Shreyas Iyer Added 188% Win Probability in IPL 2025 — More Than Any Other Batter
What Is WPA and Why It Matters More Than Strike Rate
Win Probability Added measures the actual impact of every delivery on the match outcome. On each ball, we compute win probability before and after using our logistic regression model (trained on 263,420 ball states, 1,146 matches, isotonic-calibrated to <1% gap). The delta gets attributed to the batter and bowler.
A batter who hits a six when WP is 48% and pushes it to 55% just added +7% WPA. A batter who gets bowled when WP is 50% and drops it to 38% just cost their team -12% WPA. Sum those deltas across every ball in a season, and you get a total that captures when the runs were scored — not just how many.
This is why WPA can diverge dramatically from strike rate. A batter can score 400 runs at 165 SR and still have negative WPA if those runs came in dead matches, low-leverage situations, or on deliveries where the game was already decided.
The Batting WPA Leaderboard
| # | Batter | WPA | Per Ball | SR | Runs | Balls | Clutch Hits |
|---|---|---|---|---|---|---|---|
| 1 | SS Iyer (PBKS) | +187.7% | +0.574% | 176.8 | 578 | 327 | 38 |
| 2 | SA Yadav (MI) | +148.9% | +0.349% | 167.9 | 717 | 427 | 47 |
| 3 | N Pooran (LSG) | +148.5% | +0.560% | 195.8 | 519 | 265 | 32 |
| 4 | JC Buttler (GT) | +127.7% | +0.387% | 163.0 | 538 | 330 | 49 |
| 5 | JM Sharma (MI) | +121.1% | +0.823% | 177.6 | 261 | 147 | 28 |
| 6 | Ashutosh Sharma (SRH) | +101.3% | +1.126% | 164.4 | 148 | 90 | 15 |
| 7 | Abhishek Sharma (SRH) | +84.2% | +0.374% | 195.1 | 439 | 225 | 47 |
| 8 | V Kohli (RCB) | +78.2% | +0.172% | 144.7 | 657 | 454 | 41 |
| 9 | V Suryavanshi (RR) | +70.3% | +0.581% | 208.3 | 252 | 121 | 29 |
| 10 | Shubman Gill (GT) | +65.0% | +0.157% | 156.8 | 649 | 414 | 46 |
Shreyas Iyer: The WPA King
Shreyas Iyer's +187.7% WPA across 327 balls is the highest total in IPL 2025 — 38.8 percentage points clear of second-place Suryakumar Yadav. His +0.574% per ball means that, on average, every delivery Iyer faced moved PBKS's win probability by more than half a percentage point in their favour.
The volume-rate combination is what makes this exceptional. Pooran's +0.560% per ball is comparable, but Iyer sustained it across 62 more balls. That's 10 additional overs at elite per-ball WPA. And he did it with 38 "clutch hits" — deliveries where his batting swung win probability by 3%+ in a single ball.
At 176.8 SR with 578 runs, Iyer's traditional stats are strong but not league-leading. He's 10th in runs, 15th in SR. WPA reveals what those numbers miss: Iyer scored his runs when they mattered most. His death-overs strike rate of 232.1 (reported in our earlier analysis) confirms this — he accelerated at the exact moments where WP sensitivity is highest.
The Per-Ball Efficiency Leaders
Total WPA rewards volume. WPA per ball rewards efficiency — who shifts the needle most on every delivery they face?
| Batter | WPA/Ball | Total WPA | SR | Balls |
|---|---|---|---|---|
| Ashutosh Sharma (SRH) | +1.126% | +101.3% | 164.4 | 90 |
| JM Sharma (MI) | +0.823% | +121.1% | 177.6 | 147 |
| V Suryavanshi (RR) | +0.581% | +70.3% | 208.3 | 121 |
| SS Iyer (PBKS) | +0.574% | +187.7% | 176.8 | 327 |
| N Pooran (LSG) | +0.560% | +148.5% | 195.8 | 265 |
| KK Nair (RCB) | +0.502% | +55.2% | 180.0 | 110 |
Ashutosh Sharma's +1.126% per ball is the highest rate among qualified batters. Every ball he faced swung the match by more than a full percentage point in SRH's favour. He managed this despite a middling 164.4 SR — proof that WPA captures something SR doesn't: situational timing. He batted in high-leverage moments and consistently delivered.
The Volume vs Rate Tension
WPA splits the batting world into two archetypes:
Volume accumulators — batters who face many balls and stack moderate per-ball WPA into large totals:
- Kohli: +78.2% total but just +0.172% per ball (454 balls)
- Gill: +65.0% total but +0.157% per ball (414 balls)
- Yadav: +148.9% total at +0.349% per ball (427 balls)
Leverage hitters — batters who face fewer balls but in higher-stakes moments:
- Ashutosh: +101.3% from just 90 balls (+1.126% per ball)
- JM Sharma: +121.1% from 147 balls (+0.823% per ball)
- Sameer Rizvi: +57.8% from 79 balls (+0.731% per ball)
The ideal player combines both — high rate sustained across high volume. In 2025, that player was Shreyas Iyer: 327 balls at +0.574% per ball. The only batters with higher per-ball rates faced significantly fewer deliveries.
The WPA Destroyers: Negative Impact at Scale
| Batter | WPA | SR | Balls | Per Ball |
|---|---|---|---|---|
| YBK Jaiswal (MI) | -132.8% | 162.3 | 313 | -0.424% |
| B Sai Sudharsan (GT) | -125.5% | 156.2 | 486 | -0.258% |
| SO Hetmyer (RR) | -110.2% | 144.5 | 155 | -0.711% |
| S Dube (CSK) | -99.6% | 128.7 | 268 | -0.372% |
| SB Dubey (PBKS) | -76.0% | 161.5 | 65 | -1.169% |
Jaiswal's -132.8% WPA is the most negative in IPL 2025 despite a 162.3 SR. This counterintuitive result reveals the core insight of WPA: when you score matters as much as how much you score. Jaiswal batted 313 balls — the 6th most in the tournament — but accumulated WPA at -0.424% per ball. He scored runs in situations that were already decided, and failed to convert in tight situations.
Sai Sudharsan's -125.5% from 486 balls (the most in the IPL) is the highest negative volume in the dataset. At +0.157% WPA per ball, he's not failing outright — he's contributing at the wrong times.
Hetmyer's -0.711% per ball is the worst rate among batters with 100+ balls. At 144.5 SR across 155 balls, his scoring consistently came in low-leverage situations while his dots and dismissals concentrated in high-leverage ones.
The Bowling WPA Leaderboard
For bowlers, WPA is flipped: a bowler gets positive WPA when they reduce the batting team's win probability. Dots, wickets, and economical overs in tight situations generate the most bowling WPA.
| # | Bowler | WPA | Per Ball | Econ | Wkts | Balls |
|---|---|---|---|---|---|---|
| 1 | Arshdeep Singh (PBKS) | +195.6% | +0.559% | 8.66 | 22 | 350 |
| 2 | JJ Bumrah (MI) | +160.1% | +0.564% | 6.70 | 21 | 284 |
| 3 | Mohammed Siraj (RCB) | +151.3% | +0.442% | 8.95 | 16 | 342 |
| 4 | TA Boult (RR) | +134.4% | +0.388% | 8.76 | 23 | 346 |
| 5 | JR Hazlewood (RCB) | +122.2% | +0.463% | 8.70 | 22 | 264 |
| 6 | KH Pandya (LSG) | +95.8% | +0.347% | 8.07 | 17 | 276 |
| 7 | Avesh Khan (KKR) | +89.0% | +0.313% | 10.08 | 13 | 284 |
| 8 | Kuldeep Yadav (DC) | +79.4% | +0.281% | 6.89 | 15 | 282 |
| 9 | DS Rathi (DC) | +79.0% | +0.253% | 8.10 | 14 | 312 |
| 10 | Prasidh Krishna (RR) | +62.8% | +0.177% | 8.39 | 26 | 354 |
Arshdeep Over Bumrah: The WPA Surprise
Arshdeep Singh's +195.6% bowling WPA leads the league — 35 percentage points ahead of Bumrah's +160.1%. This isn't because Arshdeep is a better bowler (his 8.66 economy is nearly 2 runs per over higher than Bumrah's 6.70). It's because Arshdeep bowled in higher-leverage situations more often.
Arshdeep bowled 350 balls — 66 more than Bumrah. And crucially, PBKS were in more close matches this season (their end-of-2025 Elo of 1522.9 kept them competitive across the schedule). Every Arshdeep wicket in a tight game moved win probability more than a Bumrah wicket in a game MI were already leading or trailing heavily.
Per ball, though, Bumrah edges it: +0.564% vs +0.559%. On a per-delivery basis, Bumrah generates slightly more WPA — but Arshdeep's volume advantage compounds to a larger total.
Avesh Khan: High WPA Despite Bad Economy
Avesh Khan's +89.0% WPA at 10.08 economy is the most counterintuitive entry on the bowling leaderboard. A bowler conceding 10 runs per over shouldn't appear in the top 10 of any positive metric.
But Avesh took 13 wickets across 284 balls, and those wickets came at moments of peak leverage. In T20, a wicket when the batting team needs 40 off 18 swings WP by 15-25% in a single delivery. Avesh's contribution was lumpy — expensive between wickets, devastating when he struck. WPA captures that lumpiness; economy does not.
Methodology
Win Probability Added per delivery:
```
WPA = WP(after delivery) - WP(before delivery)
```
For batters, positive WPA means the delivery helped their team. For bowlers, the sign is flipped — positive WPA means the delivery hurt the batting team. The win probability model is our logistic regression + isotonic calibration system (see Models page for full details).
"Clutch Hits" = deliveries where batter WPA exceeded +3%. These are the high-impact moments: sixes at the death, boundaries when the required rate is climbing, surviving key dot balls that maintain batting position.
"Big Swings" = deliveries where the absolute WPA exceeded 5% — regardless of direction. These identify players who are consistently involved in high-leverage moments.
Qualification: Minimum 50 balls faced (batting) or bowled (bowling) in IPL 2025. Data: 70 matches from Cricsheet ball-by-ball.