My musings: How IPL Teams Use Game Theory

Introduction

In elite-level cricket, strategy is no longer just about instinct. It’s about interpreting patterns, anticipating decisions, and shaping outcomes. At the heart of this evolution lies game theory—a powerful tool that helps IPL franchises and international teams make data-backed, scenario-based decisions.

Game theory doesn’t require full access to every data point. Even with limited information, such as wagowheels or dismissal zones, smart teams can draw actionable insights. This blog breaks down how elite teams use game theory in real match scenarios—and how both bowlers and batters can use the same framework to gain a strategic edge.

Section 1: What Is Game Theory and Why Does It Matter in Cricket?

Game Theory is the study of decision-making between two or more strategic players where each player's best choice depends on the decisions of others.

In cricket, it applies to:

Bowlers and captains: Field Setting and delivery sequences
Batters: Choosing scoring options based on field placement and bowler behavior

You don’t need Hawkeye or full match analytics to apply game theory. Even local leagues, academy setups, and teams with basic wagon wheels can benefit.

🔍 Core Principles in Cricket Context:

🎯 1. Nash Equilibrium

Definition: A balanced state where neither side benefits from changing strategy unless the other does.
Cricket Example: Batter safely rotates strike, bowler contains without risk — both waiting for the other to break the pattern.

🔁 2. Mixed Strategy

Definition: Randomized decisions to stay unpredictable.
Cricket Example: Bowler varies length, speed, and line to prevent premeditated shots. Batter changes rhythm between sweep, nudge, and loft to remain unreadable.

❌ 3. Dominated Strategy

Definition: A consistently poor decision that leads to inferior outcomes.
Cricket Example: Batter keeps slogging across the line despite fielders set for it. Bowler keeps bowling short to a hooker with deep square and fine leg open.

Section 2: What Do Elite Teams Actually Do?

Elite teams like IPL franchises follow a scenario-matching model using limited but rich data:

Wagon wheels: From KSCA app or manual analysis
Dismissal patterns: Who gets out where and how
Score phase pressure: Acceleration vs consolidation
Match-ups: Lefty vs wrist spin, power vs pace

🧠 Case Study 1: Bumrah vs Russell (IPL)

Situation: Final over, Russell on strike, field spread, expected yorker

What actually happened:

Bumrah starts with a slower bouncer
Next ball: wide yorker
Then: quick body ball
Each ball challenges Russell’s rhythm

Game Theory at Play:

Bumrah didn’t fall into a predictable pattern (mixed strategy)
Each ball was aimed at restricting Russell’s comfort zones (forcing him into a dominated decision)

🧠 Case Study 2: Steve Smith and Ravi Shastri’s Game Plan

During Steve Smith’s peak in Test cricket, especially in 2020-21, he dominated scoring through the off-side — late cuts, drives, back-foot punches.

Ravi Shastri’s Direction to Indian Team:

Bowlers were told: “Nothing on the off-side. Bowl straight with on-side field.”
Objective: Force Smith to play across the line into the leg-side, increasing chances of LBW or bowled
Smith’s trigger movement and open stance made it tough to bowl at him conventionally — so India reversed the strategy

Why It Worked Initially:

Smith had limited boundary options
Was forced to manufacture shots
Got out playing across or mistiming

Why It Was Abandoned Later:

Successor coaches moved back to traditional off-stump plans for whatever reason

Lesson:

Game theory sometimes looks counterintuitive. Playing against a batter’s strength isn’t always smart — but denying him his preferred scoring zone forces adaptation, which creates windows for dismissal.

This was a perfect real-life application of game theory: deny the high-probability zone, herd into low-probability scoring areas, and create pressure.

Section 3: Game Theory from a Batter’s Perspective

Elite batters don’t just react — they reverse-engineer intent.

“What is the bowler trying to make me do?” → Then: “How do I flip it or delay it?”

🔄 Three Tools Elite Batters Use:

Map Field Imbalance
- Fine leg up → Ramp in play
- Off-side packed → Bait to go leg side
- Deep midwicket only → Invite loft, deny pull
Break Rhythm
- Step across, delay trigger, or walk out to disrupt bowler’s length
Manipulate the Field
- Score in awkward zones → Force field shift → Then attack opened zone

📚 Real Example: Kane Williamson in T20

May face 6 dot balls early
Quiet rotation forces captain to shift field
Then targets the freshly exposed region with one big over

That’s not passivity. That’s controlled deception using game theory.

📚 Real Example: Sachin Tendulkar vs Sri Lanka

Situation: Sri Lanka packed the leg-side and bowled at his pads to dry up scoring options.

What Sachin did:

Pulled out the sweep shot, a stroke rarely used by him
Used it consistently to attack the on-side with control
Disrupted the bowler’s rhythm and the captain’s field plan

Game Theory Insight:

Sri Lanka had created a Nash Equilibrium: bowl at pads, deny off-side, expect dot balls
Tendulkar broke the pattern by introducing a low-risk but high-reward response (sweep)
Once the sweep came into play, fielders had to be moved, and the original plan unraveled

This was a masterclass in using game theory to flip a pre-set field plan by introducing an unanticipated but effective counter-move.

🎯 What Grassroots Batters Can Copy:

At the grassroots level, batters don’t always face structured bowling plans. But even without data or visible tactics, you can use simplified game theory thinking to stay one step ahead:

After a dot: Ask, “What’s the field telling me?” instead of “What shot should I play?”
👉 Most bowlers won’t have a plan—but you can still observe intent. Is the bowler repeating length? Is the field shifting subtly? Stay watchful.
When the field changes: Ask, “What just got exposed?” and “What trap is being set for me?”
👉 A sudden deep midwicket fielder or a fine leg up is a clue. Don’t chase the bait blindly.
Against repeat balls: Instead of reacting the same way, ask, “What other options do I have if it lands here again?”
👉 Change footwork, angle of bat swing, or tempo — to stay ahead of predictability.

Section 4: Applying Game Theory at the Grassroots and Club Level

Game theory isn’t just for IPL teams. Even club and academy cricketers can use it to:

Bowl smarter
Set proactive fields
Avoid reactive errors

🎯 Core Question for Bowlers:

"Where do I want the batter to hit?"

Then:

Choose fielders for that shot
Bowl to force that option
Make sure it’s risky or low scoring

🧩 Club-Level Field Setting Mini-Framework:

Find the batter’s favorite zones (via memory or wagon wheel)
Shut those zones with field + bowling
Leave open zones where batter is uncomfortable

✅ Coach Drills:

Set a goal: “Force 3 bad decisions per over”
Ask your bowlers: “What is the worst shot this batter can play? Now make him play it.”
Batting nets: “Where is the trap? Where can you safely rotate?”

Game theory simplifies cricket. It’s not about guessing — it’s about narrowing options and shaping outcomes.

Section 5: How to Build Plan A, B, and C Using Game Theory

The smartest teams don’t just build one plan — they build flexible branches:

✅ Plan A: Control the Default Behavior

Identify the batter’s natural scoring pattern (e.g., cover drive)
Block that option with line + field

✅ Plan B: Pressure with Deception

If Plan A creates pressure → use variation to invite error
Example: Yorker plan → then slower one in slot

✅ Plan C: Flip the Field

If batter adapts and scores → move field radically
Force them to rethink their pattern again

The key is to create decision discomfort in the opponent.

📋 How to Make These Plans:

Identify key scoring shots (via video or memory)
Build a counter plan to deny it
Have a secondary trap if they adapt
Always keep one move unrevealed (last-ball surprise)

This is not “overthinking.” It is dynamic adaptation that elite captains and bowlers like Dhoni, Ashwin, or Bumrah use over a T20 spell.

🧾 Summary Checklist for Coaches and Players

✅ Ask: What do THEY want me to do?
✅ Choose: What is the worst outcome for THEM?
✅ Plan: Where will I direct the play?
✅ Adjust: If they change strategy, what’s my next best move?
✅ Prepare: Plan A (default), Plan B (variation), Plan C (reset)

Whether you’re an IPL analyst or a 3rd division club seamer — this approach wins moments, which win games.

📢 Final Thought: Game theory is not theory anymore. It’s applied, everyday thinking — disguised as smart cricket. Learn it, apply it, teach it.

Sunday, June 15, 2025

How IPL Teams Use Game Theory — And How You Can Too