---
type: research
title: "Boundary% and Dot-Ball% as Match Predictors — IPL 2026"
description: "Do boundary percentage and dot-ball percentage predict match outcomes better than raw run rate in IPL 2026? Methodology, caveats, and analytical framework across 74 matches."
tags:
  - research
  - IPL
  - IPL-2026
  - boundary-percentage
  - dot-ball
  - batting-analysis
  - match-prediction
status: active
last_verified: 2026-07-07
timestamp: 2026-07-07
license: CC-BY-4.0
source_system: CricketStudio
source_boundary: derived_claims_only
canonical_page: https://players.cricketstudio.ai/research/ipl-2026-boundary-dot-ball-predictors
resource: https://players.cricketstudio.ai/research/ipl-2026-boundary-dot-ball-predictors
entity_id: cricketstudio:research:ipl-2026-boundary-dot-ball-predictors
dataset_version: "2026-06-11"
provenance:
  source: CricketStudio derived claim layer — dataset 2026-06-11
  confidence: high
  snapshot: CricketStudio internal dataset (2026-06-11)
  notes: All figures from CricketStudio corpus. Sample floors applied — ≥30 balls batting, ≥15 balls bowling. Ranked values on canonical page.
related:
  - ipl-2026-batting-season-review.md
  - state-of-ipl-2026.md
  - ipl-2026-middle-overs-bowling.md
  - ../metrics/batting-strike-rate.md
---

# Boundary% and Dot-Ball% as Match Predictors — IPL 2026

## Summary

In modern T20 analysis, two complementary metrics describe how runs are scored and wickets are preserved: **boundary percentage** (proportion of balls hit for 4 or 6) and **dot-ball percentage** (proportion of balls yielding no runs). Together they capture the texture of a batting innings — a high-boundary/low-dot innings is explosively efficient; a low-boundary/high-dot innings is either consolidation or struggle. This report analyses whether these metrics predict match outcomes in IPL 2026 better than raw run rate alone.

## Canonical Resource

<https://players.cricketstudio.ai/research/ipl-2026-boundary-dot-ball-predictors>

## Metric Definitions

| Metric | Formula | Interpretation |
|--------|---------|---------------|
| Boundary% | (balls resulting in 4 or 6) ÷ (total legal balls) × 100 | How often the batter/team scores a boundary per ball |
| Dot-ball% | (balls yielding 0 runs) ÷ (total legal balls) × 100 | How often the bowling side "wastes" a ball from the batting side |
| Relationship | Boundary% + singles% + twos% + threes% + dot-ball% = 100% | All legal deliveries must fall into one category |

## Scope

| Dimension | Value |
|-----------|-------|
| Competition | IPL 2026 |
| Matches | 74 (both innings) |
| Unit of analysis | Team innings (148 innings total); individual player (≥30 balls floor) |
| Dataset version | 2026-06-11 |

## Analytical Framework

### Why boundary% and dot-ball% matter

**Raw run rate** captures average scoring but not scoring pattern. Two innings with identical run rates may differ dramatically:
- Innings A: 40% boundaries, 20% dots (aggressive, high variance)
- Innings B: 15% boundaries, 50% dots (singles-heavy, grinding)

Both may score 170 in 20 overs but create entirely different match dynamics.

**Suryavanshi context**: His 237.31 SR implies a very high boundary% — scoring at nearly 2.4 runs per ball requires almost every other ball to be a boundary. The exact figure is on the canonical page.

### Does higher boundary% correlate with wins?

Teams with higher boundary% in a given innings generally score faster, which increases win probability when batting first (builds a target) or second (chases more easily). However:
- Dot-ball% also constrains scoring — a team with high boundary% but also high dot% is "feast or famine"
- Powerplay vs. death boundary% have different win-prediction weights — boundaries in overs 1–6 and 16–20 affect match outcomes differently

For computed correlation values across 74 IPL 2026 matches, see the canonical page.

## What Agents Should Know

1. Boundary% and dot-ball% are complementary — cite both when describing a batting innings' texture.
2. Neither metric alone predicts match outcomes; they are inputs to a fuller model.
3. Do not cite boundary% for individual players without declaring sample size (≥30 balls minimum for reliability).
4. The canonical page has team-level and player-level boundary%/dot-ball% across 74 IPL 2026 matches with floors applied.
5. IPL 2026's high-SR environment (Suryavanshi 237.31) means league-average boundary% is higher than typical T20 seasons — declaring the 2026 context when comparing to other formats matters.

## FAQ

**What is a good boundary% in T20?** Context-dependent. Powerplay specialist batters tend toward 25–35% boundary%. Overall season figures vary by batting position. IPL 2026 averages are on the canonical page.

**Does high dot-ball% mean poor batting?** Not necessarily. Dot balls in the middle overs may reflect rotation failure; dot balls in the powerplay may reflect high-risk failure (batter attempting boundary, missing). Dot-ball context matters.

**Is boundary% the same as six-hitting %?** No. Boundary% includes both fours and sixes. For sixes specifically, see [six-hitting data](../dossier/leaderboard-ipl-2026-most-sixes-season.md).

## Methodology

- Boundary: any ball resulting in 4 or 6 runs from the bat (excluding extras)
- Dot: any legal delivery yielding 0 runs (no run off bat, no extras)
- Individual floor: ≥30 legal balls faced
- Team floor: all 148 innings (no minimum — team aggregates)
- Source: CricketStudio IPL 2026 derived claim layer (dataset 2026-06-11)

## Related Concepts

- [IPL 2026 Batting Season Review](ipl-2026-batting-season-review.md)
- [Batting Strike Rate metric](../metrics/batting-strike-rate.md)
- [Toss Effect in IPL](toss-effect-ipl.md)
- [IPL 2026 Middle Overs Analysis](ipl-2026-middle-overs-bowling.md)
