Ice Shard (Ice fast)

type effectiveness

bugdarkdragonelectricfairyfightingfireflyingghostgrassgroundicenormalpoisonpsychicrocksteelwater
bug1-1111-1-1-1
dark1-1111-1-1-1
dragon11111121221111
electric1-1111-1-1-1
fairy1-1111-1-1-1
fighting1-1111-1-1-1
fire-1-1-1-1-1-1-1-2-1-1-1-1-2-2
flying11211111221111
ghost1-1111-1-1-1
grass11211121121111
ground11211121211111
ice-1-1-1-1-1-2-1-1-1-1-1-1-2-2
normal1-1111-1-1-1
poison1-1111-1-1-1
psychic1-1111-1-1-1
rock1-1111-1-1-1
steel-1-1-1-1-1-2-1-2-1-1-1-1-1-2
water-1-1-1-1-1-2-1-2-1-1-1-1-2-1

3x3 stats

STAB?TurnsEP-3P-2P-1P0P1P2PPT-3PPT-2PPT-1PPT0PPT1PPT2EPT
πŸ—™ (-4)3101.11.762.814.57.211.50.3660.5860.9381.52.43.843.33
βœ“ (-4)3101.322.113.385.48.6413.80.4390.7031.121.82.884.613.33
πŸ—™ (-3)3101.252.013.215.148.2313.20.4180.671.071.712.744.393.33
βœ“ (-3)3101.512.413.866.179.8715.80.5020.8041.292.063.295.273.33
πŸ—™ (-2)3101.462.343.7569.615.40.4880.7811.2523.25.123.33
βœ“ (-2)3101.762.814.57.211.518.40.5860.9381.52.43.846.143.33
πŸ—™ (-1)3101.762.814.57.211.518.40.5860.9381.52.43.846.143.33
βœ“ (-1)3102.113.385.48.6413.822.10.7031.121.82.884.617.373.33
πŸ—™3102.23.525.62914.4230.7321.171.8834.87.683.33
βœ“3102.644.226.7510.817.327.60.8781.412.253.65.769.223.33
πŸ—™ (1)3102.754.397.0311.21828.80.9151.462.343.7569.63.33
βœ“ (1)3103.295.278.4413.521.634.61.11.762.814.57.211.53.33
πŸ—™ (2)3103.295.278.4413.521.634.61.11.762.814.57.211.53.33
βœ“ (2)3103.956.3310.116.225.941.51.322.113.385.48.6413.83.33
πŸ—™ (3)3103.846.159.8415.825.240.31.282.053.285.258.413.43.33
βœ“ (3)3104.617.3811.818.930.248.41.542.463.946.310.116.13.33
πŸ—™ (4)3104.397.0311.21828.846.11.462.343.7569.615.43.33
βœ“ (4)3105.278.4413.521.634.655.31.762.814.57.211.518.43.33

Nx1 stats

STAB?TurnsEP-3P-2P-1P0P1P2PPT-3PPT-2PPT-1PPT0PPT1PPT2EPT
πŸ—™2102.443.916.25101625.61.221.953.125812.85
βœ“2102.934.697.51219.230.71.462.343.7569.615.45

users

Seel, Dewgong, Shellder, Cloyster, Lapras, Articuno, Sneasel, Piloswine, Glalie, Mega Glalie, Snover, Weavile, Glaceon, Cryogonal, Mr. Rime, Cetoddle, Cetitan

PokΓ©mon GO: A Quantitative Approach