Chicago Wolves

GP: 82 | W: 44 | L: 33 | OTL: 5 | P: 93
GF: 468 | GA: 440 | PP%: 40.83% | PK%: 62.50%
GM : Camil Costandi | Morale : 53 | Team Overall : 59
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Player Name C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SP
1Patrick BrownXX100.008077867277798559745262665946466534610
2Chris BourqueXX100.006660796760808465506658645559596413610
3Adam Johnson (R)XX100.007164876264838862785962625944446571610
4Mitchell StephensX100.007770926570687063795964656144446581610
5C.J. SmithXXX100.006341997067588163255070684555556758610
6Wayne SimpsonX100.007669916469838961505662645944446567610
7Saku Maenalanen (R)XXX100.007844837271547956356162602547476474590
8Joel L'Esperance (R)XX100.007744897375627868535060582545456275590
9Travis MorinX100.007774856474828956705850644845456078590
10Mikhail Vorobyev (R)X100.006141957172547563565758602545456176580
11Morgan KlimchukX100.007068766968656856504760605744446079570
12Andrew Oglevie (R)X100.007565976065545455504857625444445924540
13Brent Pedersen (R)X100.007876846876515249504053625044445623530
14Calle RosenX100.007065817065757962256246644455556045620
15Doyle SomerbyX100.008383846583636749253843674152525462600
16Kevin CzuczmanX100.007576746576778450254441623946465551590
17Cavan FitzgeraldX100.007268816468677250253943624154545474580
18Ryan Lindgren (R)X100.006871616071687447254541583744445040550
19Matt Finn (R)X100.007671866071404043252843604144444923510
Scratches
1Philippe MyersX100.008545967476677862255150662545456035630
2Niklas HanssonX100.007368856568778449254043604144445520580
TEAM AVERAGE100.00746485677167755744505463444747605359
Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Goalie Name CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Michael McNiven (R)100.00555873805357586258583044445726580
2Dan Vladar (R)100.00546784805057546055553044445667580
Scratches
TEAM AVERAGE100.0055637980525756615757304444574758
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Scott Gordon72587669704765USA56160,000$


Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Player Name Team NamePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Mitchell StephensChicago Wolves (QUE)C825791148-3984012913741713324413.67%47151618.50132538421340111216153.32%14448131041.9503512795
2Adam HelewkaNordiquesLW596266128710870101683519218717.66%44137223.27171330391101236976042.98%1147739161.8601257865
3C.J. SmithChicago Wolves (QUE)C/LW/RW714064104-1055561172648312715.15%35126917.8861420121031014303231.93%9747139021.6400001433
4Adam JohnsonChicago Wolves (QUE)C/LW82375289-135115101932378815515.61%40134116.366111714961012286455.59%5905537011.3300111343
5Saku MaenalanenChicago Wolves (QUE)C/LW/RW823244761524087572167712914.81%28104112.710331140001133053.85%394721021.4600000243
6Wayne SimpsonChicago Wolves (QUE)RW73363975-1363096701984811818.18%29128017.54761314980111133141.18%854833011.1700213224
7Hudson FaschingNordiquesRW4932387010463088891976712516.24%49122825.06481211871122873146.12%2454837021.1402600325
8Joel L'EsperanceChicago Wolves (QUE)C/RW82412768319571732446012816.80%31102712.53011070000211346.13%3106320011.3200001542
9Philippe MyersChicago Wolves (QUE)D59113849-12757410811647559.48%86146224.7911718231290000105100.00%02358000.6700010011
10Patrick BrownChicago Wolves (QUE)C/RW24242448422203935112336921.43%947419.774101417430001161055.17%5222710032.0200112322
11Calle RosenChicago Wolves (QUE)D64538434612560638437385.95%76133820.91571211103011374000.00%01245000.6400023001
12Lawrence PilutNordiquesD6763137426041689433456.38%79120718.03336667000160100.00%0747000.6100000002
13Ian McCoshenNordiquesD6072835-144820978311141396.31%107139323.22671320114000086000.00%02146000.5000202110
14Morgan KlimchukChicago Wolves (QUE)LW8210142413515394412935747.75%166778.2600000000001050.00%18328000.7100102010
15Travis MorinChicago Wolves (QUE)C8210102081610414787165211.49%186267.64000000004171151.74%230209000.6400101000
16Kevin CzuczmanChicago Wolves (QUE)D59115169834558413220263.13%4373212.42000432000131000.00%0725000.4400414001
17Mikhail VorobyevChicago Wolves (QUE)C8258133101081726111219.23%42953.600222260001100044.00%50115000.8800002000
18Doyle SomerbyChicago Wolves (QUE)D77012123764053443922170.00%6287711.4000002000027000.00%0529000.2700233000
19Aaron NessNordiquesD71011113412523454022150.00%4693013.11011025000218000.00%0325000.2400131000
20Cavan FitzgeraldChicago Wolves (QUE)D8209961210193115760.00%245326.4900003000014000.00%0010000.3400110000
21Ryan LindgrenChicago Wolves (QUE)D48000-1155121010230.00%102996.250000000005000.00%018000.0000010000
22Matt FinnChicago Wolves (QUE)D6000-200110000.00%0294.830000000001000.00%000000.0000000000
Team Total or Average1443416659107524839425129413413019974166413.78%8832095614.52821182002161202461030783361347.78%46216595821221.0306292135383937
Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Dan VladarChicago Wolves (QUE)43251210.8824.562357201791513862300.50023839202
2Michael McNivenChicago Wolves (QUE)32161030.8774.7417591501391129652610.5002320012
Team Total or Average75412240.8804.63411717031826421514910.50047039214


Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Player Name Team NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Force Waivers Contract Type Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Link
Adam JohnsonChicago Wolves (QUE)C/LW241994-06-22Yes174 Lbs6 ft0NoNoNo1Pro & Farm925,000$0$0$NoLink
Andrew OglevieChicago Wolves (QUE)RW231995-02-16Yes181 Lbs5 ft10NoNoNo2Pro & Farm925,000$0$0$No925,000$Link
Brent PedersenChicago Wolves (QUE)LW221995-07-05Yes205 Lbs6 ft2YesNoNo1Pro & Farm500,000$0$0$NoLink
C.J. SmithChicago Wolves (QUE)C/LW/RW231994-12-01No185 Lbs5 ft11NoNoNo2Pro & Farm700,000$0$0$No700,000$Link
Calle RosenChicago Wolves (QUE)D241994-02-02No176 Lbs6 ft0NoNoNo1Pro & Farm925,000$0$0$NoLink
Cavan FitzgeraldChicago Wolves (QUE)D211996-08-23No186 Lbs6 ft0NoNoNo1Pro & Farm656,667$0$0$NoLink
Chris BourqueChicago Wolves (QUE)LW/RW321986-01-29No174 Lbs5 ft8YesNoNo1Pro & Farm500,000$0$0$NoLink
Dan VladarChicago Wolves (QUE)G201997-08-20Yes185 Lbs6 ft5NoNoNo1Pro & Farm728,333$0$0$NoLink
Doyle SomerbyChicago Wolves (QUE)D231994-07-04No218 Lbs6 ft6NoNoNo1Pro & Farm725,000$0$0$NoLink
Joel L'EsperanceChicago Wolves (QUE)C/RW221995-08-18Yes201 Lbs6 ft2NoNoNo2Pro & Farm722,500$0$0$No722,500$Link
Kevin CzuczmanChicago Wolves (QUE)D271991-01-09No206 Lbs6 ft2NoNoNo1Pro & Farm700,000$0$0$NoLink
Matt FinnChicago Wolves (QUE)D241994-02-03Yes199 Lbs6 ft0YesNoNo1Pro & Farm500,000$0$0$NoLink
Michael McNivenChicago Wolves (QUE)G201997-07-08Yes221 Lbs6 ft1NoNoNo1Pro & Farm682,222$0$0$NoLink
Mikhail VorobyevChicago Wolves (QUE)C211997-01-04Yes194 Lbs6 ft2NoNoNo2Pro & Farm784,167$0$0$No784,167$Link
Mitchell StephensChicago Wolves (QUE)C211997-02-05No191 Lbs6 ft0NoNoNo1Pro & Farm925,000$0$0$NoLink
Morgan KlimchukChicago Wolves (QUE)LW231995-03-01No185 Lbs6 ft0NoNoNo1Pro & Farm700,000$0$0$NoLink
Niklas HanssonChicago Wolves (QUE)D231995-01-08No181 Lbs6 ft1NoNoNo0Pro & Farm0$0$NoLink
Patrick BrownChicago Wolves (QUE)C/RW261992-05-29No210 Lbs6 ft1NoNoNo2Pro & Farm700,000$0$0$No700,000$Link
Philippe MyersChicago Wolves (QUE)D211997-01-25No196 Lbs6 ft5NoNoNo2Pro & Farm678,333$0$0$No678,333$Link
Ryan LindgrenChicago Wolves (QUE)D201998-02-10Yes198 Lbs6 ft0NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Link
Saku MaenalanenChicago Wolves (QUE)C/LW/RW241994-05-28Yes185 Lbs6 ft3NoNoNo1Pro & Farm925,000$0$0$NoLink
Travis MorinChicago Wolves (QUE)C341984-01-08No200 Lbs6 ft1YesNoNo1Pro & Farm500,000$0$0$NoLink
Wayne SimpsonChicago Wolves (QUE)RW281989-11-19No194 Lbs5 ft11YesNoNo1Pro & Farm500,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2323.74193 Lbs6 ft11.30688,140$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Mitchell Stephens40122
2Adam Johnson30122
3Saku MaenalanenJoel L'Esperance20122
4Morgan KlimchukTravis Morin10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
140122
230122
3Doyle SomerbyKevin Czuczman20122
4Cavan FitzgeraldRyan Lindgren10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Mitchell Stephens60122
2Adam Johnson40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
160122
240122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
160122
2Mitchell Stephens40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
160122
240122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
16012260122
24012240122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
160122
2Mitchell Stephens40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
160122
240122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Mitchell Stephens
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Mitchell Stephens
Extra Forwards
Normal PowerPlayPenalty Kill
Mikhail Vorobyev, Joel L'Esperance, Saku MaenalanenMikhail Vorobyev, Joel L'EsperanceSaku Maenalanen
Extra Defensemen
Normal PowerPlayPenalty Kill
Doyle Somerby, Kevin Czuczman, Cavan FitzgeraldDoyle SomerbyKevin Czuczman, Cavan Fitzgerald
Penalty Shots
, , Mitchell Stephens, ,
Goalie
#1 : Dan Vladar, #2 :


Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
OverallHomeVisitor
# VS Team GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Binghampton Senators22000000181351100000010641100000087141.000183351001112001534981011121999826791816389444.44%8362.50%0779168346.29%778166846.64%756166345.46%172299717207481504742
2Boisbriand Armada210010001385100010005411100000084441.000132033001112001534931011121999826892435328450.00%5340.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
3Brampton Battalion22000000188101100000011381100000075241.000182846001112001534821011121999826913628275480.00%4325.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
4Bridgeport Sound Tigers5320000026224220000001358312000001317-460.6002640660011120015341781011121999826209709610616425.00%13653.85%0779168346.29%778166846.64%756166345.46%172299717207481504742
5Calgary Hitman2100000114131110000009721000000156-130.75014233700111200153493101112199982669186336350.00%30100.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
6Chicoutimi Sagueneens42101000312292100100017125211000001410460.750315485001112001534173101112199982614245276012650.00%7271.43%0779168346.29%778166846.64%756166345.46%172299717207481504742
7Drummondville Voltigeurs210000011183110000009541000000123-130.750111728001112001534981011121999826571516396350.00%3166.67%0779168346.29%778166846.64%756166345.46%172299717207481504742
8Grand Rapids Griffins42100100232302110000011110210001001212050.62523345700111200153412910111219998262085221848225.00%8275.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
9Hartford Wolf Pack5320000027234220000001385312000001415-160.600274370001112001534188101112199982623263328011218.18%110100.00%4779168346.29%778166846.64%756166345.46%172299717207481504742
10Hershey Bears3210000015114110000006332110000098140.66715264100111200153411610111219998261024312477114.29%6350.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
11Lake Erie Monsters21000001181261100000011471000000178-130.75018304800111200153411610111219998267723173410550.00%110.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
12Las Vegas Wranglers21100000161421100000010551010000069-320.5001626420011120015349510111219998267930133910440.00%4325.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
13Laval Rockets31200000221931010000058-3211000001711620.33322375900111200153413310111219998261113822587685.71%6266.67%0779168346.29%778166846.64%756166345.46%172299717207481504742
14London Knights211000001617-111000000116510100000511-620.500162642001112001534601011121999826842578334250.00%4325.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
15Lowell Devils20200000511-61010000024-21010000037-400.00059140011120015347110111219998268124832100.00%4250.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
16Manitoba Moose312000001417-320200000913-41100000054120.3331420340011120015341351011121999826112522749700.00%6350.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
17Milwaukee Admirals321000002020022000000171431010000036-340.66720345400111200153412510111219998261434542436466.67%11645.45%0779168346.29%778166846.64%756166345.46%172299717207481504742
18Peoria Riverman320010002316711000000945210010001412261.00023386100111200153412510111219998261154431394375.00%13561.54%1779168346.29%778166846.64%756166345.46%172299717207481504742
19Philadelphia Phantoms523000002731-421100000880312000001923-440.40027416800111200153418510111219998261906636959333.33%13376.92%0779168346.29%778166846.64%756166345.46%172299717207481504742
20Portland Pirates3210000017152220000009631010000089-140.667173249001112001534101101112199982613243234310330.00%10280.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
21Quebec Rempart22000000963110000007521100000021141.00091827001112001534741011121999826802936275240.00%40100.00%1779168346.29%778166846.64%756166345.46%172299717207481504742
22Rimouski Oceanic422000002018232100000161151010000047-340.500202848001112001534148101112199982612235437311872.73%9455.56%0779168346.29%778166846.64%756166345.46%172299717207481504742
23Rochester Americans20200000814-61010000047-31010000047-300.00081220001112001534891011121999826763367257228.57%6350.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
24Seattle Thunderbirds30300000820-1220200000616-101010000024-200.00081321101112001534961011121999826963278697342.86%9366.67%0779168346.29%778166846.64%756166345.46%172299717207481504742
25Sherbrooke Phoenix21100000810-2110000006421010000026-420.5008152300111200153462101112199982676178266350.00%4175.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
26Texas Stars312000001014-41100000043120200000611-520.33310182800111200153411510111219998261143526468225.00%9366.67%0779168346.29%778166846.64%756166345.46%172299717207481504742
27Toronto Marlies210001008621000010034-11100000052330.75081422001112001534861011121999826431213456116.67%4250.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
Total8240330420346844028412612021002522025041142102103216238-22930.5674687691237101112001534324510111219998263218102391914132188940.83%2087862.50%6779168346.29%778166846.64%756166345.46%172299717207481504742
29Victoriaville Tigres201010001419-510100000511-61000100098120.500142640001112001534891011121999826943125294375.00%10730.00%0779168346.29%778166846.64%756166345.46%172299717207481504742
30Worcester Sharks31200000910-1211000006511010000035-220.333914230011120015349210111219998261152537628225.00%13284.62%0779168346.29%778166846.64%756166345.46%172299717207481504742
_Since Last GM Reset8240330420346844028412612021002522025041142102103216238-22930.5674687691237101112001534324510111219998263218102391914132188940.83%2087862.50%6779168346.29%778166846.64%756166345.46%172299717207481504742
_Vs Conference51242402100272261112515901000132113192691501100140148-8530.5202724387101011120015341914101112199982620006435119111254536.00%1334069.92%5779168346.29%778166846.64%756166345.46%172299717207481504742

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8293W24687691237324532181023919141310
All Games
GPWLOTWOTL SOWSOLGFGA
8240334203468440
Home Games
GPWLOTWOTL SOWSOLGFGA
4126122100252202
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4114212103216238
Last 10 Games
WLOTWOTL SOWSOL
702001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2188940.83%2087862.50%6
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
10111219998261112001534
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
779168346.29%778166846.64%756166345.46%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
172299717207481504742


Last Played Games
Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
1 - 2019-10-044Rimouski Oceanic5Chicago Wolves10WBoxScore
3 - 2019-10-0624Chicago Wolves6Chicoutimi Sagueneens1WBoxScore
5 - 2019-10-0838Hartford Wolf Pack4Chicago Wolves8WBoxScore
6 - 2019-10-0952Chicago Wolves4Texas Stars6LBoxScore
7 - 2019-10-1065Chicago Wolves7Grand Rapids Griffins6WBoxScore
8 - 2019-10-1166Chicago Wolves8Bridgeport Sound Tigers6WBoxScore
10 - 2019-10-1386Chicoutimi Sagueneens5Chicago Wolves9WBoxScore
11 - 2019-10-14101Chicago Wolves5Hartford Wolf Pack9LBoxScore
13 - 2019-10-16117Manitoba Moose6Chicago Wolves3LBoxScore
15 - 2019-10-18137Rimouski Oceanic5Chicago Wolves3LBoxScore
16 - 2019-10-19146Chicago Wolves4Philadelphia Phantoms7LBoxScore
18 - 2019-10-21165Chicago Wolves10Laval Rockets2WBoxScore
19 - 2019-10-22176Philadelphia Phantoms3Chicago Wolves4WBoxScore
22 - 2019-10-25198Chicago Wolves2Bridgeport Sound Tigers5LBoxScore
23 - 2019-10-26208Worcester Sharks2Chicago Wolves5WBoxScore
25 - 2019-10-28228Grand Rapids Griffins8Chicago Wolves5LBoxScore
28 - 2019-10-31248Chicago Wolves2Sherbrooke Phoenix6LBoxScore
29 - 2019-11-01263Brampton Battalion3Chicago Wolves11WBoxScore
31 - 2019-11-03279London Knights6Chicago Wolves11WBoxScore
32 - 2019-11-04295Chicago Wolves3Bridgeport Sound Tigers6LBoxScore
34 - 2019-11-06308Chicago Wolves2Quebec Rempart1WBoxScore
35 - 2019-11-07321Lowell Devils4Chicago Wolves2LBoxScore
37 - 2019-11-09339Rimouski Oceanic1Chicago Wolves3WBoxScore
38 - 2019-11-10353Chicago Wolves5Grand Rapids Griffins6LXBoxScore
40 - 2019-11-12368Hershey Bears3Chicago Wolves6WBoxScore
42 - 2019-11-14385Chicago Wolves6Las Vegas Wranglers9LBoxScore
43 - 2019-11-15397Chicago Wolves7Brampton Battalion5WBoxScore
44 - 2019-11-16409Toronto Marlies4Chicago Wolves3LXBoxScore
46 - 2019-11-18429Worcester Sharks3Chicago Wolves1LBoxScore
48 - 2019-11-20443Chicago Wolves2Drummondville Voltigeurs3LXXBoxScore
49 - 2019-11-21453Chicago Wolves2Seattle Thunderbirds4LBoxScore
50 - 2019-11-22469Boisbriand Armada4Chicago Wolves5WXBoxScore
52 - 2019-11-24485Chicago Wolves2Texas Stars5LBoxScore
53 - 2019-11-25500Texas Stars3Chicago Wolves4WBoxScore
55 - 2019-11-27518Chicago Wolves5Toronto Marlies2WBoxScore
56 - 2019-11-28529Lake Erie Monsters4Chicago Wolves11WBoxScore
58 - 2019-11-30548Chicoutimi Sagueneens7Chicago Wolves8WXBoxScore
60 - 2019-12-02563Chicago Wolves3Worcester Sharks5LBoxScore
61 - 2019-12-03575Chicago Wolves3Milwaukee Admirals6LBoxScore
63 - 2019-12-05590Grand Rapids Griffins3Chicago Wolves6WBoxScore
64 - 2019-12-06604Chicago Wolves8Boisbriand Armada4WBoxScore
66 - 2019-12-08620Philadelphia Phantoms5Chicago Wolves4LBoxScore
68 - 2019-12-10639Chicago Wolves8Portland Pirates9LBoxScore
69 - 2019-12-11649Bridgeport Sound Tigers3Chicago Wolves7WBoxScore
71 - 2019-12-13664Chicago Wolves5London Knights11LBoxScore
72 - 2019-12-14677Bridgeport Sound Tigers2Chicago Wolves6WBoxScore
74 - 2019-12-16697Chicago Wolves6Philadelphia Phantoms8LBoxScore
75 - 2019-12-17708Milwaukee Admirals4Chicago Wolves6WBoxScore
77 - 2019-12-19723Chicago Wolves3Hartford Wolf Pack4LBoxScore
78 - 2019-12-20740Seattle Thunderbirds8Chicago Wolves2LBoxScore
80 - 2019-12-22757Chicago Wolves9Philadelphia Phantoms8WBoxScore
81 - 2019-12-23769Seattle Thunderbirds8Chicago Wolves4LBoxScore
83 - 2019-12-25785Chicago Wolves6Hartford Wolf Pack2WBoxScore
84 - 2019-12-26800Hartford Wolf Pack4Chicago Wolves5WBoxScore
86 - 2019-12-28815Chicago Wolves3Lowell Devils7LBoxScore
87 - 2019-12-29825Chicago Wolves8Chicoutimi Sagueneens9LBoxScore
88 - 2019-12-30838Calgary Hitman7Chicago Wolves9WBoxScore
91 - 2020-01-02860Laval Rockets8Chicago Wolves5LBoxScore
92 - 2020-01-03873Chicago Wolves4Rimouski Oceanic7LBoxScore
94 - 2020-01-05887Victoriaville Tigres11Chicago Wolves5LBoxScore
96 - 2020-01-07910Rochester Americans7Chicago Wolves4LBoxScore
97 - 2020-01-08919Chicago Wolves7Laval Rockets9LBoxScore
99 - 2020-01-10939Chicago Wolves7Lake Erie Monsters8LXXBoxScore
100 - 2020-01-11949Manitoba Moose7Chicago Wolves6LBoxScore
102 - 2020-01-13968Binghampton Senators6Chicago Wolves10WBoxScore
104 - 2020-01-15991Milwaukee Admirals10Chicago Wolves11WBoxScore
105 - 2020-01-16999Chicago Wolves4Hershey Bears5LBoxScore
108 - 2020-01-191023Chicago Wolves5Hershey Bears3WBoxScore
110 - 2020-01-211034Quebec Rempart5Chicago Wolves7WBoxScore
111 - 2020-01-221053Drummondville Voltigeurs5Chicago Wolves9WBoxScore
112 - 2020-01-231059Chicago Wolves4Rochester Americans7LBoxScore
115 - 2020-01-261084Sherbrooke Phoenix4Chicago Wolves6WBoxScore
116 - 2020-01-271095Chicago Wolves8Binghampton Senators7WBoxScore
118 - 2020-01-291107Chicago Wolves9Victoriaville Tigres8WXBoxScore
120 - 2020-01-311125Peoria Riverman4Chicago Wolves9WBoxScore
123 - 2020-02-031148Las Vegas Wranglers5Chicago Wolves10WBoxScore
124 - 2020-02-041166Chicago Wolves5Calgary Hitman6LXXBoxScore
125 - 2020-02-051174Chicago Wolves5Manitoba Moose4WBoxScore
127 - 2020-02-071183Portland Pirates2Chicago Wolves3WBoxScore
128 - 2020-02-081196Chicago Wolves9Peoria Riverman8WXBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
132 - 2020-02-121216Portland Pirates4Chicago Wolves6WBoxScore
133 - 2020-02-131230Chicago Wolves5Peoria Riverman4WBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price2510
Attendance80,14240,064
Attendance PCT97.73%97.72%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
0 2932 - 97.73% 87,372$3,582,243$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
1,784,940$ 1,582,722$ 1,582,722$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 1,784,940$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 12,259$ 0$




OverallHomeVisitor
Year GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
20198240330420346844028412612021002522025041142102103216238-22934687691237101112001534324510111219998263218102391914132188940.83%2087862.50%6779168346.29%778166846.64%756166345.46%172299717207481504742
Total Regular Season8240330420346844028412612021002522025041142102103216238-22934687691237101112001534324510111219998263218102391914132188940.83%2087862.50%6779168346.29%778166846.64%756166345.46%172299717207481504742