Login

Chicago Wolves
GP: 11 | W: 3 | L: 7 | OTL: 1 | P: 7
GF: 26 | GA: 38 | PP%: 23.33% | PK%: 66.67%
GM : Francis Lachance | Morale : 99 | Team Overall : 65
Next Games #155 vs Colorado Eagles
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Game Center
Grand Rapids Griffins
5-4-2, 12pts
3
FINAL
1 Chicago Wolves
3-7-1, 7pts
Team Stats
W2StreakL3
2-3-1Home Record0-4-0
3-1-1Home Record3-3-1
5-3-2Last 10 Games3-6-1
2.82Goals Per Game2.36
2.82Goals Against Per Game3.45
23.26%Power Play Percentage23.33%
81.08%Penalty Kill Percentage66.67%
Chicago Wolves
3-7-1, 7pts
2
FINAL
4 Ontario Reign
5-4-1, 11pts
Team Stats
L3StreakW1
0-4-0Home Record4-2-1
3-3-1Home Record1-2-0
3-6-1Last 10 Games5-4-1
2.36Goals Per Game3.50
3.45Goals Against Per Game3.20
23.33%Power Play Percentage21.21%
66.67%Penalty Kill Percentage78.57%
Chicago Wolves
3-7-1, 7pts
Day 26
Colorado Eagles
7-2-2, 16pts
Team Stats
L3StreakW2
0-4-0Home Record5-1-1
3-3-1Away Record2-1-1
3-6-1Last 10 Games7-2-1
2.36Goals Per Game4.45
3.45Goals Against Per Game4.45
23.33%Power Play Percentage35.48%
66.67%Penalty Kill Percentage83.78%
Chicago Wolves
3-7-1, 7pts
Day 30
Springfield Thunderbirds
6-3-1, 13pts
Team Stats
L3StreakW1
0-4-0Home Record2-2-0
3-3-1Away Record4-1-1
3-6-1Last 10 Games6-3-1
2.36Goals Per Game3.60
3.45Goals Against Per Game3.60
23.33%Power Play Percentage26.32%
66.67%Penalty Kill Percentage79.17%
Toronto Marlies
2-4-5, 9pts
Day 33
Chicago Wolves
3-7-1, 7pts
Team Stats
OTL1StreakL3
2-2-2Home Record0-4-0
0-2-3Away Record3-3-1
2-3-5Last 10 Games3-6-1
3.00Goals Per Game2.36
4.00Goals Against Per Game2.36
21.74%Power Play Percentage23.33%
81.03%Penalty Kill Percentage66.67%
Team Leaders
Goals
Christopher Lalancette
4
Assists
Terik Parascak
8
Points
Terik Parascak
10
Plus/Minus
Nicholas Henry
0
Wins
Topias Leinonen
3
Save Percentage
Topias Leinonen
0.916

Team Stats
Goals For
26
2.36 GFG
Shots For
399
36.27 Avg
Power Play Percentage
23.3%
7 GF
Offensive Zone Start
39.2%
Goals Against
38
3.45 GAA
Shots Against
432
39.27 Avg
Penalty Kill Percentage
66.7%%
5 GA
Defensive Zone Start
39.1%
Team Info

General ManagerFrancis Lachance
CoachPaul Maurice
DivisionEastern
ConferenceConference 1
Captain
Assistant #1
Assistant #2


Arena Info

Capacity10,000
Attendance10,000
Season Tickets4,000


Roster Info

Pro Team24
Farm Team21
Contract Limit45 / 75
Prospects2


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 SPAgeContractSalary
1Juraj Slafkovsky (R)X99.008143747883707081637576727355548999690201925,000$
2Terik Parascak (R)X99.007329818573767681637774727429418299680183925,000$
3Martin Frk X100.007741768578858567526468666584735099680301750,000$
4Filip SveningssonX100.0083506587767276775167755868707046996802531,100,000$
5Nicholas HenryX100.0075387682757778725671716868626359996702511,000,000$
6Cutter Gauthier (R)XX99.007534768078727270836774707337388599660201925,000$
7Artyom ManyukanX100.006124808765757770506565606564804699650262800,000$
8Anthony SalinitriX100.006128787771677165795765626872764599630262510,000$
9Tyler SoyX100.005115888671748160865664606866714099630271510,000$
10Alex DostieX100.005216878674788161875760656358555599630271600,000$
11Christopher Lalancette X99.00418998775828358875558586367713999630301510,000$
12Reid DukeX100.005625837776737758865260626875764399620283510,000$
13Connor Carrick X100.005324908777868566566866626476903399680301750,000$
14Tristan Luneau (R)X99.006936767174727278587268676847617699660203500,000$
15Henry Thrun (R)X100.006633818777838364526353625548586399650231725,000$
16Mitchell WheatonX100.005520977883848556545453685561654099650292880,000$
17Jakub VotjaX100.007439647168606057516464666382821799630371500,000$
18Matthew CairnsX100.006933776976687148494848715052555799620262625,000$
19Yann SauveX100.004811998781807936483537714871712299620342500,001$
20Will BorgenX100.005722817975737749544641665063844999620271500,001$
Scratches
1Luke Mittelstadt (R)X88.416533757770727269507069626843525799640212500,000$
TEAM AVERAGE99.19642981817575776463616265646166529965
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 SPAgeContractSalary
1Frans Tuohimaa 100.008285817992717176766965787530996503311,000,000$
2Michael Hrabal (R)97.00807881858180808079777841398199620192650,000$
3Topias Leinonen (R)100.00777885857483837373726841407899610201650,000$
Scratches
TEAM AVERAGE99.0080808283827878767673705351639963
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Paul Maurice69898672949578CAN564250,000$


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
1Terik ParascakChicago Wolves (CAR)RW112810-42011134519394.44%1121219.29156825000000036.84%19111000.9400000001
2Cutter GauthierChicago Wolves (CAR)C/LW11369-44015202281513.64%321319.43325725000000047.10%27656000.8400000001
3Christopher Lalancette Chicago Wolves (CAR)C11448-50061933121212.12%1423521.40011420000000057.14%12654000.6800000100
4Tyler SoyChicago Wolves (CAR)C11336-50021524121512.50%619117.42000010001120055.26%15233000.6300000000
5Juraj SlafkovskyChicago Wolves (CAR)LW11426-48016135212257.69%821119.24123724000001036.36%1186000.5700000000
6Tristan LuneauChicago Wolves (CAR)D11044-540101216490%1422820.8002242700000000%049000.3500000000
7Artyom ManyukanChicago Wolves (CAR)RW11044000410289190%414012.7900000000170033.33%394000.5700000000
8Martin Frk Chicago Wolves (CAR)RW11213-4001694010255.00%819017.3000072100000000%362000.3200000010
9Alex DostieChicago Wolves (CAR)C11123-5007613357.69%101089.8900001000000056.78%11824000.5500000001
10Nicholas HenryChicago Wolves (CAR)RW1121302017102072110.00%313712.51000000000110050.00%1023000.4400000101
11Filip SveningssonChicago Wolves (CAR)LW11123-32017204012422.50%517916.3600000000081060.00%1083000.3300000001
12Anthony SalinitriChicago Wolves (CAR)C11202-6001381341015.38%511410.4100000000020037.50%864000.3500000000
13Henry ThrunChicago Wolves (CAR)D10022-200667450%617117.18000015000111000%034000.2300000000
14Jakub VotjaChicago Wolves (CAR)D11022-32012813230%1217716.1400001500006000%005000.2300000000
15Luke MittelstadtChicago Wolves (CAR)D9112020131712838.33%1318120.1310142000000000%045000.2200000000
16Connor Carrick Chicago Wolves (CAR)D11011-42091312410%1417415.8900000000010000%023000.1100000000
17Mitchell WheatonChicago Wolves (CAR)D11011-1008132040%817415.820000500005000%0010000.1100000000
18Reid DukeChicago Wolves (CAR)C11101-10030100100.00%0222.04101121000001042.86%700000.8900000000
19Matthew CairnsChicago Wolves (CAR)D11000-200531220%1877.930000400002000%00400000000000
20Yann SauveChicago Wolves (CAR)D11000-500074100%2877.990000000001000%01200000000000
21Will BorgenChicago Wolves (CAR)D11000-500131010%3383.500000500002000%00000000000000
Team Total or Average228264470-682801912253991332566.52%150328014.3971219422350003853051.41%7437982000.4300000215
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
1Topias LeinonenChicago Wolves (CAR)93510.9163.235392029345176000092210
2Michael HrabalChicago Wolves (CAR)20200.9074.071180088634010028000
Team Total or Average113710.9143.3765820374312100101110210


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 Acquired By Last Trade Date Force Waivers Waiver Possible Contract Contrat Signature Date Type Current Salary Salary RemainingSalary 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 10No Trade Year 2No Trade Year 3No Trade Year 4No Trade Year 5No Trade Year 6No Trade Year 7No Trade Year 8No Trade Year 9No Trade Year 10Link
Alex DostieChicago Wolves (CAR)C271987-10-09No187 Lbs6 ft1NoNoN/ANoNo1Pro & Farm600,000$521,466$0$0$No------------------
Anthony SalinitriChicago Wolves (CAR)C261988-08-31No186 Lbs5 ft11NoNoFree AgentNoNo22024-09-02Pro & Farm510,000$443,246$0$0$No510,000$--------No--------
Artyom ManyukanChicago Wolves (CAR)RW261988-09-04No159 Lbs5 ft7NoNoFree AgentNoNo22024-09-02Pro & Farm800,000$695,288$0$0$No800,000$--------No--------
Christopher Lalancette Chicago Wolves (CAR)C301984-10-14No197 Lbs6 ft1NoNoN/ANoNo1Pro & Farm510,000$443,246$0$0$No------------------
Connor Carrick Chicago Wolves (CAR)D301984-10-14No206 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$651,832$0$0$No------------------
Cutter GauthierChicago Wolves (CAR)C/LW201994-09-01Yes206 Lbs6 ft4NoNoN/ANoNo1Pro & Farm925,000$803,927$0$0$No------------------
Filip SveningssonChicago Wolves (CAR)LW251989-09-07No196 Lbs6 ft3NoNoFree AgentNoNo32024-09-02Pro & Farm1,100,000$956,021$0$0$No1,100,000$1,100,000$-------NoNo-------
Frans Tuohimaa Chicago Wolves (CAR)G331981-10-14No190 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,000,000$869,110$0$0$No------------------
Henry ThrunChicago Wolves (CAR)D231991-08-31Yes207 Lbs6 ft3NoNoN/ANoNo1Pro & Farm725,000$630,105$0$0$No------------------
Jakub VotjaChicago Wolves (CAR)D371977-08-31No35 Lbs1 ft7NoNoN/ANoNo1Pro & Farm500,000$434,555$0$0$No------------------
Juraj SlafkovskyChicago Wolves (CAR)LW201994-09-01Yes235 Lbs6 ft5NoNoN/ANoNo1Pro & Farm925,000$803,927$0$0$No------------------
Luke Mittelstadt (Out of Payroll)Chicago Wolves (CAR)D211993-09-09Yes175 Lbs6 ft1NoNoN/ANoNo2Pro & Farm500,000$434,555$0$0$Yes500,000$--------No--------
Martin Frk Chicago Wolves (CAR)RW301984-10-14No219 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$651,832$0$0$No------------------
Matthew CairnsChicago Wolves (CAR)D261988-08-31No210 Lbs6 ft2NoNoN/ANoNo2Pro & Farm625,000$543,194$0$0$No625,000$--------No--------
Michael HrabalChicago Wolves (CAR)G191995-09-09Yes220 Lbs6 ft9NoNoN/ANoNo2Pro & Farm650,000$564,921$0$0$No650,000$--------No--------
Mitchell WheatonChicago Wolves (CAR)D291985-10-05No237 Lbs6 ft5NoNoN/ANoNo2Pro & Farm880,000$764,817$0$0$No880,000$--------No--------
Nicholas HenryChicago Wolves (CAR)RW251989-10-04No205 Lbs5 ft11NoNoTrade2024-01-05NoNo1Pro & Farm1,000,000$869,110$0$0$No------------------
Reid DukeChicago Wolves (CAR)C281986-09-07No205 Lbs6 ft0NoNoFree AgentNoNo32024-09-02Pro & Farm510,000$443,246$0$0$No510,000$510,000$-------NoNo-------
Terik ParascakChicago Wolves (CAR)RW181996-09-03Yes179 Lbs5 ft11NoNoProspectNoNo32024-09-02Pro & Farm925,000$803,927$0$0$No925,000$925,000$-------NoNo-------
Topias LeinonenChicago Wolves (CAR)G201994-09-01Yes238 Lbs6 ft7NoNoN/ANoNo1Pro & Farm650,000$564,921$0$0$No------------------
Tristan LuneauChicago Wolves (CAR)D201994-09-03Yes192 Lbs6 ft2NoNoProspectNoNo32024-09-02Pro & Farm500,000$434,555$0$0$No500,000$500,000$-------NoNo-------
Tyler SoyChicago Wolves (CAR)C271987-10-09No186 Lbs6 ft0NoNoN/ANoNo1Pro & Farm510,000$443,246$0$0$No------------------
Will BorgenChicago Wolves (CAR)D271987-09-04No202 Lbs6 ft2NoNoN/ANoNo1Pro & Farm500,001$434,556$0$0$No------------------
Yann SauveChicago Wolves (CAR)D341980-08-06No229 Lbs6 ft2NoNoN/ANoNo2Pro & Farm500,001$434,556$0$0$No500,001$--------No--------
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2425.88196 Lbs6 ft01.63701,875$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Juraj SlafkovskyCutter GauthierTerik Parascak31014
2Filip SveningssonTyler SoyMartin Frk 28023
3Nicholas HenryChristopher Lalancette Artyom Manyukan22023
4Christopher Lalancette Alex DostieAnthony Salinitri19032
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Tristan LuneauConnor Carrick 33122
2Mitchell WheatonHenry Thrun27122
3Will BorgenJakub Votja26122
4Matthew CairnsYann Sauve14122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Juraj SlafkovskyCutter GauthierTerik Parascak53005
2Christopher Lalancette Reid DukeMartin Frk 47014
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Mitchell WheatonTristan Luneau53014
2Henry ThrunJakub Votja47113
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Tyler SoyNicholas Henry55131
2Filip SveningssonArtyom Manyukan45131
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Henry ThrunConnor Carrick 55140
2Mitchell WheatonJakub Votja45140
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Tyler Soy55140Henry ThrunConnor Carrick 54140
2Nicholas Henry45140Will BorgenMitchell Wheaton46140
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Cutter GauthierJuraj Slafkovsky55113
2Tyler SoyTerik Parascak45122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Mitchell WheatonTristan Luneau55122
2Henry ThrunJakub Votja45122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Juraj SlafkovskyCutter GauthierTerik ParascakTristan LuneauHenry Thrun
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Juraj SlafkovskyCutter GauthierTerik ParascakTristan LuneauHenry Thrun
Extra Forwards
Normal PowerPlayPenalty Kill
Tyler Soy, Cutter Gauthier, Artyom ManyukanTyler Soy, Alex DostieTyler Soy
Extra Defensemen
Normal PowerPlayPenalty Kill
Connor Carrick , Will Borgen, Matthew CairnsWill BorgenWill Borgen, Matthew Cairns
Penalty Shots
Terik Parascak, Juraj Slafkovsky, Cutter Gauthier, Filip Sveningsson, Tyler Soy
Goalie
#1 : Michael Hrabal, #2 : Topias Leinonen, #3 : Frans Tuohimaa
Custom OT Lines Forwards
Cutter Gauthier, Artyom Manyukan, Anthony Salinitri, Tyler Soy, Terik Parascak, Nicholas Henry, Nicholas Henry, Filip Sveningsson, Martin Frk , Christopher Lalancette , Alex Dostie
Custom OT Lines Defensemen
Tristan Luneau, Connor Carrick , Henry Thrun, Mitchell Wheaton, Jakub Votja


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
1Bakersfield Condors1010000036-31010000036-30000000000000.000369007514037142124132143114172150.00%2150.00%016429156.36%13629046.90%8216150.93%2351372359619095
2Bridgeport's Islanders11000000211000000000001100000021121.000235007514039142124132135126153133.33%3166.67%016429156.36%13629046.90%8216150.93%2351372359619095
3Calgary Wranglers11000000422000000000001100000042221.0004711007514042142124132142132183133.33%10100.00%016429156.36%13629046.90%8216150.93%2351372359619095
4Charlotte Checkers1010000023-1000000000001010000023-100.00024600751403814212413213613019500.00%000%016429156.36%13629046.90%8216150.93%2351372359619095
5Grand Rapids Griffins1010000013-21010000013-20000000000000.00011200751403114212413213412620100.00%3166.67%016429156.36%13629046.90%8216150.93%2351372359619095
6Henderson Silver Knights1010000035-21010000035-20000000000000.000336107514038142124132140154222150.00%2150.00%016429156.36%13629046.90%8216150.93%2351372359619095
7Ontario Reign1010000024-2000000000001010000024-200.000224007514036142124132147140132150.00%000%016429156.36%13629046.90%8216150.93%2351372359619095
8Providence Bruins1010000014-31010000014-30000000000000.000123007514031142124132130144145120.00%20100.00%016429156.36%13629046.90%8216150.93%2351372359619095
9Syracuse Crunch1000010023-1000000000001000010023-110.50024600751403514212413213415018300.00%000%016429156.36%13629046.90%8216150.93%2351372359619095
10Texas Stars1010000025-3000000000001010000025-300.000246007514031142124132153172212150.00%110.00%016429156.36%13629046.90%8216150.93%2351372359619095
11Wilkes-Barre/Scranton Penguins11000000422000000000001100000042221.000481200751404114212413213814214200.00%10100.00%016429156.36%13629046.90%8216150.93%2351372359619095
Total1137001002638-1240400000818-10733001001820-270.318264470107514039914212413214321503019130723.33%15566.67%016429156.36%13629046.90%8216150.93%2351372359619095
_Since Last GM Reset1137001002638-1240400000818-10733001001820-270.318264470107514039914212413214321503019130723.33%15566.67%016429156.36%13629046.90%8216150.93%2351372359619095
_Vs Conference1137001002638-1240400000818-10733001001820-270.318264470107514039914212413214321503019130723.33%15566.67%016429156.36%13629046.90%8216150.93%2351372359619095
_Vs Division612001001216-42010000027-541100100109130.25012223400751402151421241321207801810019210.53%9277.78%016429156.36%13629046.90%8216150.93%2351372359619095

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
117L32644703994321503019110
All Games
GPWLOTWOTL SOWSOLGFGA
113701002638
Home Games
GPWLOTWOTL SOWSOLGFGA
4040000818
Visitor Games
GPWLOTWOTL SOWSOLGFGA
73301001820
Last 10 Games
WLOTWOTL SOWSOL
360100
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
30723.33%15566.67%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
142124132175140
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
16429156.36%13629046.90%8216150.93%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
2351372359619095


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
114Providence Bruins4Chicago Wolves1BLBoxScore
424Henderson Silver Knights5Chicago Wolves3BLBoxScore
640Chicago Wolves2Charlotte Checkers3ALBoxScore
853Bakersfield Condors6Chicago Wolves3BLBoxScore
1063Chicago Wolves4Wilkes-Barre/Scranton Penguins2AWBoxScore
1277Chicago Wolves4Calgary Wranglers2AWBoxScore
1490Chicago Wolves2Syracuse Crunch3ALXBoxScore
17103Chicago Wolves2Bridgeport's Islanders1AWBoxScore
20122Chicago Wolves2Texas Stars5ALBoxScore
22132Grand Rapids Griffins3Chicago Wolves1BLBoxScore
25147Chicago Wolves2Ontario Reign4ALBoxScore
26155Chicago Wolves-Colorado Eagles-
30181Chicago Wolves-Springfield Thunderbirds-
33195Toronto Marlies-Chicago Wolves-
34203Chicago Wolves-Hartford Wolfpack-
36216Chicago Wolves-Abbotsford's Canucks-
38226Iowa Wild-Chicago Wolves-
41242Syracuse Crunch-Chicago Wolves-
43253Belleville Senators-Chicago Wolves-
45268Chicago Wolves-Lehigh Valley Phantoms-
47281Laval Rocket-Chicago Wolves-
51305Springfield Thunderbirds-Chicago Wolves-
53314Chicago Wolves-Rockford IceHogs-
56330Utica Comets-Chicago Wolves-
58341Chicago Wolves-San Jose Barracuda-
60354Ontario Reign-Chicago Wolves-
63371San Diego Gulls -Chicago Wolves-
65384Hershey Bears-Chicago Wolves-
68399Chicago Wolves-Henderson Silver Knights-
70409Chicago Wolves-Iowa Wild-
71416Chicago Wolves-Utica Comets-
75439Bridgeport's Islanders-Chicago Wolves-
77451Calgary Wranglers-Chicago Wolves-
79464Chicago Wolves-Hershey Bears-
80472Chicago Wolves-Rochester Americans-
84495Colorado Eagles-Chicago Wolves-
86506Texas Stars-Chicago Wolves-
88517San Jose Barracuda-Chicago Wolves-
91533Charlotte Checkers-Chicago Wolves-
93547Chicago Wolves-Belleville Senators-
95558Hartford Wolfpack-Chicago Wolves-
97567Chicago Wolves-Laval Rocket-
99581Chicago Wolves-Grand Rapids Griffins-
102596Chicago Wolves-Providence Bruins-
104606Chicago Wolves-Bakersfield Condors-
107627Abbotsford's Canucks-Chicago Wolves-
109638Lehigh Valley Phantoms-Chicago Wolves-
110647Chicago Wolves-Manitoba Moose-
112656Chicago Wolves-San Diego Gulls -
115674Rockford IceHogs-Chicago Wolves-
117685Wilkes-Barre/Scranton Penguins-Chicago Wolves-
120703Rochester Americans-Chicago Wolves-
123720Chicago Wolves-Toronto Marlies-
127738Manitoba Moose-Chicago Wolves-
131759San Jose Barracuda-Chicago Wolves-
132770Lehigh Valley Phantoms-Chicago Wolves-
135788Wilkes-Barre/Scranton Penguins-Chicago Wolves-
138809Chicago Wolves-Syracuse Crunch-
141827Chicago Wolves-Grand Rapids Griffins-
144842Chicago Wolves-Ontario Reign-
147862Chicago Wolves-Laval Rocket-
149877Charlotte Checkers-Chicago Wolves-
150882Chicago Wolves-Hershey Bears-
Trade Deadline --- Trades can’t be done after this day is simulated!
153896Utica Comets-Chicago Wolves-
154908San Diego Gulls -Chicago Wolves-
157930Bakersfield Condors-Chicago Wolves-
159941Chicago Wolves-Calgary Wranglers-
161952Iowa Wild-Chicago Wolves-
163969Chicago Wolves-Abbotsford's Canucks-
165977Chicago Wolves-Toronto Marlies-
166985Chicago Wolves-Bridgeport's Islanders-
168998Chicago Wolves-Springfield Thunderbirds-
1711017Rochester Americans-Chicago Wolves-
1731032Rockford IceHogs-Chicago Wolves-
1751045Chicago Wolves-Henderson Silver Knights-
1761048Colorado Eagles-Chicago Wolves-
1781066Chicago Wolves-Hartford Wolfpack-
1811087Providence Bruins-Chicago Wolves-
1841103Chicago Wolves-Texas Stars-
1861114Belleville Senators-Chicago Wolves-
1881128Chicago Wolves-Manitoba Moose-
1901135Laval Rocket-Chicago Wolves-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity50005000
Ticket Price3515
Attendance20,00020,000
Attendance PCT100.00%100.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
37 10000 - 100.00% 372,500$1,490,000$10000110

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
471,604$ 3,269,000$ 3,269,000$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 438,879$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
13,782,500$ 166 18,424$ 3,058,384$




Chicago Wolves Players Stat Leaders (Regular Season)

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Chicago Wolves Goalies Stat Leaders (Regular Season)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Chicago Wolves Career Team Stats

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

Chicago Wolves Players Stat Leaders (Play-Off)

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Chicago Wolves Goalies Stat Leaders (Play-Off)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA