Wolves de Chicago

GP: 7 | W: 2 | L: 5 | OTL: 0 | P: 4
GF: 36 | GA: 53 | PP%: 23.53% | PK%: 53.57%
GM : Elowan Gingras Osterstock | Morale : 40 | Team Overall : 60
Next Games #105 vs Senators de Belleville
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
1Jesse PuljujarviX98.007544898180628061446059652557576440620
2Tanner FritzXX99.007569896969798462786258645544446440620
3Nicolas RoyX95.008178876878838960755461675844446640620
4Gage QuinneyXX100.007873916273707264805963686050506540610
5Peyton KrebsX99.005651737269799569717254555730309540610
6Valentin ZykovX100.007344977180557169326058522546466240590
7Samuel FagemoXX100.005147947072779564625264516740409540590
8William CarrierX100.008478997678596345503844674256575440560
9Tyrell GoulbourneX100.006370466470778453504754565144445640550
10Reid DukeXX100.007370796570525255694956615344445840550
11Ryan MurphyX97.007367888067758154254941653960615740630
12Haydn FleuryX95.007845967282607658254547677553535940620
13Dylan Coghlan (R)X100.007670896570798459254954645144446240610
14Brett LernoutX100.008180837480596346253341663955555340600
15Jake BischoffX100.007671896971738048253940623848485440590
16Zach Whitecloud (R)X100.007876846276667150254541633944445440580
Scratches
1Patrick BrownXX96.008077867277798559745262665946466540620
2Keegan KolesarXS17782666582798559505162655945456340600
TEAM AVERAGE98.83746685707570785849515362504747644060
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
1Oscar Dansk100.00606176796062596662613044446140600
Scratches
1Garret Sparks94.00626159836657556569629547476240610
TEAM AVERAGE97.0061616881636057666662634646624061
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Rocky Thompson50647168504758CAN411500,000$


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
1Gage QuinneyWolves de Chicago (VGK)C/LW7105155009729101234.48%310515.062247190000012100.00%394012.8500000200
2Jesse PuljujarviWolves de Chicago (VGK)RW7211135601171851711.11%211816.93033320000080033.33%3222002.1900000010
3Nicolas RoyWolves de Chicago (VGK)C736961351292061315.00%516423.560001190111390061.97%7185001.0900001000
4Patrick BrownWolves de Chicago (VGK)C/RW6549-31951216225922.73%614323.962137191013300061.68%167143011.2500010001
5Tanner FritzWolves de Chicago (VGK)C/RW7347-812101062491412.50%514320.471235240001171050.00%10194000.9800011000
6Valentin ZykovWolves de Chicago (VGK)LW7246100721651312.50%19113.010000000000000.00%2200001.3200000001
7Peyton KrebsWolves de Chicago (VGK)LW7156-724014156136.67%112217.53033524000000066.67%12232000.9800000000
8Keegan KolesarWolves de Chicago (VGK)RW723519945661971610.53%19613.75000000000130050.00%1474001.0400315000
9Zach WhitecloudWolves de Chicago (VGK)D7055311510127540.00%88912.730000000005000.00%002001.1200001000
10Reid DukeWolves de Chicago (VGK)C/RW7325100571321023.08%59113.0100000000000060.49%8146001.1000000000
11Ryan MurphyWolves de Chicago (VGK)D7033-51009912420.00%1418226.14000424000033000.00%019000.3300000000
12Brett LernoutWolves de Chicago (VGK)D70333181081210340.00%713719.58022420000024000.00%006000.4400002000
13Dylan CoghlanWolves de Chicago (VGK)D721342081096622.22%1015121.61213321000027000.00%0311000.4000000000
14Haydn FleuryWolves de Chicago (VGK)D7112-52081412348.33%2319027.18101324000236000.00%0114000.2100000000
15Jake BischoffWolves de Chicago (VGK)D7022200681230.00%59213.160000000001000.00%013000.4300000000
16Samuel FagemoWolves de Chicago (VGK)LW/RW7202-1002151340.00%0152.200000000000000.00%040002.6000000000
17William CarrierWolves de Chicago (VGK)LW7000220451110.00%3446.3500002000080053.33%1510000.0000000000
18Tyrell GoulbourneWolves de Chicago (VGK)LW7000000001000.00%081.160000000000000.00%100000.0000000000
Team Total or Average1253659954218801281352348014415.38%99198715.90814224222211272472260.16%37913775020.96003310212
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
1Garret SparksWolves de Chicago (VGK)72200.8156.833600041222147100.000070000
2Oscar DanskWolves de Chicago (VGK)30300.70012.205900124020000.000007000
Team Total or Average102500.7987.574200053262167100.000077000


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 StatusType Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Link
Brett LernoutWolves de Chicago (VGK)D241995-09-23No213 Lbs6 ft4NoNoNo1RFAPro & Farm653,333$0$0$NoLink
Dylan CoghlanWolves de Chicago (VGK)D211998-02-19Yes189 Lbs6 ft2NoNoNo3ELCPro & Farm716,666$0$0$NoLink
Gage QuinneyWolves de Chicago (VGK)C/LW241995-07-29No201 Lbs6 ft0NoNoNo2RFAPro & Farm715,000$0$0$NoLink
Garret SparksWolves de Chicago (VGK)G261993-06-28No210 Lbs6 ft3NoNoNo1RFAPro & Farm675,000$0$0$NoLink
Haydn FleuryWolves de Chicago (VGK)D231996-07-08No221 Lbs6 ft3NoNoNo1RFAPro & Farm863,333$0$0$NoLink
Jake BischoffWolves de Chicago (VGK)D251994-07-25No194 Lbs6 ft1NoNoNo1RFAPro & Farm833,750$0$0$NoLink
Jesse PuljujarviWolves de Chicago (VGK)RW211998-05-07No211 Lbs6 ft4NoNoNo1ELCPro & Farm925,000$0$0$NoLink
Keegan KolesarWolves de Chicago (VGK)RW221997-04-08No227 Lbs6 ft2NoNoNo2ELCPro & Farm702,500$0$0$NoLink
Nicolas RoyWolves de Chicago (VGK)C221997-02-05No208 Lbs6 ft4NoNoNo2ELCPro & Farm720,000$0$0$NoLink
Oscar DanskWolves de Chicago (VGK)G251994-02-28No195 Lbs6 ft3NoNoNo1RFAPro & Farm650,000$0$0$NoLink
Patrick BrownWolves de Chicago (VGK)C/RW271992-05-29No210 Lbs6 ft1NoNoNo1RFAPro & Farm650,000$0$0$NoLink
Peyton KrebsWolves de Chicago (VGK)LW182001-01-26 16:15:49No187 Lbs6 ft5NoNoNo1ELCPro & Farm0$0$No
Reid DukeWolves de Chicago (VGK)C/RW231996-01-28No191 Lbs6 ft0NoNoNo2RFAPro & Farm770,000$0$0$NoLink
Ryan MurphyWolves de Chicago (VGK)D261993-03-31No185 Lbs5 ft11NoNoNo1RFAPro & Farm650,000$0$0$NoLink
Samuel FagemoWolves de Chicago (VGK)LW/RW192000-03-14 16:24:05No187 Lbs6 ft5NoNoNo1ELCPro & Farm0$0$No
Tanner FritzWolves de Chicago (VGK)C/RW281991-08-20No192 Lbs5 ft11NoNoNo1UFAPro & Farm650,000$0$0$NoLink
Tyrell GoulbourneWolves de Chicago (VGK)LW251994-01-25No195 Lbs5 ft11NoNoNo1RFAPro & Farm715,000$0$0$NoLink
Valentin ZykovWolves de Chicago (VGK)LW241995-05-14No224 Lbs6 ft1NoNoNo2RFAPro & Farm675,000$0$0$NoLink
William CarrierWolves de Chicago (VGK)LW241994-12-20No212 Lbs6 ft2NoNoNo2RFAPro & Farm725,000$0$0$NoLink
Zach WhitecloudWolves de Chicago (VGK)D221996-11-27Yes209 Lbs6 ft2NoNoNo2ELCPro & Farm925,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2023.45203 Lbs6 ft21.45660,729$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Peyton KrebsTanner Fritz40122
2Gage QuinneyNicolas RoyJesse Puljujarvi30122
3Valentin ZykovReid Duke20122
4Samuel FagemoNicolas Roy10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan MurphyHaydn Fleury40122
2Dylan CoghlanBrett Lernout30122
3Jake BischoffZach Whitecloud20122
4Ryan MurphyHaydn Fleury10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Peyton KrebsTanner Fritz60122
2Gage QuinneyNicolas RoyJesse Puljujarvi40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan MurphyHaydn Fleury60122
2Dylan CoghlanBrett Lernout40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Nicolas Roy60122
2Tanner FritzJesse Puljujarvi40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan MurphyHaydn Fleury60122
2Dylan CoghlanBrett Lernout40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
160122Ryan MurphyHaydn Fleury60122
2Nicolas Roy40122Dylan CoghlanBrett Lernout40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Nicolas Roy60122
2Tanner FritzJesse Puljujarvi40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan MurphyHaydn Fleury60122
2Dylan CoghlanBrett Lernout40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Peyton KrebsTanner FritzRyan MurphyHaydn Fleury
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Peyton KrebsTanner FritzRyan MurphyHaydn Fleury
Extra Forwards
Normal PowerPlayPenalty Kill
William Carrier, Tyrell Goulbourne, William Carrier, Tyrell Goulbourne
Extra Defensemen
Normal PowerPlayPenalty Kill
Jake Bischoff, Zach Whitecloud, Dylan CoghlanJake BischoffZach Whitecloud, Dylan Coghlan
Penalty Shots
, Nicolas Roy, Tanner Fritz, Jesse Puljujarvi, Peyton Krebs
Goalie
#1 : , #2 : Oscar Dansk
Custom OT Lines Forwards
, Nicolas Roy, Tanner Fritz, Jesse Puljujarvi, Peyton Krebs, Gage Quinney, Gage Quinney, , Valentin Zykov, Samuel Fagemo, William Carrier
Custom OT Lines Defensemen
Ryan Murphy, Haydn Fleury, Dylan Coghlan, Brett Lernout, Jake Bischoff


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
1Admirals de Milwaukee10100000512-710100000512-70000000000000.00059140014139032927666050174686233.33%8625.00%09313966.91%7213453.73%7313852.90%1581011545710651
2Barracuda de San José211000001214-2110000007611010000058-320.500122234001413906992766607122534011327.27%14657.14%19313966.91%7213453.73%7313852.90%1581011545710651
3Bruins de Providence 1010000024-21010000024-20000000000000.00022400141390349276660322021207114.29%8362.50%09313966.91%7213453.73%7313852.90%1581011545710651
4Heat de Stockton11000000633110000006330000000000021.00068140014139030927666030101918300.00%7271.43%09313966.91%7213453.73%7313852.90%1581011545710651
5Reign d'Ontario10100000711-40000000000010100000711-400.0007121900141390349276660382222202150.00%6350.00%09313966.91%7213453.73%7313852.90%1581011545710651
6Roadrunners de Tucson1010000049-5000000000001010000049-500.00046100014139035927666041861225120.00%13653.85%09313966.91%7213453.73%7313852.90%1581011545710651
Total725000003653-17422000002025-5303000001628-1240.2863659950014139023492766602629922212834823.53%562653.57%19313966.91%7213453.73%7313852.90%1581011545710651
_Since Last GM Reset725000003653-17422000002025-5303000001628-1240.2863659950014139023492766602629922212834823.53%562653.57%19313966.91%7213453.73%7313852.90%1581011545710651
_Vs Conference624000003449-15321000001821-3303000001628-1240.3333457910014139020092766602307920110827725.93%482352.08%19313966.91%7213453.73%7313852.90%1581011545710651
_Vs Division523000002937-8220000001394303000001628-1240.4002948770014139016892766601806215510021523.81%401757.50%19313966.91%7213453.73%7313852.90%1581011545710651

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
74L23659952342629922212800
All Games
GPWLOTWOTL SOWSOLGFGA
72500003653
Home Games
GPWLOTWOTL SOWSOLGFGA
42200002025
Visitor Games
GPWLOTWOTL SOWSOLGFGA
30300001628
Last 10 Games
WLOTWOTL SOWSOL
250000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
34823.53%562653.57%1
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
9276660141390
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
9313966.91%7213453.73%7313852.90%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1581011545710651


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 - 2019-08-164Barracuda de San José6Wolves de Chicago7WBoxScore
3 - 2019-08-1817Wolves de Chicago5Barracuda de San José8LBoxScore
7 - 2019-08-2242Bruins de Providence 4Wolves de Chicago2LBoxScore
9 - 2019-08-2447Wolves de Chicago4Roadrunners de Tucson9LBoxScore
11 - 2019-08-2674Heat de Stockton3Wolves de Chicago6WBoxScore
12 - 2019-08-2775Wolves de Chicago7Reign d'Ontario11LBoxScore
14 - 2019-08-2990Admirals de Milwaukee12Wolves de Chicago5LBoxScore
16 - 2019-08-31105Senators de Belleville-Wolves de Chicago-
18 - 2019-09-02119Wolves de Chicago-Penguins de Wilkes-Barre/Scranton-
20 - 2019-09-04130Wolves de Chicago-Phantoms de Lehigh Valley-
21 - 2019-09-05136Wolves de Chicago-IceHogs de Rockford-
24 - 2019-09-08160Eagles du Colorado-Wolves de Chicago-
26 - 2019-09-10176Gulls de San Diego-Wolves de Chicago-
30 - 2019-09-14195Rocket de Laval-Wolves de Chicago-
32 - 2019-09-16217Moose du Manitoba-Wolves de Chicago-
35 - 2019-09-19225Wolves de Chicago-Monsters de Cleveland-
37 - 2019-09-21247Wolves de Chicago-Marlies de Toronto-
39 - 2019-09-23262Wolves de Chicago-Bears de Hershey-
40 - 2019-09-24266Wolves de Chicago-Griffins de Grand Rapids-
43 - 2019-09-27285IceHogs de Rockford-Wolves de Chicago-
46 - 2019-09-30304Wolves de Chicago-Reign d'Ontario-
47 - 2019-10-01315Heat de Stockton-Wolves de Chicago-
49 - 2019-10-03330Marlies de Toronto-Wolves de Chicago-
51 - 2019-10-05345Barracuda de San José-Wolves de Chicago-
53 - 2019-10-07359Condors de Bakersfield-Wolves de Chicago-
55 - 2019-10-09367Wolves de Chicago-Stars du Texas-
57 - 2019-10-11383Wolves de Chicago-Admirals de Milwaukee-
59 - 2019-10-13401Roadrunners de Tucson-Wolves de Chicago-
62 - 2019-10-16423Wolves de Chicago-Wolfpack de Hartford-
63 - 2019-10-17428Wolves de Chicago-Devils de Binghamton-
65 - 2019-10-19444Wolves de Chicago-Sound Tigers de Bridgeport-
68 - 2019-10-22466Wolfpack de Hartford-Wolves de Chicago-
70 - 2019-10-24482IceHogs de Rockford-Wolves de Chicago-
72 - 2019-10-26496Wolves de Chicago-Rampage de San Antonio-
73 - 2019-10-27500Wolves de Chicago-Stars du Texas-
75 - 2019-10-29517Comets d'Utica-Wolves de Chicago-
77 - 2019-10-31533Wild de l'Iowa-Wolves de Chicago-
79 - 2019-11-02546Wolves de Chicago-Comets d'Utica-
82 - 2019-11-05568Wolves de Chicago-Barracuda de San José-
83 - 2019-11-06580Eagles du Colorado-Wolves de Chicago-
87 - 2019-11-10582Wolves de Chicago-Gulls de San Diego-
88 - 2019-11-11601Roadrunners de Tucson-Wolves de Chicago-
91 - 2019-11-14624Gulls de San Diego-Wolves de Chicago-
93 - 2019-11-16637Phantoms de Lehigh Valley-Wolves de Chicago-
95 - 2019-11-18652Rampage de San Antonio-Wolves de Chicago-
98 - 2019-11-21673Penguins de Wilkes-Barre/Scranton-Wolves de Chicago-
100 - 2019-11-23688Reign d'Ontario-Wolves de Chicago-
102 - 2019-11-25701Monsters de Cleveland-Wolves de Chicago-
105 - 2019-11-28715Wolves de Chicago-Americans de Rochester-
107 - 2019-11-30735Wolves de Chicago-Senators de Belleville-
109 - 2019-12-02748Wolves de Chicago-Rocket de Laval-
112 - 2019-12-05761Wolves de Chicago-Bruins de Providence -
122 - 2019-12-15786Wolves de Chicago-Checkers de Charlotte-
123 - 2019-12-16800Wolves de Chicago-Admirals de Milwaukee-
126 - 2019-12-19822Wolves de Chicago-Crunch de Syracuse-
128 - 2019-12-21831Wolves de Chicago-Thunderbirds de Springfield-
130 - 2019-12-23852Checkers de Charlotte-Wolves de Chicago-
133 - 2019-12-26871Wolves de Chicago-Wild de l'Iowa-
135 - 2019-12-28890Rampage de San Antonio-Wolves de Chicago-
137 - 2019-12-30905Sound Tigers de Bridgeport-Wolves de Chicago-
139 - 2020-01-01919Bears de Hershey-Wolves de Chicago-
142 - 2020-01-04939Crunch de Syracuse-Wolves de Chicago-
144 - 2020-01-06958Thunderbirds de Springfield-Wolves de Chicago-
145 - 2020-01-07959Wolves de Chicago-Gulls de San Diego-
148 - 2020-01-10983Condors de Bakersfield-Wolves de Chicago-
Trade Deadline --- Trades can’t be done after this day is simulated!
150 - 2020-01-12998Americans de Rochester-Wolves de Chicago-
152 - 2020-01-141016Reign d'Ontario-Wolves de Chicago-
154 - 2020-01-161027Devils de Binghamton-Wolves de Chicago-
157 - 2020-01-191048Wolves de Chicago-Moose du Manitoba-
159 - 2020-01-211060Wolves de Chicago-Heat de Stockton-
160 - 2020-01-221067Wolves de Chicago-Condors de Bakersfield-
163 - 2020-01-251087Wolves de Chicago-Wild de l'Iowa-
166 - 2020-01-281111Wolves de Chicago-Eagles du Colorado-
168 - 2020-01-301130Stars du Texas-Wolves de Chicago-
169 - 2020-01-311133Wolves de Chicago-Roadrunners de Tucson-
172 - 2020-02-031163Griffins de Grand Rapids-Wolves de Chicago-
174 - 2020-02-051175Comets d'Utica-Wolves de Chicago-
176 - 2020-02-071190Roadrunners de Tucson-Wolves de Chicago-
180 - 2020-02-111223Wolves de Chicago-Moose du Manitoba-
182 - 2020-02-131232Wolves de Chicago-Condors de Bakersfield-
184 - 2020-02-151244Wolves de Chicago-Heat de Stockton-
186 - 2020-02-171271Wolves de Chicago-Comets d'Utica-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance00
Attendance PCT0.00%0.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
37 0 - 0.00% 0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
0$ 1,321,458$ 1,321,458$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 0$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 172 7,105$ 1,222,060$




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
1725000003653-17422000002025-5303000001628-1243659950014139023492766602629922212834823.53%562653.57%19313966.91%7213453.73%7313852.90%1581011545710651
Total Regular Season725000003653-17422000002025-5303000001628-1243659950014139023492766602629922212834823.53%562653.57%19313966.91%7213453.73%7313852.90%1581011545710651