worth, with its 2025 prediction accuracy standing out as a highlight. If you’re looking for flexibility and creativity in your bracket strategy, it’s a solid choice for manual, prompt-based approaches.
Ultimately, the right tool depends on whether you value precision, community engagement, or a mix of both.
Conclusion
Bracket building has shifted from guesswork to data-driven precision, thanks to AI tools like Rithmm and ChatGPT. These tools have raised the bar, with AI-generated brackets consistently outperforming traditional picks by tapping into extensive data insights. This leap in predictive accuracy highlights the importance of selecting a tool that aligns with your approach to bracket strategy.
Whether you're drawn to pure data analysis or prefer community-driven insights, the right tool can make all the difference. Options like Rithmm and KenPom focus on proprietary models and advanced efficiency metrics, catering to those who prioritize analytics. For a more social experience, BettorEdge offers features like custom groups, head-to-head challenges, and live leaderboards. Meanwhile, tools like ChatGPT and Perplexity provide flexibility, allowing users to experiment with custom prompts and access real-time data feeds.
"In 2025, we're making a million-dollar bet with a professional sports bettor, and the reason we feel confident to do that is because data, we feel, will beat humans." – Alan Levy, CEO, 4C Predictions
Ultimately, your choice should reflect your pool size and risk tolerance. Whether you lean on advanced analytics or thrive on social competition, AI tools are ready to deliver insights that can elevate your March Madness 2026 bracket strategy.
FAQs
How do AI tools like Rithmm and ESPN's AI Bracket Predictor help create more accurate March Madness brackets?
AI tools are transforming how brackets are built, offering sharper predictions by processing vast amounts of data. Take Rithmm, for instance - it uses advanced AI models to analyze over a billion data points. These include team performance, matchup dynamics, injury reports, roster updates, and even betting trends, all to deliver accurate picks in just seconds.
Though exact details about ESPN's AI Bracket Predictor remain under wraps, AI-powered tools have a clear edge over traditional methods. By eliminating bias and leveraging real-time insights, they significantly improve your chances of putting together a winning bracket.
What should I look for in an AI tool to build my March Madness bracket?
When picking an AI tool to help with your March Madness bracket, it's all about the quality of the data it uses. The best tools dig deep into stats like win-loss records, team efficiency, seedings, and even past tournament results. The more detailed the data, the better the AI can spot trends and predict those thrilling upsets.
You’ll also want to look at the tool’s analytical capabilities and adaptability. Tools that run simulations or account for real-time updates - like injuries or roster changes - can offer predictions tailored to specific matchups. And don’t overlook usability and community features. For example, platforms like BettorEdge pair AI-driven insights with social features like group challenges and leaderboards, making it fun to compete with friends and track your progress. A tool that combines rich data, smart analysis, and an easy-to-use interface can give you a real shot at creating a winning bracket.
How can I use KenPom stats to predict potential upsets in March Madness?
KenPom’s advanced stats - like Adjusted Efficiency Margin, tempo, and strength of schedule - offer a powerful way to pinpoint underdogs that might outperform their tournament seed. These stats dig deeper than simple win-loss records, providing a clearer picture of how teams actually stack up.
To identify potential upsets, start by examining the Adjusted Efficiency Margin (calculated as offensive efficiency minus defensive efficiency). If a lower-seeded team’s margin is close to or even better than its opponent’s, it could signal a higher likelihood of an upset. Next, consider tempo: slower-paced teams can often throw faster opponents off their rhythm. Finally, check the strength of schedule to ensure the underdog’s numbers weren’t padded by facing weaker competition.
For an even sharper edge, combine these metrics with updates on injuries and recent performance trends. This data-driven approach can help you make smarter picks when filling out your bracket.
