An AI trade analyzer that knows your roster
Drop any trade offer into ChatGPT or Claude and FantasyBot grades it against your actual roster and scoring format, who wins on value, what it does to your starting lineup, and the risk you're taking on. Values come from a model calibrated to the market curve rather than a fixed value chart, which is why the same trade can be fine in a 10-team redraft and bad in your superflex dynasty.
Why static value charts mislead
A value chart assigns each player one number, league-agnostic. That's fast and it's wrong in the two situations where trades actually matter. It doesn't know that you're starting three running backs and one is on bye. It doesn't know that your league starts two quarterbacks, which reprices every passer on the board.
It also ignores roster construction. Trading two good players for one great one is a win on raw value and can still leave you starting a replacement-level flex, the thing that loses you the week.
What you get back
A trade evaluation returns a verdict, the value each side gives up and receives, and the effect on your actual starting lineup, not just a thumbs up.
- Which side wins, and by how much, on values calibrated to your format
- The change to your projected starting lineup, not just to your roster total
- The positional hole the trade opens or closes
- Risk factors: injury status, bye-week collisions, schedule
- A single-player value on a 0–100 scale, if you just want to know what someone is worth
How FantasyBot actually computes an answer
Most AI fantasy tools are a pipe: they hand your league's raw JSON to a general-purpose model and let it reason from scratch. That works for reading a roster back to you and falls apart on anything requiring calibration, because the model has no fantasy-specific model of value, it's pattern-matching on text.
FantasyBot computes first, then explains. A positional grader scores every starting slot against the market curve, so a median starting lineup lands near 80 and an all-#1 roster approaches 100. Trade values come from a model calibrated to that same curve rather than a static value chart, which is why it can tell you a deal is fine in a 10-team redraft and terrible in your superflex dynasty. Weekly projections, matchup outlooks, and league power rankings all run off the same shared scoring, so the numbers agree with each other.
That's the difference you feel in an answer: you get a verdict with the figures behind it, not a paragraph of hedged prose.
Try these
Questions
Is there an AI trade analyzer that uses my real league?
Yes. Connect ESPN, Yahoo, or Sleeper to FantasyBot and evaluate trades in ChatGPT or Claude. It grades the offer against your actual roster, scoring format, and starting lineup rather than a generic value chart.
Does it work for dynasty and superflex?
Yes. It reads your league settings, so superflex repricing and dynasty value curves are applied rather than ignored.
Can it tell me what a single player is worth?
Yes, ask for a player's trade value and you get a 0–100 score with context on what it would take to acquire them.
Related
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