Sixty hours of expert DFS commentary drops every NFL week across the top 20 shows. The analysts covering this sport are good. Knowing the full spectrum of what they think, across every show, is what separates a confident lineup decision from a guess.
RotoRecon synthesizes every take and puts that knowledge in reach. Cited, timestamped, and ready to query whenever you have ten minutes, whether that's the night before lock, between meetings, or on the way to the stadium.
Not a firehose. A curated list evaluated for DFS signal density, activity, and analytical depth. Within minutes of publish, each episode is transcribed, diarized, and timestamped. Every host, every segment, every take.
Phonetic entity resolution. Temporal context. Coreference. Sentiment-on-entity. A fine-tuned DeBERTa-DFS model turns audio into structured opinion across 6 dimensions. 97.2% structural precision.
Ask anything. Get an answer cited by source, timestamped to the minute, with live stats and weather context baked in. No hallucinations. Every claim traces back to a specific take in a specific episode.
Generic AI blends every expert opinion into a single score. We preserve every voice. See exactly where analysts agree, where they diverge, and what the outliers are saying. The contrarian take you almost missed might be the one that wins your tournament.
Purpose-built for DFS audio, not a general-purpose model applied to a new domain. Here's what does the work.
Fine-tuned, not prompted.
A DeBERTa-v3-base backbone fine-tuned on 10,502 expert-annotated DFS records across 6 sentiment dimensions: talent, matchup, opportunity, health, value, and ownership. It understands "smash play," "I'm off," and "leverage spot", not just generic positive/negative polarity.
Read on /technologyEvery take, resolved to a player.
Phonetic entity resolution handles "J-Chase" vs "Chase" vs "Jamar." Coreference binds "he" to the right antecedent. Temporal binding anchors every take to the correct slate. No take gets lost.
Read on /technologyA credit score for every player.
Borrowed from FICO-model scoring: Phase 1 ranks weekly metrics within position group; Phase 2 blends with historical baselines. Every player gets a 0–100 score updated hourly, directly comparable across positions and slates.
Read on /technologyWe don't republish transcripts. We extract structured takes and cite the original episode, host, and timestamp, a direct click-through to the source podcast. The creators we synthesize get credit, not competition.
Weekly billing aligned to the NFL schedule. Monthly for the regulars. Season-long for grinders who already know.
For casuals entering a few contests a week.
For serious players with a DFS process.
For high-volume players who build their own models.
Still stuck? Email the founders We read every message and ship fixes by Friday.