2019 Terrapin at Toronto

March 9, 2019


Toronto C

1Toronto GL2152451942010.751013013.00
2Waterloo AW39514021232019.751426018.57
3Toronto FW4809041202024.001630018.75
4Toronto EW5006031412025.001732018.82
5Toronto DW3102453812015.501119017.27
6Toronto GW42511021312021.251527018.00
7Waterloo AW4101755812020.501326020.00
8Toronto FW35010531032017.501322016.92
9Toronto EW3202511252016.001321016.15
10Toronto DW37518031022018.751324018.46
11Toronto DW35517531002017.751321016.15

Colin Veevers1020073880.703.800.800.885.6323%44544.50
Gareth Thorlakson11220123131.092.820.274.0014.3320%47543.18
Ryan Hamilton1122041740.361.550.361.005.2510%21019.09
Sky Li1122073260.642.910.551.176.5018%39535.91


Toronto D

1Toronto EW2851702952014.251119017.27
2Toronto FW3754521332018.751523015.33
3Toronto GW28519011042014.251119017.27
4Waterloo AW3708511332018.501424017.14
5Toronto CL2453104532012.25915016.67
6Toronto EW33510011222016.751321016.15
7Toronto FW35512031142017.751422015.71
8Toronto GW35015511132017.501224020.00
9Waterloo AW20512501052010.251013013.00
10Toronto CL180375161209.00711015.71
11Toronto CL175355433208.75710014.29

Josh Lane1122041240.361.090.361.004.007%16014.55
Milan Fernandez11220432100.362.910.910.403.6016%33030.00
Sam Hauer11220740100.643.640.910.704.7021%45541.36
Wentao Cui11220519120.451.731.090.422.0011%20518.64


Toronto E

1Toronto DL170285090208.509808.89
2Toronto GL115290063205.7567011.67
3Waterloo AW2402151832012.00916017.78
4Toronto CL60500020203.0024020.00
5Toronto FW2351502912011.751112010.91
6Toronto DL100335151205.006406.67
7Toronto GL155250160207.7578011.43
8Waterloo AW2801553932014.001216013.33
9Toronto CL25320023201.2522010.00
10Toronto FL180265163209.00712017.14

Eric Raju91800980.001.000.890.001.135%505.56
Jade Goh-McMillen1020041410.401.400.104.0018.009%19519.50
Qaasim Karim1020031540.301.500.400.754.509%17517.50
Zhongtian Wang1020022440.202.400.400.506.5013%25025.00


Toronto F

1Waterloo AL150220070207.5078011.43
2Toronto DL45375043202.254205.00
3Toronto CL90480032204.5037023.33
4Toronto GW2501152722012.50916017.78
5Toronto EL150235070207.5078011.43
6Waterloo AW2101451812010.50912013.33
7Toronto DL120355131206.0048020.00
8Toronto CL105350063205.2566010.00
9Toronto GL90375052204.5055010.00
10Toronto EW26518001212013.251215012.50

Luc Foster10200236100.203.601.000.203.8019%34034.00
Olive Nugent1020021400.201.400.000.000.008%17017.00
Spandan Sengupta918001250.001.330.560.002.407%9510.56


Toronto G

1Toronto CW2452151902012.251014014.00
2Toronto EW29011511152014.501219015.83
3Toronto DL190285171209.50811013.75
4Toronto FL115250065205.7568013.33
5Waterloo AW2051300912010.25912013.33
6Toronto CL110425131205.5047017.50
7Toronto EW2501554822012.501212010.00
8Toronto DL155350164207.75710014.29
9Toronto FW3759031122018.751423016.43
10Waterloo AW3656021112018.251323017.69

Jacky Li918041280.441.330.890.502.009%14015.56
Mark Wong1020043070.403.000.700.574.8617%32532.50
Raymond Chen1020063970.603.900.700.866.4323%44544.50


Waterloo A

1Toronto FW2201503612011.00912013.33
2Toronto CL140395153207.0069015.00
3Toronto EL21524001032010.751013013.00
4Toronto DL85370146204.2556012.00
5Toronto GL130205084206.508708.75
6Toronto FL145210075207.25710014.29
7Toronto CL175410160208.75710014.29
8Toronto EL155280073207.75710014.29
9Toronto DL125205051206.2558016.00
10Toronto GL60365032203.0034013.33

Dante Mazza102002970.200.900.700.291.576%858.50
Justin Song102002830.200.800.300.673.335%959.50
Kaveen Makumbura10200120110.102.001.100.091.9111%16016.00
Tim He1020012470.102.400.700.143.5713%22022.00