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Samjhana Khadka 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.

overallT205571369314.6102.913.346.0HIGH

Why we like it

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

  • Phase: middle (T20)MEDIUM sample

    195 runs off 204 balls in 13 T20 matches — strike rate 95.6 vs 102.9 overall, average 24.4 vs 14.6 overall.

  • Opposition: United Arab Emirates (T20)LOW sample

    93 runs off 72 balls in 2 T20 matches — strike rate 129.2 vs 102.9 overall, average 93.0 vs 14.6 overall.

  • Venue: Gahanga International Cricket Stadium. Rwanda (T20)LOW sample

    82 runs off 73 balls in 3 T20 matches — strike rate 112.3 vs 102.9 overall, average 27.3 vs 14.6 overall.

  • Venue: Gahanga B Ground, Rwanda (T20)LOW sample

    79 runs off 69 balls in 5 T20 matches — strike rate 114.5 vs 102.9 overall, average 19.8 vs 14.6 overall.

Risks

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

  • Opposition: Malaysia (T20)MEDIUM sample

    143 runs off 153 balls in 11 T20 matches — strike rate 93.5 vs 102.9 overall, average 15.9 vs 14.6 overall.

  • Venue: Bayuemas Oval, Kuala Lumpur (T20)MEDIUM sample

    194 runs off 209 balls in 16 T20 matches — strike rate 92.8 vs 102.9 overall, average 14.9 vs 14.6 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.

MalaysiaT201114315315.993.57.838.6MEDIUM
Hong KongT2069810019.698.09.048.0LOW
United Arab EmiratesT202937293.0129.219.438.9LOW
VanuatuT202767038.0108.618.648.6LOW
ThailandT206696911.5100.015.953.6LOW
RwandaT202544927.0110.216.344.9LOW
NetherlandsT204524813.0108.318.854.2LOW

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.

Bayuemas Oval, Kuala LumpurT201619420914.992.89.142.6MEDIUM
Tribhuvan University International Cricket Ground, KirtipurT201011611111.6104.516.250.5LOW
Entebbe Cricket OvalT206767612.7100.09.248.7LOW
Gahanga International Cricket Stadium. RwandaT203827327.3112.319.247.9LOW
Gahanga B Ground, RwandaT205796919.8114.515.942.0LOW
Rangiri Dambulla International StadiumT203835741.5145.622.836.8LOW
Terdthai Cricket Ground, BangkokT204484916.098.012.246.9LOW

By country

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

UnknownT205571369314.6102.913.346.0HIGH

By match phase

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

powerplayT205348546812.8103.614.748.9HIGH
middleT201319520424.495.68.339.7MEDIUM

Against pace and spin

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

PACET205241739012.3106.916.449.0HIGH
SPINT203226726819.199.69.741.8MEDIUM
UNKNOWNT2013293529.082.95.745.7LOW

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.