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S Kolcharam betting stats, splits & projections

Batter

Every figure below is counted from stored ball-by-ball deliveries — no estimates, no averages copied from elsewhere. Splits with fewer balls behind them are marked LOW sample and carry less weight in the model.

Record by format

Formats are never pooled: a twenty-over record tells you nothing about fifty-over scoring, so they are modelled and shown separately.

overallT203044441519.3107.012.341.9HIGH
overallT2011814247.235.5LOW

Why we like it

Splits where S Kolcharam scores materially faster or lasts materially longer than their own baseline in the same format.

  • Venue: Roma Cricket Ground (T20)LOW sample

    86 runs off 68 balls in 4 T20 matches — strike rate 126.5 vs 107.0 overall, average 43.0 vs 19.3 overall.

  • Phase: death (T20)LOW sample

    114 runs off 86 balls in 10 T20 matches — strike rate 132.6 vs 107.0 overall, average 22.8 vs 19.3 overall.

Risks

Splits pointing the other way — the conditions and opponents where the record is worse than usual.

  • Opposition: Switzerland (T20)LOW sample

    58 runs off 60 balls in 3 T20 matches — strike rate 96.7 vs 107.0 overall, average 19.3 vs 19.3 overall.

  • Venue: Hazelaarweg, Rotterdam (T20)LOW sample

    71 runs off 77 balls in 5 T20 matches — strike rate 92.2 vs 107.0 overall, average 14.2 vs 19.3 overall.

  • Venue: SSC Karlsruhe (T20)LOW sample

    58 runs off 60 balls in 3 T20 matches — strike rate 96.7 vs 107.0 overall, average 19.3 vs 19.3 overall.

  • Phase: powerplay (T20)LOW sample

    93 runs off 109 balls in 15 T20 matches — strike rate 85.3 vs 107.0 overall, average 18.6 vs 19.3 overall.

Against each opponent

Head-to-head record by format. Small head-to-head samples move the model very little — read the sample column before leaning on a line here.

ItalyT20710510217.5102.912.746.1LOW
DenmarkT203817627.0106.610.539.5LOW
SwitzerlandT203586019.396.711.746.7LOW
Isle of ManT2015031—161.322.625.8LOW
SpainT201293029.096.713.330.0LOW

By venue

Ground-by-ground record. Venue effects are real but slow to prove, so grounds with few balls are shown for transparency rather than used as evidence.

Hazelaarweg, RotterdamT205717714.292.214.357.1LOW
Roma Cricket GroundT204866843.0126.514.729.4LOW
SSC KarlsruheT203586019.396.711.746.7LOW
GelsenTrabPark, GelsenkirchenT203464815.395.88.335.4LOW
Ishoj Cricket Club, VejledalenT203534326.5123.314.046.5LOW
Bayer Uerdingen Cricket GroundT20529389.776.35.352.6LOW
Simar Cricket Ground, RomeT201293029.096.713.330.0LOW

Bowling

Grainville, St Saviour, JerseyT20485236.517.3LOW
Integrated Polytechnic Regional CentreT20406009.0—LOW

By country

Conditions vary more by country than by ground; this is the broader pitch-and-conditions view.

UnknownT203044441519.3107.012.341.9HIGH

Bowling

UnknownT2011814247.235.5LOW

By match phase

Powerplay, middle overs and death. Phase splits drive the simulated scoring rate ball by ball.

middleT201823722018.2107.712.339.5MEDIUM
powerplayT20159310918.685.311.056.9LOW
deathT20101148622.8132.614.029.1LOW

Bowling

deathT20608038.026.7LOW
middleT20404006.0—LOW

Against pace and spin

Record against each bowling type faced, rolled up when a finer category has too few balls.

PACET202520519220.5106.813.540.6MEDIUM
SPINT202115013916.7107.911.543.9MEDIUM
UNKNOWNT2013898422.3106.010.741.7LOW

How these splits are used

The same aggregates feed the ball-by-ball simulation behind every projection: format baselines, phase scoring rates, the bowling types a batter will face and the expected attack. See the current match projections on the cricket betting hub and the model's tested record on the cricket model performance page.