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Paper #1In active draftingMLB

Closing Line Value Is the Metric That Matters: A 2,682-Pick MLB Empirical Study

The folkloric claim that CLV predicts ROI, tested on 2,682 graded MLB picks across three independent model versions. Headline finding: CLV explains roughly 2.5× more variance in cohort ROI than win rate (R² 0.49 vs 0.20).

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What's in the paper

  • ~15-20 page PDF, citation-ready
  • Full methodology, reproducible from any pick history with the same fields
  • Print-resolution charts (bucket analysis, cross-version scatter, regression face-off)
  • Robustness appendix — bootstrap CIs, sample-size convergence, version cross-validation
  • Glossary + references to academic literature

Data used

Every field that goes into the analysis. Open methodology — you can reproduce this paper from any pick history with these columns.

FieldTypeSourceWhat it means
pick_idBIGINTmlb_picksUnique identifier for each graded MLB pick.
model_versionTEXTmlb_picksWhich OddsIQ model version generated the pick (v1, v2, v3).
pick_dateDATEmlb_picksCalendar date the pick was generated and bet would have been placed.
pick_teamTEXTmlb_picksTeam selected by the model.
opponent_teamTEXTmlb_picksOpposing team for the same game.
bet_marketTEXTmlb_picksMarket type — moneyline only for this paper (spreads/totals deferred).
entry_bookTEXTmlb_picksSportsbook used to record the entry price.
entry_oddsINTmlb_picksAmerican odds at the moment the pick was generated.
closing_bookTEXTmlb_picksSportsbook used as the closing-line reference (typically Pinnacle).
closing_oddsINTmlb_picksAmerican odds at game start (sharp closing line).
entry_implied_probNUMERIC(5,4)mlb_picksRaw implied probability from entry odds (with vig).
closing_implied_probNUMERIC(5,4)mlb_picksRaw implied probability from closing odds (with vig).
entry_no_vig_probNUMERIC(5,4)mlb_picksDevigged entry probability — both sides normalized to 100%.
closing_no_vig_probNUMERIC(5,4)mlb_picksDevigged closing probability — the headline CLV input.
clv_pctNUMERIC(6,4)mlb_picksClosing minus entry no-vig probability — the per-pick CLV.
bet_outcomeTEXTmlb_picksGraded outcome — win, loss, or push.
units_stakedNUMERIC(6,3)mlb_picksStake size in units, derived from the model’s Kelly fraction.
units_returnedNUMERIC(7,3)mlb_picksNet units after grading (negative for loss, +odds for win).
roi_per_pickNUMERIC(6,4)derivedunits_returned / units_staked. The dependent variable.