Draft Smarter, Not Harder: Using AI to Optimize Your Fantasy Football Picks
SoFi Stadium, Los Angeles, CA
Drafting a fantasy football team can be a complex process, involving hours of research, analysis, and decision-making. This year, I decided to take a different approach by incorporating AI into my draft strategy. Here’s how I used AI to help me build a competitive fantasy football team, step by step.
The Draft Strategy
Before the draft began, I knew I wanted to leverage AI to help me make informed decisions, particularly in the later rounds when the choices get tougher. My strategy was to use AI to:
Evaluate Players: Get real-time insights into player performance, injuries, and potential.
Compare Options: Compare players at each draft pick to make the best possible decision.
Stay Updated: Ensure I was aware of the latest news and updates, such as team changes or injuries that could impact player value.
The Draft Process
Early Rounds: High-Profile Picks
In the early rounds, I focused on drafting high-profile players who could anchor my team. With AI’s help, I was able to:
Draft Justin Herbert as my QB, knowing he’s a top-tier option with a strong supporting cast.
Select CeeDee Lamb and Cooper Kupp as my primary wide receivers. AI provided insights into their target share and role in their respective offenses, making them solid WR1 options.
Secure Joe Mixon as my RB1, understanding his expected workload in Houston and his consistency in PPR formats.
Mid Rounds: Building Depth
As the draft progressed, AI became even more crucial in identifying value picks and avoiding potential pitfalls:
Drafted Geno Smith as a Flex Option QB. AI highlighted his solid performance last season and the potential boost from the Seahawks' new offensive coordinator.
Picked Rhamondre Stevenson as an RB2. AI pointed out his expected role as the lead back in New England, making him a reliable option.
Added Tyler Lockett for WR depth, despite a minor injury concern. AI’s analysis indicated that Lockett’s role in Seattle’s offense should remain strong, especially in PPR leagues.
Late Rounds: High-Upside and Sleeper Picks
In the late rounds, AI helped identify players with high upside and potential breakout candidates:
Selected Tyler Allgeier as a high-upside handcuff. AI noted that while Bijan Robinson is the lead back in Atlanta, Allgeier could see significant work, especially in a run-heavy scheme.
Drafted Drake Maye as a high-upside rookie QB. AI highlighted his potential to develop into a starting role in New England.
Finished with the Seahawks Defense and Jalen McMillan. AI suggested the Seahawks defense for its solid secondary and pass rush (and new coach Mike MacDonald) and identified McMillan as a sleeper with potential upside in Tampa Bay’s offense.
The Final Team
Here’s the team I ended up with after using AI throughout my draft:
Quarterbacks:
Justin Herbert (Chargers)
Geno Smith (Seahawks)
Drake Maye (Patriots)
Running Backs:
Joe Mixon (Texans)
Rhamondre Stevenson (Patriots)
Tyler Allgeier (Falcons)
Wide Receivers:
CeeDee Lamb (Cowboys)
Cooper Kupp (Rams)
Garrett Wilson (Jets)
Chris Godwin (Buccaneers)
Tyler Lockett (Seahawks)
Jalen McMillan (Buccaneers)
Tight End:
Pat Freiermuth (Steelers)
Defense/Special Teams:
Seahawks Defense
The Draft Experience
Using AI in my draft provided several advantages. It helped me make informed decisions quickly, particularly when it came to comparing players and evaluating risks. However, there were also some challenges, such as outdated information that required me to double-check certain facts. Despite these hiccups, AI proved to be a valuable tool in navigating the complexities of the draft.
In conclusion, integrating AI into my fantasy football draft allowed me to build a well-rounded team with a mix of established stars and high-upside picks. As the season progresses, I’ll continue to monitor the performance of my team and make adjustments as needed, but I feel confident in the foundation I’ve built, thanks in part to the insights provided by AI.
