MLB Betting Analyzer

V2 Framework — How the Report is Structured

Every bet candidate — regardless of market — passes through the same six-check evaluation engine before appearing in the report. The engine produces a letter grade (A–F) and a recommendation tier. The top of the report shows your actionable plays; the full sweep table below it shows every candidate evaluated that day so you can audit the model's reasoning.

Section	What it shows
V2 Ranked Plays	Grade A (Best Play) and Grade B (Good Add) candidates with full detail — check bar, key factors, risk flags, and contradiction flags
Full Candidate Sweep	Every evaluated bet in one compact table grouped by grade tier. Use this to understand why a play was filtered out.
Today's Slate	DraftKings reference lines for all games
Detail Sections	Game bets (with key factors, injury/weather notes) and NRFI — full signal detail below the V2 ranked plays

V2 Six-Check System

Each check returns PASS ✓, WARN !, FAIL ✗, or N/A –. Checks that need unavailable data degrade to N/A without penalising the grade. Two points for PASS, one for WARN or N/A, zero for FAIL.

#	Check	What it evaluates	PASS condition
1	Baby Line	Line size, batter opportunity, run-line cushion	No baby-line flags, adequate PA opportunity, RL cushion ≥0.2 runs
2	Model Edge	Projection vs DK line (edge for game bets, DIFF% for props)	Edge ≥ threshold for the market type
3	Books Agree	DK implied direction + consensus lean % across all other books	DK agrees with model AND ≥55% of consensus books lean same side
4	Matchup	Park factor, weather, pitcher handedness vs lineup splits	Park/weather support the bet direction; platoon matchup neutral or favorable
5	Role / Injury	Confirmed lineup spot, injury flags, workload concerns	No injury flags; lineup confirmed in a favorable spot
6	Game Script	Combined park × weather run environment; run-line margin vs spread	Environment supports bet direction; RL margin cushion ≥0.5 runs

Grades & Recommendations

Grade	Score	Recommendation	When to bet
A	10–12, 0 FAILs	BEST PLAY	Core play — all six checks aligned
B	7–9, ≤1 FAIL	GOOD ADD	Strong play with minor caveats
C	4–6	PASS	Thin — skip unless you have a strong personal read
D	2–3 or model edge FAIL	PASS	Do not bet — weak signal
F	0–1	HARD FADE	Consider betting the other side

Hard override: a Model Edge FAIL always caps at Grade D regardless of other checks. Books Strongly Disagree caps at Grade C.

Contradiction Flags ⚡

When two recommended plays on the same game send opposing run-environment signals, a ⚡ contradiction flag is added to both plays. The bet is not removed — it is flagged so you can decide consciously whether the conflict makes sense.

Pattern	Why it conflicts
Total Over + NRFI	High-run game expectation vs no runs in the 1st inning
Total Under + YRFI	Low-run game expectation vs runs scoring in the 1st
K Prop Over + YRFI	Pitcher dominates yet run scores early
Batter Overs + Total Under	Player production expected but game total is low
Outs Over + K Under (same SP)	Long outing projected but few strikeouts — projection inconsistency

API Quota Bar

Element	Meaning
Progress bar	Visual fill of monthly Odds API usage
used / total	Requests consumed vs. your monthly cap — each run costs ~1 request per game (combined market fetch)

Today's Slate

Column	Meaning
Away ML / Home ML	DraftKings moneyline. −150 = bet $150 to win $100 • +130 = bet $100 to win $130
Away RL / Home RL	Run line (always ±1.5) with its odds. −1.5(−110) = team must win by 2+
Total	Over/Under line (e.g. O/U 8.5)
Con ML	Consensus moneyline direction — which side the majority of other books (FanDuel, BetMGM, Caesars, etc.) favor

Game Bets — Column Definitions

Column	Meaning
Size	FULL ≥20% edge • HALF 15–20% • QRTR at threshold. Capped at HALF if one SP missing, QRTR if both missing.
Type	Moneyline, Run Line, Total Over/Under
DK Odds	DraftKings price for that side
Implied	DK implied probability after vig removal
Model	Win probability our model calculates independently
Edge	Model% − Implied%. Min 15% to surface a game bet.
EV/$100	Expected profit per $100 wagered: (win_prob × profit) − (loss_prob × $100)
Conf	HIGH full SP + offense data • MED one source missing • LOW mostly league averages

How the Model Works — The Simple Version

The model is asking one question: does DraftKings have the wrong price on this game?

It independently calculates how likely each team is to win by grading two things: how good is today's starting pitcher (xFIP vs league average) and how good is the opposing lineup (wRC+ vs league average). It adds a small home-field bonus, blends in the pitcher's last 5 starts (35% weight), then converts the result to a win probability. That probability is compared to what DraftKings implies. If the gap is ≥15%, it surfaces as a bet.

The model caps at ~68–70% win probability even in extreme mismatches — baseball is unpredictable and overconfident models lose money. Missing data automatically reduces confidence and bet sizing.

How the Model Works — Win Probability (Technical)

For every game the model builds a score differential from three inputs, then converts it to a win probability using a logistic (S-curve) function. Here is each step:

Step	What it calculates	Data source	Weight
1. Pitching edge	How much better or worse each SP is vs. the league-average xFIP of 4.20. home_pitch = (4.20 − home_xFIP) / 4.20 pitch_edge = home_pitch − away_pitch A positive number means the home SP is above average relative to the away SP.	FanGraphs xFIP (direct API call) — the best early-season ERA predictor because it removes defense and luck	50%
2. Offense edge	How much stronger or weaker each lineup is vs. the league-average wRC+ of 100. home_bat = (home_wRC+ − 100) / 100 off_edge = home_bat − away_bat A team with wRC+ 110 contributes +0.10; one at 90 contributes −0.10.	MLB Stats API team batting — OPS converted to wRC+ via (OPS / 0.720) × 100	35%
3. Home field	Fixed constant added to the home team's side every game.	Historical MLB average home-field effect	+4%
4. Score diff	score_diff = 0.50 × pitch_edge + 0.35 × off_edge + 0.04	Combined signal driving the probability below
5. Win probability	home_win_prob = logistic(1.5 × score_diff) The logistic scale of 1.5 keeps the model from being overconfident — even an extreme mismatch caps out around 68–70%.	Standard logistic sigmoid: 1 / (1 + e−x)

Recent Form Blending

Season stats are stable but slow to react. Recent form can signal a pitcher heating up or falling apart. The model blends both:

Source	Weight	Stats blended
Season-to-date (FanGraphs)	65%	xFIP, ERA, WHIP, K%, K/9
Last 5 starts (MLB Stats API game logs)	35%	ERA, WHIP, K%, K/9 — computed from raw game log totals

xFIP is season-only (requires full-season HR data to normalize). ERA trend from recent starts adjusts the blended ERA implicitly.

How the Model Works — Expected Run Total

For Over/Under bets the model projects a total runs scored using a similar framework:

Step	Calculation
Base	2 × 4.5 league-average runs/game = 9.0
SP factor	Average of (home xFIP / 4.20) and (away xFIP / 4.20). Uses xFIP for consistency with the win-probability model — ERA includes luck and inflates totals for pitchers who got unlucky.
Offense factor	Average of (home wRC+ / 100) and (away wRC+ / 100).
Raw total	9.0 × (0.60 × SP factor + 0.40 × off_factor)
Park adjustment	Raw total × venue run factor (e.g. Coors 1.32, Oracle Park 0.92). Blended at 60% weight: 0.40 × raw + 0.60 × park_adjusted

Weather adjustments layer on top: headwind (N/NW/NE) × 0.93 on run total • tailwind (S/SW/SE) × 1.08 • cold (≤45°F) × 0.96

What IS Integrated

Factor	Status
Savant pitcher quality (xwOBA, xERA)	Integrated. SP quality in NRFI blends xFIP (60%) + xwOBA allowed (40%) when Savant data available.
Savant whiff% / put-away%	Integrated for K props. Primary projection driver when available (65% weight).
Opp pitcher contact quality for batter props	Integrated. Opposing pitcher xwOBA allowed adjusts batter projections (±up to 15%).
Lineup order / day-of lineup	Integrated for batter props (confirmed lineup spot + projected PA). Game-level model uses full-team season wRC+.

What IS Integrated (continued)

Factor	Status
Bullpen fatigue	Integrated (Session 16). Relief appearances over past 3 days tracked per team; tired pen (>2.7 RP/game avg) raises expected total via BULLPEN_WEIGHT (15%). Surfaced in Game Script check.
Rest days	Integrated (Session 16). Back-to-back teams receive a −1.5% win-probability penalty; well-rested teams receive a +1.0% bonus. Applied to full-game and F5 models.
Umpire K-rate	Integrated (Session 15). Static table of ~70 umpires with historical K/9 values. Wide-zone umps adjust K prop projections and NRFI scores up; tight-zone umps adjust down. Dampened ±12% cap.
Handedness / platoon splits	Integrated (Sessions 3 & 15). Opposing lineup wRC+ vs. SP hand sourced from MLB splits API. Platoon mismatch adjusts win probability ±2% per side (capped ±4% total). Surfaced in Matchup check.
Projection blend (regression to mean)	Integrated (Session 17). Stats regressed toward league average early in season: blend_w = IP ÷ 80 for pitchers, games ÷ 81 for teams. Prevents 5-IP ERA outliers from driving model in April.

What the Model Does NOT Include (yet)

Factor	Status
Batter vs. pitch-type matchup	Integrated. Savant team-vs-pitch-type xwOBA adjusts K prop projections and NRFI/YRFI scores when SP's primary pitch type is known. Opponent teams that struggle vs the SP's top pitch raise K over projections and NRFI scores.
Individual batter vs. pitcher H2H	Planned for a future phase.
Pre-season projection prior (Steamer/ZiPS)	Not integrated — projection endpoints not available. Regression-to-mean (blending toward league avg by IP) used as a practical substitute.

NRFI — No Run First Inning

Column	Meaning
Away SP / Home SP	Probable starter name (or TBD if not yet announced)
NRFI Score	Composite score out of 10. ≥7.7 = PLAY. SP quality (40%) blends xFIP + xwOBA allowed when Savant data is available; K-rate (35%); team offense (25%)

Sizing Guide

Label	Edge Required	Suggested Unit Size
FULL	≥20%	Full unit
HALF	≥15%	Half unit
QRTR	≥15%	Quarter unit (data quality cap)
(none)	<15%	No bet — below threshold

Confidence Guide

Label	What it means
HIGH	Both pitchers and both offenses have full stat profiles
MED	One or more data sources are missing or incomplete
LOW	Model running mostly on league averages — proceed with caution

Model Notes

Term	Definition
xFIP	Expected Fielding Independent Pitching — ERA predictor that strips out defense and luck. Lower = better pitcher. League avg ~4.20
wRC+	Weighted Runs Created Plus — offensive quality. 100 = league average. 115+ = above average. Estimated from team OPS via MLB Stats API
Recent form	Last 5 starts blended at 35% weight, season stats at 65%
Park factor	Venue run/HR factor applied to expected total. Coors Field ~1.32, Oracle Park ~0.92
Edge	Model win probability minus the book's implied probability (after vig removal)
EV/$100	Expected value: (win_prob × profit) − (loss_prob × stake)
F5 bets	First 5 innings — pitching weight raised to 65% (starters matter more), scaled to 4.5/9.0 IP
DK note	The "Bet on DK" button opens DraftKings' MLB section. Game-specific deep links require DK's partner event ID, not included in the free Odds API tier

Disclaimer: For informational and research purposes only. Bet responsibly. Always verify probable pitchers and lineups before placing any bet. Past model performance does not guarantee future results.