Today's Slate
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📐 Model Methodology — Why the numbers say what they say
The model is an ensemble of eight inputs that each independently move a game's run, strikeout, and win-probability projections, then get blended with empirically-derived weights. Nothing here is guessed — every component is either a MLB Stats API pull, an Open-Meteo weather pull, or a hand-tuned coefficient derived from multi-year league baselines.
- 25%Starting pitcher quality — season ERA, WHIP, K/9, and BB/9. Each point of ERA above 4.00 adds ~0.25 runs to the team total; WHIP above 1.30 inflates opposing OBP expectation.
- 20%Handedness splits — the team's actual OPS/OBP/AVG/K% against the exact hand of pitcher they're facing. A lineup that OPSes .810 vs LHP but .680 vs RHP is a completely different offense depending on who starts.
- 15%Park factors — 30-park table (runs, HR-L, HR-R, doubles, walks). Coors (1.35) and Great American (1.10) amplify; Oracle (0.91) and loanDepot (0.94) suppress. Home-run factors split by batter handedness because Yankee Stadium boosts LHB HRs 24%.
- 15%Wind vector projection — meteorological wind direction is projected onto each park's home-to-CF bearing so "8 mph NNE" becomes actionable "OUT to LCF." Wind OUT adds up to ~1.2 runs; wind IN subtracts ~0.9. Domes ignore wind.
- 10%Opponent K% and contact profile — high-K lineups inflate pitcher K prop overs and team-K-thrown totals. Low-K lineups suppress them even against ace pitchers.
- 8%Bullpen load — proxied by recent IP; fatigued pens lift late-game totals and hurt the F5 under.
- 5%Temperature and humidity — warm air is less dense (ball travels ~0.4 ft per 10°F) and adds carry, nudging HR projections.
- 2%Home-field baseline — +0.20 runs of model edge for the home team, applied after all other inputs.
What the model believes: most public totals over-react to the last 3 games of either team and under-weight park/wind, which is why it looks for ≥0.8 runs of disagreement before flagging an OVER/UNDER. On strikeout props it trusts K/9 over reputation — a 30% K% SP facing a 26% K% opponent at Tropicana will project higher total Ks than a household-name ace facing Cleveland. On moneylines the model intentionally stays small because public books are sharpest there; it only flags >0.3 ERA-equivalent gaps. Human-element layer (news/injury) is currently a qualitative overlay you should apply after reading the narrative, not auto-fed.
Projected totals (by game)
Projected team Ks thrown
📝 Game-by-Game Analysis
Full writeup of every matchup — projected winner, projected score, pitcher read, offense read, park and weather effects, bullpen status, and the bet plays that follow. Re-runs on every refresh.
🧙 AI Wizard — Deep Per-Game Brief
Expert-level writeup for every game on the slate. Blends the 11-factor Moneyline model, individual lineup splits vs the starter, BvP career history, bullpen leverage status, park + weather context, and Statcast xERA / xwOBA when the overlay is available. Every card ends with a clear verdict and a ranked bet list.
💎 Value Bets — Model vs Market
This is where picking winners becomes picking bets that actually make money. Each row compares our 11 factor model's implied win probability against the vig free market probability. Only plays where we beat the market by 3 points or more are called value. Quarter Kelly sizing tells you how much of your bankroll to wager; it scales with the edge and is capped at 5% per bet.
📈 PNL and Results
Every pick the model locks in gets snapshotted at game time along with the market price. After the game finishes we grade it, measure closing line value, and fold the result into bankroll, ROI by bet type, and the heat map below.
Top Bets (Model-Ranked)
Edge derived from park + weather + pitcher + team K model. Human element layer applied.
Moneyline Picks
Multi-factor model: team offense (OPS vs hand), pitcher quality (ERA/WHIP/K9), recent team form (7d record + run diff), bullpen availability, and park factors. Confidence tiers: 🔒 LOCK · 💪 STRONG · 👍 LEAN · ⏸️ PASS
Run Line (-1.5 / +1.5)
Game script leaning
Totals (Over / Under)
Wind + park + pitcher projection
First 5 Innings — Overs
First 5 Innings — Unders
Pitcher Strikeout Props
K/9, opp K%, handedness splits
Team Strikeout Props — Total Ks Thrown
Projected total Ks by a team's pitching staff (SP + pen) against opponent K rate. Lineup-aware: when lineups are confirmed, uses each batter's individual K rate vs the SP's hand instead of team averages.
Hit Props (Batter Hits O/U)
Now uses hitter 7-day hot/cold form + opposing pitcher WHIP. Hot hitters get boosted, cold hitters get suppressed.
SP Earned Runs Props (O/U)
Projected earned runs for each starter based on their ERA, recent form, opponent OPS, and park factor. Lower ER projection = take the under.
SP Walk Props (O/U)
Projected walks issued by each starter based on BB/9 rate, opponent walk rate, and recent control trends.
Pitcher Analysis
Live season stats & handedness splits
Batter vs Pitcher History
Career BvP for today's starting batters (loads in background, 5+ AB)
⭐ Yankees Focus — Tonight's Game
Deep dive on the Bronx Bombers' game: opponent, starting pitchers, projections, bets to target, and a narrative on why.
Matchups — Team Offense vs Opposing SP
For each side of every game: team's batting splits vs the opposing pitcher's handedness, the opposing SP's own splits allowed, and a weighted Matchup Edge. Click any column to sort.
Matchup Edge (higher = hitters favored)
Full matchup table i
- Game
- Away @ Home matchup abbreviation
- Team
- The batting team in this row
- vs SP
- Opposing starting pitcher and their throwing hand (RHP/LHP)
- T AVG
- Team batting average vs the SP's hand (season splits)
- T OBP
- Team on-base percentage vs SP hand
- T OPS
- Team OPS (on-base + slugging) vs SP hand — key offensive power metric
- T K%
- Team strikeout rate vs SP hand — lower is better for hitters
- SP ERA
- Opposing pitcher's season earned run average — lower = tougher matchup
- SP WHIP
- Pitcher walks+hits per inning — lower = fewer baserunners allowed
- SP K/9
- Pitcher strikeouts per 9 innings — higher = more dominant
- SP OPS Allowed
- What OPS the pitcher allows to hitters of this team's hand
- LU OPS vs Hand
- Average OPS of the actual confirmed lineup batters specifically against this pitcher's hand (L or R) — uses individual batter season splits, not team averages
- Platoon%
- What percentage of the lineup has the platoon advantage (LHB vs RHP, RHB vs LHP, or switch hitters). Higher = more favorable matchup.
- Edge
- Composite matchup edge: positive = hitters favored, negative = pitcher favored. Now factors in individual lineup batter splits vs the SP's hand and platoon advantage.
Team Batting Splits vs LHP / RHP
Strikeouts, OPS, OBP, AVG — toggle the metric and the handedness to see who feasts on (or struggles against) lefties vs righties.
Team OPS — vs LHP & vs RHP
Full splits table
🧢 Bullpen Usage & Availability
Pitch counts from each team's last 3 days of games. 🔴 likely unavailable (back-to-back or high pitch load). 🟡 limited. 🟢 fresh.
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🔥 Hot / Cold Teams Report
Recent team performance over 3-day, 7-day, and season windows. W-L record, run differential, streak, offense and pitching breakdown.
🔥 Hot / Cold Hitters
Individual batter performance over the last 3 and 7 days. Find who's locked in and who's slumping before you bet player props.
⭐ Hitter Spotlight — Yesterday's Top Performers
Players who went off yesterday. Multi-hit games, home runs, high-impact performances. These are the bats to watch today.
Confirmed Lineups
Pulled live from MLB Stats API
Weather & Park Factors
Wind vector projected onto each park's home-to-CF orientation