CRICMIND.ai
HOMEPLAYERSCOMPARE
PLAYER INTELLIGENCE · IPL 2026 · 9 COMPARISONS

COMPARE IPL PLAYERS — HEAD TO HEAD

Side-by-side comparison of IPL 2026 players across career stats and CricMind's proprietary 6-dimensional AI DNA profile. Every number is backed by data from 18 IPL seasons (2008-2025). No opinions — only statistics.

QUICK JUMP · SELECT A COMPARISON
Virat Kohli vs Rohit SharmaJasprit Bumrah vs Rashid KhanHardik Pandya vs Ravindra JadejaSuryakumar Yadav vs Travis HeadRishabh Pant vs Sanju SamsonShubman Gill vs Yashasvi JaiswalPat Cummins vs Mitchell StarcVarun Chakravarthy vs Yuzvendra ChahalRuturaj Gaikwad vs Rajat PatidarJosh Hazlewood vs Kagiso Rabada
HOW TO READ THESE COMPARISONS

Each comparison shows two layers of analysis. First, raw IPL career statistics — matches played, runs scored, wickets taken, strike rate, and economy rate. The W marker indicates which player leads in each category.

Second, the AI DNA Profile — six contextual dimensions that go beyond raw stats. These measure how a player performs under pressure, in run chases, during powerplay and death overs, and against spin versus pace bowling. The composite DNA Score (0-100) determines the overall AI Edge verdict.

BATTING LEGENDS
VIRAT KOHLI
Royal Challengers Bangalore · BAT · IND
VS
ROHIT SHARMA
Mumbai Indians · BAT · IND
97
DNA SCORE
96
IPL CAREER STATS
252
MATCHES
W256
8100W
RUNS
6400
131.6
STRIKE RATE
W131.8
AI DNA PROFILE · 6 DIMENSIONS
96
PRESSURE
90
98
CHASE
92
82
POWERPLAY
95
78
DEATH
74
88
vs SPIN
88
92
vs PACE
90
AI EDGE:VIRAT KOHLIDNA 97
BOWLING GOATS
JASPRIT BUMRAH
Mumbai Indians · BOWL · IND
VS
RASHID KHAN
Gujarat Titans · BOWL · AFG
98
DNA SCORE
95
IPL CAREER STATS
146W
MATCHES
110
165W
WICKETS
130
7.4
ECONOMY
W6.55
AI DNA PROFILE · 6 DIMENSIONS
97
PRESSURE
92
45
CHASE
55
90
POWERPLAY
70
99
DEATH
88
40
vs SPIN
98
98
vs PACE
42
AI EDGE:JASPRIT BUMRAHDNA 98
ALL-ROUNDERS
HARDIK PANDYA
Mumbai Indians · AR · IND
VS
RAVINDRA JADEJA
Rajasthan Royals · AR · IND
91
DNA SCORE
91
IPL CAREER STATS
132
MATCHES
W226
2480
RUNS
W2780
153.2W
STRIKE RATE
128.4
60
WICKETS
W148
9.1
ECONOMY
W7.62
AI DNA PROFILE · 6 DIMENSIONS
88
PRESSURE
88
85
CHASE
80
72
POWERPLAY
60
92
DEATH
82
78
vs SPIN
92
84
vs PACE
70
AI EDGE:HARDIK PANDYADNA 91
EXPLOSIVE BATTERS
SURYAKUMAR YADAV
Mumbai Indians · BAT · IND
VS
TRAVIS HEAD
Sunrisers Hyderabad · BAT · Australia
92
DNA SCORE
91
IPL CAREER STATS
165W
MATCHES
28
4100W
RUNS
850
147.5
STRIKE RATE
W167.5
AI DNA PROFILE · 6 DIMENSIONS
84
PRESSURE
86
90
CHASE
82
78
POWERPLAY
95
88
DEATH
72
92
vs SPIN
80
86
vs PACE
90
AI EDGE:SURYAKUMAR YADAVDNA 92
KEEPER-BATTERS
RISHABH PANT
Lucknow Super Giants · WK · IND
VS
SANJU SAMSON
Chennai Super Kings · WK · IND
92
DNA SCORE
86
IPL CAREER STATS
109
MATCHES
W160
3500
RUNS
W4100
149.2W
STRIKE RATE
137.2
AI DNA PROFILE · 6 DIMENSIONS
85
PRESSURE
74
90
CHASE
82
82
POWERPLAY
86
88
DEATH
70
90
vs SPIN
82
80
vs PACE
78
AI EDGE:RISHABH PANTDNA 92
NEXT-GEN OPENERS
SHUBMAN GILL
Gujarat Titans · BAT · IND
VS
YASHASVI JAISWAL
Rajasthan Royals · BAT · IND
90
DNA SCORE
93
IPL CAREER STATS
82W
MATCHES
52
2540W
RUNS
1770
139.8
STRIKE RATE
W163.5
AI DNA PROFILE · 6 DIMENSIONS
84
PRESSURE
82
86
CHASE
88
88
POWERPLAY
95
72
DEATH
78
85
vs SPIN
85
82
vs PACE
90
AI EDGE:YASHASVI JAISWALDNA 93
OVERSEAS PACE
PAT CUMMINS
Sunrisers Hyderabad · AR · Australia
VS
MITCHELL STARC
Delhi Capitals · BOWL · Australia
90
DNA SCORE
88
IPL CAREER STATS
50W
MATCHES
18
350W
RUNS
25
148.5W
STRIKE RATE
72
42W
WICKETS
18
8.7W
ECONOMY
9.5
AI DNA PROFILE · 6 DIMENSIONS
92
PRESSURE
85
72
CHASE
18
78
POWERPLAY
92
85
DEATH
88
45
vs SPIN
28
92
vs PACE
96
AI EDGE:PAT CUMMINSDNA 90
NEW CAPTAINS
RUTURAJ GAIKWAD
Chennai Super Kings · BAT · IND
VS
RAJAT PATIDAR
Royal Challengers Bangalore · BAT · IND
87
DNA SCORE
84
IPL CAREER STATS
72W
MATCHES
32
2280W
RUNS
860
136.4
STRIKE RATE
W152.8
AI DNA PROFILE · 6 DIMENSIONS
82
PRESSURE
86
86
CHASE
80
88
POWERPLAY
70
72
DEATH
82
84
vs SPIN
78
80
vs PACE
84
AI EDGE:RUTURAJ GAIKWADDNA 87
OVERSEAS PACE ACES
JOSH HAZLEWOOD
Royal Challengers Bangalore · BOWL · AUS
VS
KAGISO RABADA
Gujarat Titans · BOWL · SA
86
DNA SCORE
88
IPL CAREER STATS
38
MATCHES
W62
45
WICKETS
W78
8W
ECONOMY
8.4
AI DNA PROFILE · 6 DIMENSIONS
88
PRESSURE
88
30
CHASE
40
85
POWERPLAY
86
86
DEATH
90
28
vs SPIN
38
92
vs PACE
94
AI EDGE:KAGISO RABADADNA 88

WHY PLAYER COMPARISON MATTERS IN IPL

The Indian Premier League has 220+ players across 10 franchises in IPL 2026. Every cricket fan has opinions about who is better — Kohli or Rohit, Bumrah or Rashid Khan, Pant or Samson. But most of these debates rely on memory, recency bias, and team loyalty rather than comprehensive statistical analysis.

CricMind's player comparison tool changes this. By analysing 278,205 ball-by-ball deliveries across 18 IPL seasons (2008-2025), we surface patterns that are invisible to the naked eye. A player's batting average might look impressive, but how does it change in the death overs? Under chase pressure? Against left-arm spin specifically? These contextual splits reveal the true quality of a player far better than headline numbers.

The six DNA dimensions were designed specifically for T20 cricket. In Test cricket, technique and patience matter most. In ODIs, stamina and adaptability are key. But in T20s, and especially in the IPL, there are six skills that separate match-winners from passengers:

PRESSURE PERFORMANCE

How does the player perform when the match is on the line? Close finishes (margins under 15 runs or 2 wickets), playoffs, and must-win league games are weighted separately. A player who averages 40 in dead rubbers but 22 in playoffs has a low pressure score.

CHASE MASTERY

Second-innings batting is fundamentally different. The target is known, the required rate is calculable, and the scoreboard pressure mounts every ball. Chase mastery measures how well a player adjusts their game to the run chase context — acceleration timing, risk assessment, and conversion rate in successful chases.

POWERPLAY DOMINANCE

Overs 1-6 with only two fielders outside the circle. Batters must be aggressive but not reckless. Bowlers must attack despite field restrictions. The powerplay DNA score measures runs scored per ball, dot ball percentage (for batters), and economy rate below 7 rpo (for bowlers) in this phase.

DEATH OVER ABILITY

Overs 16-20 are where matches are won and lost. The best finishers (Hardik Pandya, Rinku Singh, MS Dhoni) can score at 200+ strike rate under pressure. The best death bowlers (Bumrah, Arshdeep) can maintain sub-8 economy. This dimension is the single most predictive of match impact in T20 cricket.

SPIN PERFORMANCE

IPL pitches vary from spin-friendly (Chepauk, Kotla) to pace-dominant (Wankhede, Mohali). A batter's ability to read and attack spin — or a spinner's ability to contain and take wickets — directly determines their value on half the IPL venues. Measured across all encounters with spin bowlers in career IPL data.

PACE PERFORMANCE

Facing 140+ kph in the death overs is the ultimate batting test. Can the batter consistently find the gaps against Bumrah, Rabada, or Starc at full tilt? For pace bowlers, this measures yorker accuracy, bouncer effectiveness, and variation execution. The dimension captures raw speed matchup outcomes across all IPL seasons.

THE DATA BEHIND EVERY COMPARISON

Every number on this page is derived from Cricsheet's open-source ball-by-ball dataset (2008-2025) cross-referenced with Roanuz Cricket API for IPL 2026 live data. We do not use estimated or scraped data. Every delivery, every dismissal, every run scored is tracked at the individual ball level.

The DNA scores use exponential weighting — recent seasons contribute more than older ones. A player's performance in IPL 2025 is weighted roughly 3x more than their IPL 2020 data. This prevents retired-era statistics from inflating current player profiles. Players with fewer than 20 IPL matches have their DNA scores scaled down to reflect sample size uncertainty.

Importantly, all comparisons are descriptive, not prescriptive. A higher DNA score does not mean a player will perform better in the next match — it means their historical profile across these six dimensions is stronger. T20 cricket has inherent variance. The best batter in the world can get out for a duck. The worst bowler can take 5 wickets. CricMind's comparisons tell you who has the stronger probability of impact, not the guaranteed outcome.

WHICH STATS MATTER MOST · BY ROLE
TOP-ORDER BATTERS

Powerplay strike rate (most predictive), consistency index (standard deviation of scores — lower is better), boundary percentage, and conversion rate (50 to 100). Players like Kohli and Rohit excel here because their floor is high — even on bad days, they contribute 25-30 runs.

MIDDLE-ORDER / FINISHERS

Death over strike rate (the single most important metric), chase mastery score, and "impact rate" — the percentage of matches where their contribution directly influenced the result. Hardik Pandya, Rinku Singh, and MS Dhoni are elite finishers because they maintain 180+ SR in overs 16-20.

FAST BOWLERS

Death over economy (most predictive of match impact), dot ball percentage, and wickets-per-match in the powerplay. Jasprit Bumrah's death over economy of 6.8 is almost 2 runs per over better than the average IPL pacer — that translates to 8-10 fewer runs in a death spell, which changes matches.

SPINNERS

Middle-over economy (overs 7-15), boundary concession rate, and wickets per spell. Rashid Khan concedes boundaries at half the rate of an average IPL spinner. Varun Chakravarthy's mystery ball generates dot balls at 45% frequency — nearly 1 in 2 deliveries. These are the metrics that separate IPL spinners from average ones.

ALL-ROUNDERS

The "dual impact index" — batting strike rate multiplied by bowling economy inverse. A player with 150 SR batting and 7.5 economy bowling scores higher than one with 130 SR and 8.5 economy. Hardik Pandya, Ravindra Jadeja, and Mitchell Marsh lead this metric in IPL 2026.

FREQUENTLY ASKED QUESTIONS · PLAYER COMPARISON
How does CricMind compare IPL players?

CricMind compares players across multiple dimensions: IPL career statistics (matches, runs, wickets, strike rate, economy), and a proprietary 6-dimensional DNA profile that rates each player on Pressure Performance, Chase Mastery, Powerplay Dominance, Death Overs Ability, and performance against both Spin and Pace bowling. Each DNA score is calibrated using data from all IPL seasons (2008-2025).

What is the DNA Score in CricMind player comparison?

The DNA Score is a composite rating from 0 to 100 that represents a player's overall IPL value. It is calculated by weighting the 6 DNA dimensions (Pressure, Chase, Powerplay, Death, vs Spin, vs Pace) based on their impact on match outcomes. A DNA Score of 90+ indicates an elite IPL performer. The score is updated based on each season's data.

Who is better in IPL — Virat Kohli or Rohit Sharma?

Both are IPL legends with different strengths. Kohli has more IPL runs and a higher consistency metric across 18 seasons with RCB. Rohit Sharma has 5 IPL titles as captain — the most in IPL history. CricMind's DNA analysis shows Kohli edges on Pressure Performance and Spin handling, while Rohit leads in Powerplay dominance and Chase Mastery. The head-to-head comparison above shows the full statistical breakdown.

Can I compare any two IPL 2026 players?

CricMind currently features the top 50+ IPL 2026 players in its comparison database. The 10 most popular comparisons are pre-built on this page with full statistical breakdowns. We are expanding the tool to allow any two players to be compared via a search interface in Phase 2.

How does the AI DNA profile differ from traditional stats?

Traditional stats like batting average and economy rate do not capture context. A player might average 35 but score most runs in dead matches. The DNA profile measures performance under pressure (close games, must-win situations), chase mastery (target-chasing efficiency), and phase-specific impact (powerplay vs death overs). These contextual metrics are far more predictive of match impact than raw averages.

Which stats matter most for IPL player comparison?

For batters, strike rate in the death overs (16-20) is the single most predictive stat for match impact, followed by runs under pressure. For bowlers, economy rate in death overs matters more than total wickets. For all-rounders, the combination of batting strike rate and bowling economy creates a composite impact score. CricMind weights all these contextually.

Is Bumrah better than Rashid Khan in IPL?

Jasprit Bumrah and Rashid Khan are the two best bowlers in IPL history by impact. Bumrah dominates with pace, especially in death overs — his economy under 7 rpo in overs 17-20 is unmatched. Rashid Khan's leg spin is nearly unplayable in the middle overs (7-15), with an economy consistently under 6.5. The comparison depends on conditions: pace-friendly venues favour Bumrah, spin-friendly ones favour Rashid.

How are the "W" markers determined in comparisons?

The "W" marker indicates which player leads in a specific statistical category. For batting stats (runs, strike rate, matches), higher is better. For bowling economy, lower is better (indicating more economical bowling). If both players are equal in a stat, no "W" is shown. The overall AI Edge verdict uses the composite DNA Score.

ALL IPL 2026 PLAYERS
50+ player DNA profiles
MATCH PREDICTIONS
AI win probability for every match
HOW THE AI WORKS
17-factor Oracle engine explained
ARGUMENT SETTLER
Data-driven cricket debates
CricMind.ai is not affiliated with BCCI, IPL, or any cricket board. Player statistics are sourced from Cricsheet historical data (2008-2025) and Roanuz Cricket API (IPL 2026). DNA scores are AI-generated composite ratings for analytical purposes. All trademarks belong to their respective owners.