Glossary

A

Anchor Batter

A top-order batter expected to face many balls with relatively stable output. Impact: increases floor in small-field study scenarios; may reduce ceiling when stacked with too many low-tempo partners.

Aggression Rate

Proxy for boundary intent (balls per boundary, attacking %). Impact: useful for identifying ceiling candidates in powerplay-friendly venues.

All-Rounder

Player contributing with both bat and ball. Impact: boosts lineup balance; volatility hinges on role certainty (overs bowled, batting position).

B

Boundary Rate

Frequency of 4s/6s per balls faced. Impact: key ceiling driver; sensitive to venue size and bowling type.

Bowling Phases

Overs allocated by phase (PP, middle, death). Impact: death overs add wicket upside but higher economy risk.

Bench Risk

Probability a selected player doesn’t feature. Impact: avoid unless large-field ceiling warrants it.

C

Captaincy

Multiplying a player’s points in conceptual exercises. Impact: amplifies both upside and downside; align with role certainty and conditions.

Correlation

How player outcomes move together. Positive: opening batter + same-side top-order. Negative: bowler dominating vs. opposition batters.

Contest Fit

Matching lineup volatility to field size and hypothetical payout curvature. Impact: smaller fields favor stability; larger fields tolerate leverage and contrarian builds.

D

Death Overs

Final overs of an innings with high wicket and boundary volatility. Impact: ceiling for strike bowlers and finishers; economy risk for bowlers.

Dew Factor

Moisture affecting grip and swing late. Impact: may aid chasing; adjust expectations for spin at night venues.

E

Expected Value (EV)

Weighted average outcome of a decision under uncertainty. Impact: compare options with both probability and payoff in mind; avoid chasing results from tiny samples.

Entry Timing (Conceptual)

In study scenarios, when you’d finalize a lineup relative to information flow. Impact: late role clarity increases certainty; early stance can be more contrarian.

F

Finisher

Middle/lower-order batter specializing at the death. Impact: volatile ceiling; exposure should match contest fit.

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G

Game Script

Hypothesized flow (e.g., spin-heavy choke, batting-friendly chase). Impact: drives correlation stacks and hedges.

GPP (Large-Field) — Concept

Hypothetical large-field format emphasizing ceiling and leverage. Impact: accept variance; target unique combinations.

H

H2H — Concept

Head-to-head study scenario prioritizing floor and role certainty over fragile upside.

Handedness Matchups

RHB/LHB vs. bowlers’ angle/spin type. Impact: small edge; avoid overfitting micro-splits.

I

Impact Player (Contextual)

Format-specific substitution concept. Impact: introduces role/overs uncertainty; monitor announcements.

Innings Anchor vs. Accelerator

Stability vs. pace trade-off. Impact: combine both profiles to diversify outcome paths.

L

Leverage (Concept)

Benefiting when the field underweights a viable outcome. Impact: strongest in large-field scenarios.

Lineup Diversification

Spreading exposure to reduce single-point failure. Impact: control variance across a portfolio study set.

M

Matchups & Micro-Splits (Caution)

Historical head-to-head, pace/spin splits. Impact: treat as tiebreakers unless sample sizes are meaningful.

Middle Overs

Stabilization phase. Impact: rewards accumulators and control bowlers; ceiling lower than PP/death.

O

Opportunity Share

Share of balls faced / overs bowled. Impact: primary driver of EV; role certainty matters as much as talent.

Ownership (Conceptual Popularity)

How common a pick would be in a hypothetical field. Impact: informs leverage and contrarian decisions.

P

Powerplay (PP)

First field-restriction phase. Impact: boosts boundary rates for openers; early wickets spike bowler ceilings.

Pitch Archetype

Broad surface profile (pace-friendly, spin-friendly, two-paced). Impact: affects role preference and stack logic.

Payout Curve (Conceptual)

Hypothetical distribution of rewards by rank in a contest model. Impact: steep curves justify higher variance.

R

Regression to the Mean

Extreme performances drift toward averages over time. Impact: avoid overreacting to tiny samples.

Role Certainty

Confidence in batting position or overs. Impact: primary floor driver in small-field study builds.

S

Stacking

Combining positively correlated players. Impact: increases lineup ceiling; use diversification to cap downside.

Strike Rate (SR)

Runs per 100 balls. Impact: PP and death overs amplify SR’s effect on scoring in many scoring models.

Sample Size

Amount of data behind an estimate. Impact: small samples inflate noise; prefer stable indicators for core choices.

T

Team Balance

Coverage of roles (anchors, accelerators, all-rounders, strike/death bowlers). Impact: reduces outcome clashes.

Toss Bias (Context)

Conditions changing advantage between batting first vs. chasing. Impact: adjust phase expectations and risk.

U

Upside

High-end outcome potential. Impact: death overs and boundary-friendly venues elevate upside for certain roles.

Usage Certainty

Confidence a player will actually be used as expected (overs, slot). Impact: strong tiebreaker for captaincy.

V

Variance

Outcome volatility around the average. Impact: manage via contest fit, diversification, and correlation.

Venue Effects

Ground size, altitude, surface wear, and typical pace/spin balance. Impact: nudge projections and stacks.

W

Wicket-Taking Rate

Wickets per over or balls per wicket. Impact: driver of bowler ceiling; death overs influence strongly.

Win-Probability Model (Concept)

Abstract model to reason about match state shifts. Impact: helps anticipate correlation swings and hedges.