Carolina Lefthander
    Request an Audit
    Independent Baseball Analytics

    THE NUMBERSDON'T PLAYFAVORITES

    A written record that exists before the decision does.
    NAMES REMOVED
    OIR
    1
    M. Braswell
    71.2
    2
    C. Alvarez
    58.4
    3
    D. Kirkland
    44.1
    4
    R. Boone
    66.9
    5
    J. Whitfield
    82.8
    6
    T. Sedgwick
    51.3
    7
    A. Coulter
    74.5
    8
    P. Nash
    39.7
    Identifiers stripped from the sheetIllustrative sequence. Names and ratings are fictional.
    4.1
    Runs gained per season
    45/35/20
    TPR Weights
    ≥25
    At-bats to qualify
    02 — Services

    WHAT WE PUT IN WRITING

    Player profiles that identify what to fix

    Multi-dimensional evaluation across hitting, pitching, and fielding, with the sample size behind every number stated. You get a ranked list of what to work on next, not a grade.

    Coaching intelligence

    Data-driven batting orders, pitching rotations built around arm health, and end-of-season evaluations written so a coach can hand them to a parent.

    Team selection and tryout audits

    Mathematical ranking indices applied to tryout data with names stripped off until the grading is done.

    Custom work

    If the question is specific to your program, we will tell you whether the data can answer it before you pay for the answer.

    03 — The Problem

    FOUR PLACES A DECISION GETS MADE FOR YOU

    BIAS VECTOR 1

    AT THE TRYOUT THE NAME ARRIVES BEFORE THE SWING

    Evaluators see the last name, the org on the shirt, and last year's team before a player takes a rep. Even the order players go in moves the scores. Blind evaluation strips the identifiers off the sheet until the grading is done.

    BIAS VECTOR 2

    ON THE LINEUP CARD THE ORDER IS BUILT ON HABIT

    Fastest kid leads off. Biggest kid bats fourth. It is how it has always been done, and it quietly leaves runs on the field every week — usually by burying the player who gets on base the most.

    BIAS VECTOR 3

    IN THE RECRUITING PITCH A HIGHLIGHT REEL SHOWS TWELVE SECONDS

    A reel shows a player at his best. It cannot show a hundred at-bats, a walk rate, or who he faced. College staffs know this, which is why the profiles that travel well are the ones with a full season behind them.

    BIAS VECTOR 4

    AFTER THE ROSTER POSTS EVERYONE HAS A THEORY BY MONDAY

    A cut gets explained in the parking lot, not in writing, and the explanation shifts depending on who is asking. An audit reruns the decision against the numbers that existed at the time. Sometimes it confirms the coach — that result is worth having too.

    04 — Demonstration

    The same nine players, two orders

    Below is a real batting order built the way most orders get built, and the same nine players sequenced by a model. Toggle between them.

    SLOTPLAYEROBPSLG
    3Player A.677.861
    1Player B.573.957
    2Player D.617.633
    5Player E.610.683
    7Player F.527.556
    6Player H.533.592
    4Player J.517.520
    8Player K.474.410
    9Player L.480.309

    2 spots set by reputation

    05 — Methodology

    CLEAR ARCHITECTURE, PROVEN CONTEXT, NO BLACK BOX

    Rather than relying on rigid, one-size-fits-all algorithms or gut feelings, our framework blends mathematical precision with the situational art of baseball. We evaluate the whole athlete across the core phase indices that drive run creation and prevention.

    IndexCore FocusWeight in TPR *
    OIR — Offensive Impact RatingHitting production, damage, and plate discipline45%
    PIR — Pitching Impact RatingRun suppression, command, and workload efficiency35%
    DIR — Defensive Impact RatingFielding efficiency and position-adjusted reliability20%
    TPR — Total Player RatingComprehensive composite of all active phases

    * Standard weighting. Emphasis may shift to fit the question being asked — a pitching-heavy roster or a defense-first evaluation can be weighted differently. Any change from 45/35/20 is stated in writing before work begins.

    THE SCIENCE MEETS THE ART

    Data only tells the truth when paired with proper context. Our framework stays rigorous and proprietary, but effective evaluation is an art.

    Age and development curves. A metric at 10U means something vastly different at 14U or showcase levels. We weight and interpret numbers relative to developmental baselines.

    Sample size integrity. We never draw definitive conclusions from noisy, limited data. Our reports state the reliability thresholds for every stat shown.

    Role-specific context. TPR is a complete two-way valuation. For dedicated position players who do not pitch, we do not penalize the overall profile — we weight and elevate OIR and DIR so parents and coaches see true position value without distortion.

    06 — The Margin
    4.1

    Runs per season

    That is the real number, and it is smaller than any consultant will try to sell you. Four runs across a season sounds like nothing — until you remember that most bracket weekends turn on a single run.

    The big one is roster construction. Picking the wrong players for a roster costs several times what a lineup card ever will, and it is the decision most exposed to who a coach already knows. That is the one worth doing blind.

    07 — Deliverables

    What arrives, and what it looks like

    Tryout audit sample available on request.

    The player performance profile

    A full-season written report on one player: hitting and pitching lines, advanced rates, competition context, sample-size confidence bands, and a ranked list of development priorities. Optional add-on: benchmarking against any standard you name — existing teams, all-star squads, leagues, All-State rosters, national teams.

    End-of-season team evaluation

    Every qualifying player ranked across all three phases, with written findings explaining where the model disagrees with the eye test and why. Built so a coach can hand it to a parent.

    Coaching and operational advisory

    Team selection, tryout audits, and roster construction run against the numbers that existed at the time of the decision.

    Optimized lineups and rotations

    Sabermetric batting orders built to maximize run production, and pitching rotations built around arm health first.

    08 — Confidence

    DATA INTEGRITY & SAMPLE CONTEXT

    Not all statistics stabilize at the same rate. Knowing which ones have settled and which ones have not is the difference between data and intelligence.

    Sample DepthTypicalWhat It SupportsConfidence
    Full season~100 ABDevelopmental curves and true talent levelHigh
    Extended weekend~6 IP / 12 ABApproach, zone control, plate disciplineModerate
    Single outing3-6 IP or 2-4 ABMechanical trends, watched not concludedEarly

    DATA SCIENCE MEETS REAL-WORLD EXPERIENCE

    Walk rate and strikeout rate settle early. Batting average and a short-stint ERA move on luck long after. Reading one as though it were the other is how a good player gets cut and a lucky one gets promoted.

    Age-appropriate baselines. Thresholds built for youth and prep baseball, not borrowed from professional models.

    Signal over noise. Isolating repeatable skill from tournament variance.

    Our reports state the reliability threshold for every stat shown.

    09 — Start

    Tell us what decision you are trying to make

    We will tell you whether the data can answer it before you pay for the answer.

    Or reach us directly at info@carolinalefthander.com