THE DAILY MLB PICKS SHOWDOWN
As a lifelong baseball fan and stat lover, I came up with the exact prompts to unlock AI's full potential in predicting MLB outcomes. This revolutionary prompt engineering system makes AI consistently profitable at sports betting. These results are exactly accurate for all three AIs. We're running an ongoing handicapping contest through the World Series where I use my proprietary AI prompt model to give each AI an exhaustive dive into MLB stats and trends. Check back daily to see their picks and follow the results.
Each AI must complete an exhaustive 10 prompt analysis process before submitting picks.
AIs can submit multiple bets on the same game with no restrictions. Examples include:
The sprint ran from July 29, 2025 through August 21, 2025. That is twenty four calendar days, a little more than three weeks of MLB action.
Claude dominated with elite ROI and clear bankroll growth, finishing over +46 units. ChatGPT proved solid and profitable with steady grinding, ending over +11 units. Gemini posted a winning record but still lost money, finishing negative on units and ROI.
The AI Handicapping Contest officially ran from July 29, 2025 through August 21, 2025, spanning twenty four days, a little over three weeks of MLB betting action. Each AI was required to make at least five plays per day. Picks included moneylines, run lines, totals, first five innings, team totals, and alternate lines. This contest was tracked transparently from start to finish, without cherry-picking or skipping bad days. Every result was counted.
Claude separated himself early and never looked back. ChatGPT held second throughout, finishing with a positive bankroll. Gemini managed a winning percentage over fifty five percent, but still lost money overall, failing to overcome the vig.
Claude dominated through precision and efficiency. His correlated bets (for example First 5 + Full Game on the same side) paid off consistently. He managed unit size better than the others, rarely overexposing on low-confidence plays. His bankroll curve showed quick recoveries from down days and steady long-term growth. A +15.7% ROI across almost 300 units risked is not luck — it is proof of real predictive edge.
ChatGPT thrived on volume. With 153 decisions graded, he was the busiest of the three AIs. The profit was modest at +11.45 units, but the resilience mattered. Cold streaks came and went, but the bankroll always stabilized. The limitation was lower ROI, the result of spreading bets across too many edges without scaling up the strongest ones. Still, profitability in a public contest is nothing to dismiss.
Gemini looked respectable at first glance, with a 55.9% win rate, but deeper analysis tells the truth. Unit efficiency was poor, line value was weak, and negative ROI confirmed the model could not beat the market. Even with more wins than losses, Gemini’s bettors would have lost money over three weeks. That makes it a failure in practical terms.
The AI Handicapping Contest was designed to test whether artificial intelligence could sustain profit in a betting environment. Over just over three weeks, the answer became clear. Claude is a legitimate betting weapon, producing elite returns and a dominant bankroll curve. ChatGPT proved capable and profitable, showing that disciplined volume and consistency can create steady gains. Gemini, despite a decent record, failed to make money and ultimately proved non-viable as a betting model.
The final verdict: Claude stands as the undisputed champion, ChatGPT earns respect for finishing profitable, and Gemini exits as a warning that a winning percentage alone does not equal betting success. The experiment is over, and the results speak for themselves.