IPL 2026 AI Player Impact Index

Who actually wins matches — measured by win probability, not vanity stats

Updated: · 11 matches analysed · Data: CricketPrediction AI Model

AI-powered cricket analytics — holographic player impact data visualized on a cricket field at night

After 11 IPL 2026 matches, Sameer Rizvi (DC) leads our AI Player Impact Index with a match impact score of 9.8/10 — his batting shifted Delhi Capitals's win probability by 42.1%. This page tracks every player's real match impact — not runs or wickets, but how much they actually changed the outcome. Updated after every match.

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How the AI Player Impact Index Works

🎯

Win Probability Per Ball

Our AI model calculates win probability at every delivery. Each run, wicket, and fielding action shifts the number.

📊

Contribution = Shift

A player's impact is the total win probability they shifted. A 30 off 12 in a tight chase is worth more than 80 in a dead game.

🧠

Beyond Stats

We measure batting, bowling, AND fielding impact. A game-changing catch counts. Orange Cap and Purple Cap miss this entirely.

Overall Impact Leaderboard

#PlayerImpact ↓Win% Shift ↕
1
DC
Sameer Rizvi (DC)
9.8 /10+42.1%
💡 90 off 47 vs MI — chased 163 with ease. 70* vs LSG from 26/4. Orange Cap leader (160 runs, avg 160.00)
2
RCB
Tim David (RCB)
9.5 /10+36.8%
💡 70* off 25 (8 sixes) vs CSK — powered RCB to 250/3, highest total of IPL 2026
3
RR
Vaibhav Sooryavanshi (RR)
9.4 /10+34.2%
💡 52 off 17 balls vs CSK — fastest fifty of IPL 2026. 15 years old.
4
MI
Ryan Rickelton (MI)
9.2 /10+34.2%
💡 81 off 43 (8 sixes) on IPL debut vs KKR, 148-run opening stand with Rohit
5
PBKS
Cooper Connolly (PBKS)
9.1 /10+31%
💡 72* off 44 on debut to chase 163 vs GT. 108 runs in 2 matches at avg 108
6
RR
Ravi Bishnoi (RR)
9 /10+28.5%
💡 4/41 vs GT — joint Purple Cap leader with 5 wickets in 2 matches at econ 8.14
7
LSG
Rishabh Pant (LSG)
8.8 /10+26.4%
💡 68 vs SRH to seal a 5-wicket win, chasing 157. Proving captaincy credentials.
8
SRH
Heinrich Klaasen (SRH)
8.7 /10+24%
💡 145 runs in 3 matches (52 vs KKR, 62 vs LSG). SRH's most consistent batter.
9
RCB
Virat Kohli (RCB)
8.6 /10+22%
💡 69* vs SRH in opener — anchored the chase of 202 in 15.4 overs
10
RCB
Jacob Duffy (RCB)
8.5 /10+22.5%
💡 3/22 vs SRH (POTM), joint Purple Cap leader with 5 wickets in 2 matches
11
MI
Rohit Sharma (MI)
8.4 /10+21%
💡 78 off 38 (6 sixes) vs KKR in 221-run chase. 113 runs in 2 matches at avg 56.50.
12
LSG
Mohammad Shami (LSG)
8.3 /10+20.5%
💡 2/9 vs SRH — suffocated the powerplay. Proving fitness after comeback.
13
RR
Dhruv Jurel (RR)
8.2 /10+19.5%
💡 75 vs GT — anchored RR to 210/6 in a 6-run win
14
MI
Shardul Thakur (MI)
8.1 /10+18%
💡 3/39 vs KKR on MI debut — Player of the Match in 221-run chase
15
DC
T Natarajan (DC)
8 /10+17.5%
💡 4 wickets in 2 matches (3/29 best), econ 7.57 — DC's most reliable pacer
16
RCB
Devdutt Padikkal (RCB)
7.9 /10+16.5%
💡 61 off 26 vs SRH in opener. 111 runs in 2 matches at avg 55.50.
17
PBKS
Shreyas Iyer (PBKS)
7.8 /10+15%
💡 50 vs CSK — captain's knock to seal chase of 210. Leading PBKS to 2-0 start.
18
PBKS
Vijaykumar Vyshak (PBKS)
7.7 /10+14.5%
💡 Joint Purple Cap leader — 5 wickets in 2 matches (3/34 best), econ 9.00
19
RR
Yashasvi Jaiswal (RR)
7.6 /10+14%
💡 55 vs GT — set the platform for RR's 210/6. Best young batter in world cricket.
20
SRH
Jaydev Unadkat (SRH)
7.5 /10+13.5%
💡 3/21 vs KKR — triggered the 65-run collapse. SRH's most improved bowler.

🎯 Betting Insight: What If They're Missing?

When key players are ruled out, check the win probability drop before placing your bet.

PlayerTeamIf Missing
SRH Jaydev Unadkat
SRH6%
RCB Devdutt Padikkal
RCB6.5%
MI Ryan Rickelton
MI7%
RR Dhruv Jurel
RR7%
MI Shardul Thakur
MI7%
PBKS Vijaykumar Vyshak
PBKS7%
RCB Jacob Duffy
RCB7.5%
DC T Natarajan
DC7.5%

Methodology

Our AI prediction model processes every ball of every IPL 2026 match, calculating real-time win probability for both teams throughout the innings.

Each player receives credit (or debit) for how their actions — runs scored, balls faced, wickets taken, economy rate, catches, run-outs — shifted the win probability in their team's favour. This produces three sub-scores:

  • Batting Impact: Win probability shifted through runs scored, strike rate, and batting phase (powerplay runs count differently to death overs runs).
  • Bowling Impact: Win probability shifted through wickets, economy control, and bowling phase. A powerplay wicket in a chase is worth more than a 20th-over consolation wicket.
  • Fielding Impact: Catches, run-outs, and direct hits measured by the win probability swing they caused. A boundary-line catch in the 18th over of a tight chase is high-impact.

The composite Impact Score (0-10) weights all three and normalises across the season. The Clutch Rating isolates performance in high-leverage moments (win probability between 30-70%).

This is original data from CricketPrediction's AI model. It is not available on any other platform. See our prediction track record for model accuracy.

Frequently Asked Questions

What is the AI Player Impact Index?

Our AI Player Impact Index measures how much each player shifts their team's win probability during a match. Unlike traditional stats (runs scored, wickets taken), this index captures the actual match-winning value of each contribution — a 30 off 12 in a close chase is worth more than 50 off 40 in a dead rubber.

How is the impact score calculated?

Our AI prediction model calculates win probability at every ball of every match. Each player's batting, bowling, and fielding contributions are measured by how much they moved win probability in their team's favour. The impact score is a 0-10 composite rating combining all three contributions.

What does "Win Prob Shift" mean?

Win Probability Shift is the total percentage points a player moved their team's win probability during a match. For example, +22.5% means the player's contributions increased their team's chances of winning by 22.5 percentage points across the entire match.

What is the Clutch Rating?

The Clutch Rating (A+ to D) measures performance in high-pressure moments — when the match outcome is genuinely uncertain (win probability between 30-70%). A player who delivers in tight situations earns a higher clutch grade than one who pads stats in already-decided matches.

What does "Absence Impact" show?

Absence Impact estimates how much a team's win probability drops if that player is rested, injured, or unavailable. For example, -15% means the team's win probability drops by 15 percentage points without that player. This is especially useful for betting when key players are ruled out.

How often is the Player Impact Index updated?

The index is updated after every IPL 2026 match. Impact scores become more reliable as the season progresses — after 5+ matches, the ratings stabilise and provide a strong predictive signal for remaining fixtures.

Why is this different from Orange Cap and Purple Cap?

Orange Cap (most runs) and Purple Cap (most wickets) measure volume, not impact. A player can score 400 runs in easy chases and rank high on Orange Cap while contributing little to actual wins. Our index measures what matters: did your performance change the result?

Can I use the Player Impact Index for betting?

Yes — the Absence Impact column is directly useful for betting. When a key player is confirmed out, check their absence impact to gauge how much the team's probability shifts. Always combine this with other factors (venue, conditions, opponent) and gamble responsibly.

More IPL 2026 Analysis

Player impact data is for informational purposes. Betting involves risk. Never wager more than you can afford to lose. Gamble responsibly.