Login

Wolves
GP: 80 | W: 49 | L: 21 | OTL: 10 | P: 108
GF: 356 | GA: 293 | PP%: 22.05% | PK%: 79.93%
GM : Eric Lamonde | Morale : 62 | Team Overall : 63
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Game Center
Bears
38-35-7, 83pts
2
FINAL
3 Wolves
49-21-10, 108pts
Team Stats
L1StreakL1
21-16-3Home Record27-9-4
17-19-4Away Record22-12-6
4-4-2Last 10 Games6-2-2
4.31Goals Per Game4.45
4.24Goals Against Per Game3.66
20.06%Power Play Percentage22.05%
75.69%Penalty Kill Percentage79.93%
Wolves
49-21-10, 108pts
5
FINAL
6 Marlies
43-28-9, 95pts
Team Stats
L1StreakW1
27-9-4Home Record20-16-4
22-12-6Away Record23-12-5
6-2-2Last 10 Games4-5-1
4.45Goals Per Game4.19
3.66Goals Against Per Game3.95
22.05%Power Play Percentage22.30%
79.93%Penalty Kill Percentage79.21%
Team Leaders
Goals
Alexandre Grenier
57
Assists
Kyle Rau
83
Points
Alexandre Grenier
130
Plus/Minus
Lawson Crouse
34
Wins
Laurent Brossoit
36
Save Percentage
Laurent Brossoit
0.897

Team Stats
Goals For
356
4.45 GFG
Shots For
2744
34.30 Avg
Power Play Percentage
22.0%
71 GF
Offensive Zone Start
37.0%
Goals Against
293
3.66 GAA
Shots Against
2644
33.05 Avg
Penalty Kill Percentage
79.9%
59 GA
Defensive Zone Start
36.1%
Team Info

General ManagerEric Lamonde
CoachRon Wilson
DivisionMax-Sillig
ConferenceLouis-Magnus
Captain
Assistant #1
Assistant #2


Arena Info

Capacity3,000
Attendance2,808
Season Tickets300


Roster Info

Pro Team29
Farm Team20
Contract Limit49 / 250
Prospects0


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
1Alexandre Grenier (R)X100.007133757382827673727670737072634080720251995,000$
2Kyle Rau (R)X100.006821847167837574767571716760564080710241800,000$
3Sebastian Aho (R)X100.005633818060746078706973588948437369680191500,000$
4Lawson Crouse (R)X100.008144716974578374556873675250427680670191500,000$
5Thomas Spelling (R)X100.006131767767686978576268547049463680650232500,000$
6Victor Olofsson (R)X100.005528797272736873655974577145436580650202600,000$
7Antti Suomela (R)X100.007339677280637563636866536547476180640221500,000$
8Jake Evans (R)X100.006641727262646871727065536043435942640202500,000$
9Eric Robinson (R)X100.005430737063666664595874446547475561610211500,000$
10Matthew Highmore (R)X100.006821785666666866706965436543435875610201500,000$
11Liam O'Brien (R)X100.007656716779518552635953415447504770580222500,000$
12Fredrik Olofsson (R)X100.006842555865507364566655495142435380570201600,000$
13Wade Allison (R)X100.005229736159576463565569415843425880570192500,000$
14Kevin Stenlund (R)X100.006131575370546060576155484944425163550201500,000$
15Kieffer Bellows (R)X100.005624764471626255585768346340407262550182500,000$
16Zachary Senyshyn (R)X100.004333716748545657595751476941416263540191500,000$
17Jeffrey FossX100.007332757472667173647164716272662577700281800,000$
18Joe Morrow (R)X100.006725747966687578477965715563554171700241600,000$
19Anton Lindholm (R)X100.006930826566647068476655865249465380690211650,000$
20Jeff PetryX100.007243777472657063516759686563602468680292900,000$
21Jakub Zboril (R)X100.006641776967646665426860685243427045650191500,000$
22Jalen Chatfield (R)X100.007951646185735151306450654144447180650202500,000$
23Samuel Girard (R)X100.004927767456506073338254604640407663610182500,000$
24Kale Clague (R)X100.004633766756435274277245663640408243590182500,000$
25Dylan Coghlan (R)X100.005029815156586449336044643940407955560182500,000$
Scratches
1Joona Koppanen (R)X100.005731494961396347425646445040406620480182500,000$
TEAM AVERAGE100.00633473666762676655666158584846576763
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
1Laurent Brossoit100.00827273797871728373738757544577740231950,000$
2Ebbe Siönäs100.00487256615660667376685846445079630211500,000$
Scratches
1Sergei Kostenko100.00726059617159625756607350492919610241500,000$
TEAM AVERAGE100.0067686367686367716867735149415866
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Ron Wilson83816466557149USA571500,000$


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
1Alexandre GrenierWolves (Veg)RW8057731303360014011534712522516.43%31176322.0515264159270202717610256.72%4767943011.476150009142
2Kyle RauWolves (Veg)C804183124321801231712478817616.60%48174421.811325383526214572503454.09%20435546111.42215000767
3Sebastian AhoWolves (Veg)C78485199101401041423227518014.91%38144618.5461016262140333996349.86%14307228131.37210000873
4Lawson CrouseWolves (Veg)LW80394483349151441052146912818.22%57169821.241210223726421351144239.04%1463938030.9825001635
5Joe MorrowWolves (Veg)D781063732946011217521080944.76%116205326.32613193729003316237020.00%07167000.7100000314
6Thomas SpellingWolves (Veg)RW803134652126074702286614213.60%34104713.090334652023263151.02%495318001.2402000341
7Victor OlofssonWolves (Veg)RW80333063-122089902286115514.47%26116814.61581327159000023444.23%524920001.0824000224
8Jeffrey FossWolves (Veg)D77444483152014516914874902.70%128204126.524711292830117236000.00%03461000.4701000113
9Antti SuomelaWolves (Veg)C80221638133009448147458714.97%2585310.67000020000453345.90%3902618000.8901000133
10Anton LindholmWolves (Veg)D80529346140751308628455.81%113161220.1622482050111182100.00%01146000.4201000012
11Eric RobinsonWolves (Veg)LW72171633-3320945793216318.28%22120216.71639141960004812034.04%472013000.5500000121
12Jeff PetryWolves (Veg)D7641923730081897028455.71%94147019.3412351841012159110.00%02539000.3100000101
13Fredrik OlofssonWolves (Veg)LW80111021277201003451153221.57%1896512.071121250000223042.42%33513000.4400000111
14Jake EvansWolves (Veg)C5910818-1060444010237659.80%114617.8201128000010246.08%204168000.7800000003
15Matthew HighmoreWolves (Veg)C769615440272052132817.31%62993.9500005000032050.81%12464001.0000000111
16Wade AllisonWolves (Veg)RW805813-610016167827476.41%125927.4000001000000050.00%18174000.4400000000
17Samuel GirardWolves (Veg)D72010105401048281760.00%346368.8400003000039000.00%0213000.3100000000
18Jakub ZborilWolves (Veg)D59099-24015422413140.00%345449.23000124000027000.00%0613000.3300000000
19Jalen ChatfieldWolves (Veg)D8015615501063603321153.03%5586510.8200006000010000.00%0331000.1400011000
20Kale ClagueWolves (Veg)D7006678082313350.00%224866.9600031600009000.00%0014000.2500000000
21Kieffer BellowsWolves (Veg)LW80325-11804617266911.54%86488.1100001000020144.44%935000.1500000000
22Dylan CoghlanWolves (Veg)D64044132041510540.00%212964.640000000005000.00%017000.2700000000
23Liam O'BrienWolves (Veg)C71112-22011333133.33%2801.1400009000061041.67%2400000.4900000001
24Zachary SenyshynWolves (Veg)RW67011000120010.00%0410.62000020000300058.82%1700000.4800000000
25Kevin StenlundWolves (Veg)C67000000521200.00%0590.89000020001340069.57%2300000.0000000000
Team Total or Average186635157292325260515162516832761922165712.71%9552408312.9171111182288250981321561808422551.29%5085593549280.771454012444642
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
1Laurent BrossoitWolves (Veg)60361180.8973.373468021951889974520.684385818552
2Ebbe SiönäsWolves (Veg)2413920.8863.6513800084734399100.571142155000
3Sergei KostenkoWolves (Veg)10100.7899.60250041911000.000017000
Team Total or Average854921100.8933.4848740228326421384620.654528080552


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 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 10Link
Alexandre GrenierWolves (Veg)RW251991-01-01Yes200 Lbs6 ft5NoNoNo1Pro & Farm995,000$0$0$No
Anton LindholmWolves (Veg)D211995-01-01Yes191 Lbs5 ft11NoNoNo1Pro & Farm650,000$0$0$No
Antti SuomelaWolves (Veg)C221994-01-01Yes180 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Dylan CoghlanWolves (Veg)D181998-01-01Yes190 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Ebbe SiönäsWolves (Veg)G211995-01-01No185 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Eric RobinsonWolves (Veg)LW211995-01-01Yes197 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$No
Fredrik OlofssonWolves (Veg)LW201996-01-01Yes204 Lbs6 ft2NoNoNo1Pro & Farm600,000$0$0$No
Jake EvansWolves (Veg)C201996-01-01Yes188 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Jakub ZborilWolves (Veg)D191997-01-01Yes200 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Jalen ChatfieldWolves (Veg)D201996-01-01Yes187 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Jeff PetryWolves (Veg)D291987-01-01No196 Lbs6 ft3NoNoNo2Pro & Farm900,000$0$0$No900,000$
Jeffrey FossWolves (Veg)D281988-01-01No205 Lbs6 ft2NoNoNo1Pro & Farm800,000$0$0$No
Joe MorrowWolves (Veg)D241992-01-01Yes199 Lbs6 ft0NoNoNo1Pro & Farm600,000$0$0$No
Joona KoppanenWolves (Veg)C181998-01-01Yes205 Lbs6 ft5NoNoNo2Pro & Farm500,000$0$0$No500,000$
Kale ClagueWolves (Veg)D181998-01-01Yes176 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Kevin StenlundWolves (Veg)C201996-01-01Yes209 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$No
Kieffer BellowsWolves (Veg)LW181998-01-01Yes194 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Kyle RauWolves (Veg)C241992-01-01Yes178 Lbs5 ft8NoNoNo1Pro & Farm800,000$0$0$No
Laurent BrossoitWolves (Veg)G231993-01-01No202 Lbs6 ft3NoNoNo1Pro & Farm950,000$0$0$No
Lawson CrouseWolves (Veg)LW191997-01-01Yes220 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$No
Liam O'BrienWolves (Veg)C221994-01-01Yes214 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Matthew HighmoreWolves (Veg)C201996-01-01Yes188 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Samuel GirardWolves (Veg)D181998-01-01Yes170 Lbs5 ft10NoNoNo2Pro & Farm500,000$0$0$No500,000$
Sebastian AhoWolves (Veg)C191997-01-01Yes176 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Sergei KostenkoWolves (Veg)G241992-01-01No187 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Thomas SpellingWolves (Veg)RW231993-01-01Yes176 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Victor OlofssonWolves (Veg)RW201996-01-01Yes181 Lbs5 ft11NoNoNo2Pro & Farm600,000$0$0$No650,000$
Wade AllisonWolves (Veg)RW191997-01-01Yes205 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Zachary SenyshynWolves (Veg)RW191997-01-01Yes192 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$No
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2921.10193 Lbs6 ft11.41582,586$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Lawson CrouseKyle RauAlexandre Grenier40122
2Eric RobinsonSebastian AhoThomas Spelling30122
3Fredrik OlofssonAntti SuomelaVictor Olofsson20122
4Kieffer BellowsJake EvansWade Allison10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jeffrey FossJoe Morrow40122
2Anton LindholmJeff Petry30122
3Jakub ZborilJalen Chatfield20122
4Samuel GirardKale Clague10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Lawson CrouseKyle RauAlexandre Grenier60122
2Eric RobinsonSebastian AhoThomas Spelling40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Jeffrey FossJoe Morrow60122
2Anton LindholmJeff Petry40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Kyle RauLawson Crouse60122
2Sebastian AhoEric Robinson40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Jeffrey FossJoe Morrow60122
2Anton LindholmJeff Petry40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Kyle Rau60122Jeffrey FossJoe Morrow60122
2Sebastian Aho40122Anton LindholmJeff Petry40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Kyle RauLawson Crouse60122
2Sebastian AhoEric Robinson40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jeffrey FossJoe Morrow60122
2Anton LindholmJeff Petry40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Lawson CrouseKyle RauAlexandre GrenierJeffrey FossJoe Morrow
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Lawson CrouseKyle RauAlexandre GrenierJeffrey FossJoe Morrow
Extra Forwards
Normal PowerPlayPenalty Kill
Thomas Spelling, Victor Olofsson, Antti SuomelaThomas Spelling, Victor OlofssonThomas Spelling
Extra Defensemen
Normal PowerPlayPenalty Kill
Samuel Girard, Kale Clague, Dylan CoghlanSamuel GirardSamuel Girard, Kale Clague
Penalty Shots
Alexandre Grenier, Kyle Rau, Sebastian Aho, Lawson Crouse, Thomas Spelling
Goalie
#1 : Laurent Brossoit, #2 : Ebbe Siönäs


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
1Admirals211000009721010000024-21100000073420.5009142300108120118176192295484572771716326116.67%8187.50%0931187849.57%953183052.08%717136452.57%172496216957531458732
2Barracuda311000011113-21100000043120100001710-330.500111728001081201181711292295484572974524589333.33%13376.92%0931187849.57%953183052.08%717136452.57%172496216957531458732
3Bears9520000245351043100000191455210000226215120.66745761211010812011817325922954845723049572189551120.00%361169.44%3931187849.57%953183052.08%717136452.57%172496216957531458732
4Comets311010001174211000008531000100032140.6671116270110812011817979229548457210539204811218.18%11281.82%0931187849.57%953183052.08%717136452.57%172496216957531458732
5Condors403001001018-82010010069-32020000049-510.12510162600108120118171579229548457213543187817423.53%9277.78%0931187849.57%953183052.08%717136452.57%172496216957531458732
6Crunch3300000014772200000011651100000031261.0001423370010812011817112922954845727628226711327.27%11372.73%0931187849.57%953183052.08%717136452.57%172496216957531458732
7Devils641000013525103210000016142320000011911890.750355893001081201181720592295484572210666312122731.82%301066.67%0931187849.57%953183052.08%717136452.57%172496216957531458732
8Eagles3010200010100200020008621010000024-240.667101626001081201181794922954845726927165915213.33%9277.78%0931187849.57%953183052.08%717136452.57%172496216957531458732
9Griffins20100010911-2100000107611010000025-320.5009142300108120118176192295484572752416389555.56%9366.67%0931187849.57%953183052.08%717136452.57%172496216957531458732
10Heat20100001710-31000000123-11010000057-210.250712190010812011817739229548457283241250300.00%6266.67%1931187849.57%953183052.08%717136452.57%172496216957531458732
11Icehogs220000001046110000004131100000063341.00010182800108120118176092295484572682814448225.00%7185.71%0931187849.57%953183052.08%717136452.57%172496216957531458732
12Little Stars320000101912711000000624210000101310361.0001930490010812011817111922954845721223725666233.33%10190.00%1931187849.57%953183052.08%717136452.57%172496216957531458732
13Marlies301000111314-11000001043120100001911-230.50013203300108120118171119229548457210038126313538.46%6183.33%0931187849.57%953183052.08%717136452.57%172496216957531458732
14Monsters20100001510-51000000123-11010000037-410.250571200108120118177792295484572682810461119.09%5180.00%0931187849.57%953183052.08%717136452.57%172496216957531458732
15Moose311000101617-120100010911-21100000076140.6671623390010812011817959229548457210131284811436.36%14285.71%0931187849.57%953183052.08%717136452.57%172496216957531458732
16Penguins31200000131121010000034-121100000107320.33313233600108120118171049229548457210739215313215.38%80100.00%0931187849.57%953183052.08%717136452.57%172496216957531458732
17Phantoms22000000963110000005321100000043141.000914230010812011817689229548457274441846400.00%9188.89%1931187849.57%953183052.08%717136452.57%172496216957531458732
18Punishers302000101115-42010001078-11010000047-320.33311142500108120118171169229548457210047166315213.33%8187.50%0931187849.57%953183052.08%717136452.57%172496216957531458732
19Rampage42000110191452100010098121000010106470.8751931500010812011817136922954845721294432771815.56%15380.00%1931187849.57%953183052.08%717136452.57%172496216957531458732
20Reign220000001174110000005321100000064241.0001118290010812011817699229548457273258467114.29%4175.00%0931187849.57%953183052.08%717136452.57%172496216957531458732
21Rocket21100000853110000007251010000013-220.5008101800108120118176592295484572582824439222.22%12283.33%0931187849.57%953183052.08%717136452.57%172496216957531458732
22Senators21000010963100000104311100000053241.000912210010812011817679229548457264161640100.00%8362.50%0931187849.57%953183052.08%717136452.57%172496216957531458732
23Sound Tigers6410000126188321000001410432000001128490.750264470101081201181717792295484572181695012827518.52%25292.00%1931187849.57%953183052.08%717136452.57%172496216957531458732
24Thunderbirds3300000016971100000064222000000105561.0001628440010812011817112922954845728634266012541.67%13192.31%0931187849.57%953183052.08%717136452.57%172496216957531458732
25Wolfpack330000001028220000007161100000031261.00010152501108120118177992295484572822816499111.11%80100.00%0931187849.57%953183052.08%717136452.57%172496216957531458732
Total803921032783562936340209022521751363940191201026181157241080.6753565699252210812011817274492295484572264494459516123227122.05%2945979.93%8931187849.57%953183052.08%717136452.57%172496216957531458732
_Since Last GM Reset803921032783562936340209022521751363940191201026181157241080.6753565699252210812011817274492295484572264494459516123227122.05%2945979.93%8931187849.57%953183052.08%717136452.57%172496216957531458732
_Vs Conference49281003134229165642515602110114823224134010241158332730.745229374603221081201181716689229548457215715533799802144320.09%1843680.43%6931187849.57%953183052.08%717136452.57%172496216957531458732
_Vs Division21134000041067828107300000493811116100004574017300.7141061782842010812011817707922954845726952301854381042322.12%912374.73%4931187849.57%953183052.08%717136452.57%172496216957531458732

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
80108L135656992527442644944595161222
All Games
GPWLOTWOTL SOWSOLGFGA
8039213278356293
Home Games
GPWLOTWOTL SOWSOLGFGA
402092252175136
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4019121026181157
Last 10 Games
WLOTWOTL SOWSOL
521002
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
3227122.05%2945979.93%8
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
9229548457210812011817
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
931187849.57%953183052.08%717136452.57%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
172496216957531458732


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 - 2021-11-306Wolves1Bears2ALBoxScore
5 - 2021-12-0421Bears4Wolves7BWBoxScore
8 - 2021-12-0733Wolves4Sound Tigers1AWR1BoxScore
9 - 2021-12-0840Wolves4Bears5ALXXBoxScore
10 - 2021-12-0950Sound Tigers3Wolves6BWR1BoxScore
14 - 2021-12-1366Devils7Wolves3BLBoxScore
18 - 2021-12-1786Bears5Wolves3BLBoxScore
21 - 2021-12-20103Wolves4Bears5ALXXBoxScore
22 - 2021-12-21106Wolves8Devils2AWBoxScore
26 - 2021-12-25126Eagles3Wolves4BWXBoxScore
29 - 2021-12-28142Sound Tigers1Wolves4BWR1BoxScore
32 - 2021-12-31159Bears3Wolves6BWBoxScore
35 - 2022-01-03175Wolves6Devils3AWBoxScore
37 - 2022-01-05188Punishers2Wolves3BWXXBoxScore
39 - 2022-01-07199Wolves7Little Stars5AWBoxScore
41 - 2022-01-09216Devils2Wolves5BWBoxScore
44 - 2022-01-12230Wolves8Penguins3AWBoxScore
46 - 2022-01-14241Crunch2Wolves5BWBoxScore
49 - 2022-01-17258Wolves4Rampage3AWXXBoxScore
50 - 2022-01-18266Reign3Wolves5BWBoxScore
54 - 2022-01-22285Wolves5Heat7ALBoxScore
56 - 2022-01-24294Little Stars2Wolves6BWBoxScore
58 - 2022-01-26308Wolves4Phantoms3AWBoxScore
60 - 2022-01-28317Wolves5Devils6ALXXBoxScore
61 - 2022-01-29324Thunderbirds4Wolves6BWBoxScore
64 - 2022-02-01340Wolves3Comets2AWXBoxScore
66 - 2022-02-03346Wolves4Punishers7ALBoxScore
67 - 2022-02-04355Phantoms3Wolves5BWBoxScore
70 - 2022-02-07372Wolves7Admirals3AWBoxScore
72 - 2022-02-09381Icehogs1Wolves4BWBoxScore
75 - 2022-02-12400Heat3Wolves2BLXXBoxScore
77 - 2022-02-14409Wolves3Monsters7ALBoxScore
79 - 2022-02-16419Wolves1Rocket3ALBoxScore
81 - 2022-02-18429Senators3Wolves4BWXXBoxScore
84 - 2022-02-21441Wolves7Moose6AWBoxScore
87 - 2022-02-24457Moose5Wolves6BWXXBoxScore
89 - 2022-02-26467Wolves2Penguins4ALBoxScore
91 - 2022-02-28480Wolfpack1Wolves3BWBoxScore
95 - 2022-03-04502Wolfpack0Wolves4BWBoxScore
97 - 2022-03-06510Wolves7Bears5AWBoxScore
101 - 2022-03-10529Marlies3Wolves4BWXXBoxScore
103 - 2022-03-12535Wolves6Icehogs3AWBoxScore
105 - 2022-03-14548Wolves2Eagles4ALBoxScore
107 - 2022-03-16558Rampage2Wolves4BWBoxScore
109 - 2022-03-18567Wolves5Senators3AWBoxScore
112 - 2022-03-21584Penguins4Wolves3BLBoxScore
116 - 2022-03-25597Wolves6Little Stars5AWXXBoxScore
118 - 2022-03-27610Moose6Wolves3BLBoxScore
121 - 2022-03-30627Wolves2Condors4ALBoxScore
123 - 2022-04-01638Wolves10Bears4AWBoxScore
124 - 2022-04-02641Comets0Wolves5BWBoxScore
127 - 2022-04-05661Rampage6Wolves5BLXBoxScore
131 - 2022-04-09681Wolves2Condors5ALBoxScore
132 - 2022-04-10690Comets5Wolves3BLBoxScore
136 - 2022-04-14714Griffins6Wolves7BWXXBoxScore
139 - 2022-04-17730Wolves6Barracuda7ALXXBoxScore
140 - 2022-04-18738Sound Tigers6Wolves4BLR1BoxScore
143 - 2022-04-21750Wolves3Sound Tigers4ALXXBoxScore
145 - 2022-04-23762Wolves4Thunderbirds2AWBoxScore
146 - 2022-04-24770Admirals4Wolves2BLBoxScore
149 - 2022-04-27786Wolves3Crunch1AWBoxScore
151 - 2022-04-29795Crunch4Wolves6BWBoxScore
153 - 2022-05-01805Wolves3Wolfpack1AWBoxScore
154 - 2022-05-02815Wolves2Griffins5ALBoxScore
156 - 2022-05-04826Barracuda3Wolves4BWBoxScore
159 - 2022-05-07840Wolves6Thunderbirds3AWBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
161 - 2022-05-09853Condors5Wolves4BLXBoxScore
165 - 2022-05-13873Rocket2Wolves7BWBoxScore
167 - 2022-05-15885Wolves1Barracuda3ALBoxScore
170 - 2022-05-18899Condors4Wolves2BLBoxScore
175 - 2022-05-23920Eagles3Wolves4BWXBoxScore
177 - 2022-05-25930Wolves4Marlies5ALXXBoxScore
179 - 2022-05-27943Punishers6Wolves4BLBoxScore
183 - 2022-05-31961Wolves6Reign4AWBoxScore
184 - 2022-06-01971Wolves6Rampage3AWBoxScore
186 - 2022-06-03982Devils5Wolves8BWBoxScore
190 - 2022-06-07996Wolves5Sound Tigers3AWR1BoxScore
192 - 2022-06-091007Monsters3Wolves2BLXXBoxScore
198 - 2022-06-151028Bears2Wolves3BWBoxScore
199 - 2022-06-161035Wolves5Marlies6ALBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3515
Attendance74,97837,347
Attendance PCT93.72%93.37%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 2808 - 93.60% 83,591$3,343,658$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
2,158,622$ 1,689,500$ 1,529,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
8,448$ 1,646,860$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 10,948$ 0$




Wolves 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

Wolves Goalies Stat Leaders (Regular Season)

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

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

Wolves 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

Wolves Goalies Stat Leaders (Play-Off)

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