Out of Date Version of the STHS! Please update your version!
Login

Monsters
GP: 82 | W: 49 | L: 24 | OTL: 9 | P: 107
GF: 287 | GA: 258 | PP%: 19.75% | PK%: 80.38%
GM : Benoit Toupin | Morale : 50 | Team Overall : 57
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Game Center
Monsters
49-24-9, 107pts
3
FINAL
4 Phantoms
33-46-3, 69pts
Team Stats
W1StreakL1
24-13-4Home Record17-21-3
25-11-5Away Record16-25-0
4-2-4Last 10 Games5-5-0
3.50Goals Per Game3.01
3.15Goals Against Per Game4.01
19.75%Power Play Percentage14.29%
80.38%Penalty Kill Percentage77.35%
Manchots
43-32-7, 93pts
2
FINAL
7 Monsters
49-24-9, 107pts
Team Stats
L1StreakW1
23-14-4Home Record24-13-4
20-18-3Away Record25-11-5
6-4-0Last 10 Games4-2-4
3.10Goals Per Game3.50
2.98Goals Against Per Game3.15
19.29%Power Play Percentage19.75%
82.53%Penalty Kill Percentage80.38%
Team Leaders
Goals
Benoit-Olivier Groulx
38
Assists
Nils Lundkvist
52
Points
Benoit-Olivier Groulx
83
Plus/Minus
Benoit-Olivier Groulx
31
Wins
Mads Sogaard
49
Save Percentage
Jakub Skarek
0.962

Team Stats
Goals For
287
3.50 GFG
Shots For
3209
39.13 Avg
Power Play Percentage
19.7%
47 GF
Offensive Zone Start
42.0%
Goals Against
258
3.15 GAA
Shots Against
2875
35.06 Avg
Penalty Kill Percentage
80.4%%
52 GA
Defensive Zone Start
39.0%
Team Info

General ManagerBenoit Toupin
DivisionNord-Est
ConferenceEst
Captain
Assistant #1
Assistant #2


Arena Info

Capacity3,000
Attendance2,859
Season Tickets300


Roster Info

Pro Team25
Farm Team20
Contract Limit45 / 50
Prospects16


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 Average
1Wayne SimmondsXX100.00869464727354815644625860618487050620334750,000$
2Sheldon DriesXX100.00714299746456696842597165255050050610273700,000$
3Brandon PirriXXX100.00636861676853516579526966686768050600302650,000$
4Benoit-Olivier Groulx (R)X100.00764496677359765860605777254545050600213822,500$
5Julien GauthierX100.00854694778456656034585761255757050600232990,900$
6Luke PhilpX100.00736591636564656278586263594444050590251600,000$
7Cole Fonstad (R)XX100.00706093706050495771525860554444050550211900,000$
8Dominik Bokk (R)XX100.00766991676952535150504762454444050540213863,333$
9Kasper BjorkqvistXX100.00767284647258605150435462514444050540243800,000$
10Tim SoderlundXX100.00726498645853495254514563414444050530232825,834$
11Matt FilipeXX100.00737275607256585164475060484444050530231600,000$
12Chad Yetman (R)XX100.00726492646445444961474659444444050510213560,000$
13Matt KierstedX100.00754393716764665725495078254545050620231858,750$
14Kurtis MacDermidX100.00839959699046695525444867256060050610272650,000$
15Nils Lundkvist (R)X100.00674299766664586425504866254646050600213925,000$
16Connor MackeyX100.00687258717267705525544259404444050580253925,000$
17Jake Christiansen (R)X100.00764499667254625425395464254444050570222925,000$
18Adam Ginning (R)X100.00585870617758833825333566385052050560213825,000$
Scratches
1Brandon Coe (R)X100.00757488627455574849484362434444050520193650,000$
2Chase PriskieX100.00736885656861635725504962474444050570252675,000$
3Keaton MiddletonX100.00819159619155584725384063384444050560231650,000$
4Wyatte Wylie (R)X100.00757088637059624825394161394444050550213820,833$
5Drew Helleson (R)X100.00787391697338374525363961374444050530204925,000$
TEAM AVERAGE100.0074658467715661544349516440494905057
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 Average
1Mads Sogaard (R)100.0054425386585452585655304444050560202925,000$
2Jakub Skarek (R)100.0048445581494950545050304444050520213764,167$
Scratches
TEAM AVERAGE100.005143548454525156535330444405054
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary


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
1Benoit-Olivier GroulxMonsters (Clb)C8238458331200942253861132409.84%34154618.861192063193213152259550.90%216100001.0728000944
2Brandon PirriMonsters (Clb)C/LW/RW823740772936014412235710727110.36%18145617.77713205919203371405356.65%23300011.0611000668
3Nils LundkvistMonsters (Clb)D81105262252755313513851977.25%110164420.302911551420223192100.00%000000.7500000143
4Sheldon DriesMonsters (Clb)C/LW8227305724018218348812987.76%24174821.3227947197022122378042.48%202200010.65310000333
5Matt KierstedMonsters (Clb)D82124557-718087139174651376.90%143192523.496814812110112214310.00%000000.5900000312
6Julien GauthierMonsters (Clb)RW822135565220102111255601658.24%15161219.66471149200404131150241.38%11600000.6923000122
7Luke PhilpMonsters (Clb)C8222345610240761622197015810.05%7101912.43123316000023257.86%118900011.1000000422
8Ronald AttardColumbusD51163551-632016011216456959.76%94122023.936713741331123120000.00%000100.8400000634
9Wayne SimmondsMonsters (Clb)LW/RW822129501580294122219501379.59%12154018.78156321990003385150.58%25900000.65410000325
10Cole FonstadMonsters (Clb)C/LW82172643132607791203671478.37%10110013.430113400021101156.34%14200000.7800000210
11Connor MackeyMonsters (Clb)D8282937158351976777355410.39%62142717.413471673000167010.00%000000.5200100220
12Dominik BokkMonsters (Clb)LW/RW8282533262410944112728976.30%12128415.67191025192000041149.41%8500000.5100002102
13Kurtis MacDermidMonsters (Clb)D82524291012525333488556585.88%97166420.30011281800001163100.00%000000.3500301052
14Chad YetmanMonsters (Clb)C/RW801214264240615895305912.63%498312.290223190000273244.25%11300000.5300000023
15Kasper BjorkqvistMonsters (Clb)LW/RW7071118-426063439123557.69%56399.1400002000001044.19%4300000.5600000000
16Tim SoderlundMonsters (Clb)LW/RW8071017-134025608225728.54%157279.102135110000271038.10%4200000.4700000011
17Jake ChristiansenMonsters (Clb)D82891724240934778285710.26%105150718.3911211680110129200.00%000000.2300000002
18Matt FilipeMonsters (Clb)C/LW82459-12271578837823555.13%136958.4800000000000148.93%79700000.2600012010
19Adam GinningMonsters (Clb)D271895802013162126.25%3544316.4400014000014000.00%000000.4100000000
20Brandon CoeMonsters (Clb)RW101011005312548.33%1929.2600000000000066.67%600000.2200000000
21Chase PriskieMonsters (Clb)D4000240515100.00%48922.430002400008000.00%000000.00%00000000
22Wyatte WylieMonsters (Clb)D1000100310000.00%31717.200000000000000.00%000000.00%00000000
Team Total or Average14702825067881626166020821902320997622688.79%8232438916.594786133557204971118621843442049.38%720800130.651232415413943
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
1Mads SogaardMonsters (Clb)82492490.9123.0449356025028470220.63633820674
2Jakub SkarekMonsters (Clb)20000.9621.1154001260000.00%0076000
Team Total or Average84492490.9133.024989602512873022338276674


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 Ave 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
Adam GinningMonsters (Clb)D212000-01-13Yes206 Lbs6 ft4NoNoNo3Pro & Farm825,000$0$0$No825,000$825,000$Link
Benoit-Olivier GroulxMonsters (Clb)C212000-02-05Yes195 Lbs6 ft2NoNoNo3Pro & Farm822,500$0$0$No822,500$822,500$Link
Brandon CoeMonsters (Clb)RW192001-12-01Yes190 Lbs6 ft4NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Link
Brandon Pirri (1 Way Contract)Monsters (Clb)C/LW/RW301991-04-10No186 Lbs6 ft0YesNoYes2Pro & Farm650,000$0$0$No650,000$Link
Chad YetmanMonsters (Clb)C/RW212000-02-18Yes179 Lbs5 ft11NoNoNo3Pro & Farm560,000$0$0$No560,000$560,000$Link
Chase PriskieMonsters (Clb)D251996-03-18No185 Lbs6 ft0NoNoYes2Pro & Farm675,000$0$0$No675,000$Link
Cole FonstadMonsters (Clb)C/LW212000-04-24Yes165 Lbs5 ft10YesNoNo1Pro & Farm900,000$0$0$NoLink
Connor MackeyMonsters (Clb)D251996-09-12No190 Lbs6 ft2NoNoYes3Pro & Farm925,000$0$0$No925,000$925,000$Link
Dominik BokkMonsters (Clb)LW/RW212000-02-03Yes181 Lbs6 ft2NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$Link
Drew HellesonMonsters (Clb)D202001-03-26Yes190 Lbs6 ft3NoNoNo4Pro & Farm925,000$0$0$No925,000$925,000$925,000$Link
Jake ChristiansenMonsters (Clb)D221999-09-12Yes195 Lbs6 ft1NoNoNo2Pro & Farm925,000$0$0$No925,000$Link
Jakub SkarekMonsters (Clb)G211999-11-10Yes202 Lbs6 ft3NoNoNo3Pro & Farm764,167$0$0$No764,167$764,167$Link
Julien GauthierMonsters (Clb)RW231997-10-15No227 Lbs6 ft4NoNoNo2Pro & Farm990,900$0$0$No990,900$Link
Kasper BjorkqvistMonsters (Clb)LW/RW241997-07-10No198 Lbs6 ft1NoNoYes3Pro & Farm800,000$0$0$No800,000$800,000$Link
Keaton MiddletonMonsters (Clb)D231998-02-10No240 Lbs6 ft6NoNoNo1Pro & Farm650,000$0$0$NoLink
Kurtis MacDermid (1 Way Contract)Monsters (Clb)D271994-03-25No233 Lbs6 ft5NoNoYes2Pro & Farm650,000$0$0$No650,000$Link
Luke PhilpMonsters (Clb)C251995-11-06No181 Lbs5 ft10NoNoYes1Pro & Farm600,000$0$0$NoLink
Mads SogaardMonsters (Clb)G202000-12-13Yes201 Lbs6 ft7NoNoNo2Pro & Farm925,000$0$0$No925,000$Link
Matt FilipeMonsters (Clb)C/LW231997-12-31No193 Lbs6 ft2NoNoNo1Pro & Farm600,000$0$0$NoLink
Matt KierstedMonsters (Clb)D231998-04-14No181 Lbs6 ft0NoNoNo1Pro & Farm858,750$0$0$NoLink
Nils LundkvistMonsters (Clb)D212000-07-27Yes187 Lbs5 ft10NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Link
Sheldon Dries (1 Way Contract)Monsters (Clb)C/LW271994-04-23No180 Lbs5 ft9NoNoYes3Pro & Farm700,000$0$0$No700,000$700,000$Link
Tim SoderlundMonsters (Clb)LW/RW231998-01-23No163 Lbs5 ft9NoNoNo2Pro & Farm825,834$0$0$No825,834$Link
Wayne Simmonds (1 Way Contract)Monsters (Clb)LW/RW331988-08-26No185 Lbs6 ft2YesNoYes4Pro & Farm750,000$0$0$No750,000$750,000$750,000$Link
Wyatte WylieMonsters (Clb)D211999-11-02Yes190 Lbs6 ft0NoNoNo3Pro & Farm820,833$0$0$No820,833$820,833$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2523.20193 Lbs6 ft12.40783,253$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Wayne SimmondsSheldon DriesJulien Gauthier40014
2Brandon PirriBenoit-Olivier GroulxDominik Bokk30014
3Cole FonstadLuke PhilpKasper Bjorkqvist20023
4Tim SoderlundMatt FilipeChad Yetman10032
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Kurtis MacDermidMatt Kiersted40014
2Jake ChristiansenNils Lundkvist30023
3Connor MackeyAdam Ginning20023
4Kurtis MacDermidMatt Kiersted10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Wayne SimmondsSheldon DriesJulien Gauthier60050
2Brandon PirriBenoit-Olivier GroulxDominik Bokk40005
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Kurtis MacDermidMatt Kiersted60014
2Jake ChristiansenConnor Mackey40014
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Benoit-Olivier GroulxSheldon Dries60122
2Brandon PirriJulien Gauthier40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Kurtis MacDermidMatt Kiersted60122
2Jake ChristiansenNils Lundkvist40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Benoit-Olivier Groulx60122Kurtis MacDermidMatt Kiersted60122
2Sheldon Dries40122Jake ChristiansenNils Lundkvist40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Wayne SimmondsSheldon Dries60122
2Benoit-Olivier GroulxJulien Gauthier40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Kurtis MacDermidMatt Kiersted60122
2Jake ChristiansenNils Lundkvist40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Wayne SimmondsSheldon DriesJulien GauthierKurtis MacDermidMatt Kiersted
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Brandon PirriBenoit-Olivier GroulxJulien GauthierKurtis MacDermidMatt Kiersted
Extra Forwards
Normal PowerPlayPenalty Kill
Brandon Pirri, Luke Philp, Cole FonstadCole Fonstad, Luke PhilpCole Fonstad
Extra Defensemen
Normal PowerPlayPenalty Kill
Connor Mackey, Jake Christiansen, Kurtis MacDermidConnor MackeyNils Lundkvist, Kurtis MacDermid
Penalty Shots
Wayne Simmonds, Sheldon Dries, Benoit-Olivier Groulx, Julien Gauthier, Brandon Pirri
Goalie
#1 : Mads Sogaard, #2 : Jakub Skarek


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
1Admirals211000004401010000013-21100000031220.500471100109927716731039103210937750148385120.00%4175.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
2Baby Hawks20101000710-3100010004311010000037-420.5007132000109927716801039103210937770292566500.00%10370.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
3Bears42100010161062010001078-12200000092760.750162642101099277161551039103210937713636301011815.56%14192.86%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
4Bruins310010011293110000004132000100188050.8331223350010992771611210391032109377762420728225.00%9277.78%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
5Cabaret Lady Mary Ann3300000015782200000012661100000031261.000152843001099277161831039103210937798271896300.00%9366.67%21531302550.61%1363281248.47%665137148.50%2022138218766051092557
6Caroline321000001174211000006511100000052340.6671120310010992771699103910321093771273637884250.00%13376.92%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
7Chiefs211000009721010000034-11100000063320.50091524001099277168610391032109377651516605360.00%8362.50%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
8Chill22000000844110000003211100000052341.00081422001099277168610391032109377631421447114.29%8187.50%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
9Comets2110000056-1110000003121010000025-320.50051015001099277167210391032109377722111515240.00%30100.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
10Cougars32000010161062100001012931100000041361.00016274300109927716117103910321093771043128988450.00%13469.23%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
11Crunch311010001082211000006511000100043140.66710182800109927716158103910321093778027217312325.00%7271.43%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
12Heat210001008711000010034-11100000053230.750813210010992771684103910321093778028849400.00%40100.00%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
13Jayhawks2110000046-21010000003-31100000043120.5004812001099277165710391032109377641725507228.57%9366.67%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
14Las Vegas21000010972100000105411100000043141.000914230010992771693103910321093778017214210220.00%8275.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
15Manchots422000001413122000000113820200000310-740.50014253900109927716116103910321093771283934934125.00%17194.12%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
16Marlies3200000113112110000005322100000188050.833132538001099277161201039103210937710027147315320.00%7185.71%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
17Minnesota21100000550110000003121010000024-220.500581300109927716761039103210937785282349200.00%9277.78%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
18Monarchs21001000972100010005411100000043141.00091726001099277168810391032109377692617505120.00%60100.00%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
19Monsters2010001056-11010000024-21000001032120.5005611001099277166610391032109377652212557228.57%6183.33%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
20Oceanics2020000027-51010000002-21010000025-300.00023510109927716781039103210937773204591200.00%2150.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
21Oil Kings2110000067-11010000024-21100000043120.5006111700109927716871039103210937786221841500.00%8187.50%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
22Phantoms4300000117107220000009452100000186270.87517304700109927716148103910321093771482818847114.29%80100.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
23Rocket312000001114-320200000711-41100000043120.333112031001099277161231039103210937710626236110440.00%9277.78%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
24Seattle211000006601010000012-11100000054120.5006101600109927716921039103210937781231050300.00%5180.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
25Senators321000008711010000035-22200000052340.667814220010992771687103910321093771092912819111.11%6183.33%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
26Sharks211000001082110000006241010000046-220.500101727001099277166810391032109377721318616233.33%8275.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
27Sound Tigers411001011318-52100010010912010000139-640.50013253800109927716166103910321093771755045110900.00%20670.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
28Spiders30200001715-81000000134-120200000411-710.1677132000109927716104103910321093771062722879222.22%11463.64%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
29Stars2010010013-21000010012-11010000001-110.250123001099277166510391032109377652914477114.29%70100.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
30Thunder320000101275110000005322100001074361.00012213300109927716113103910321093778325147312325.00%70100.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
31Wolf Pack4300010014122220000006422100010088070.875142337001099277161571039103210937715953358015320.00%10190.00%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
Total824024044552872582941191302331148125234121110212413913361070.65228750679320109927716320910391032109377287582362220822384719.75%2655280.38%71531302550.61%1363281248.47%665137148.50%2022138218766051092557
_Since Last GM Reset824024044552872582941191302331148125234121110212413913361070.65228750679320109927716320910391032109377287582362220822384719.75%2655280.38%71531302550.61%1363281248.47%665137148.50%2022138218766051092557
_Vs Conference4523110222515914217201240111178572125117011148185-4610.67815928344220109927716167110391032109377154742531211061412215.60%1372283.94%41531302550.61%1363281248.47%665137148.50%2022138218766051092557
_Vs Division267300203928571350001015237151323001024048-8190.365921622541010992771694510391032109377979269221643661015.15%931682.80%21531302550.61%1363281248.47%665137148.50%2022138218766051092557

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
82107W128750679332092875823622208220
All Games
GPWLOTWOTL SOWSOLGFGA
8240244455287258
Home Games
GPWLOTWOTL SOWSOLGFGA
4119132331148125
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4121112124139133
Last 10 Games
WLOTWOTL SOWSOL
420103
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2384719.75%2655280.38%7
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
10391032109377109927716
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1531302550.61%1363281248.47%665137148.50%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
2022138218766051092557


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
6 - 2022-10-126Monsters5Caroline2AWBoxScore
8 - 2022-10-1421Thunder3Monsters5BWBoxScore
9 - 2022-10-1533Monsters6Chiefs3AWBoxScore
12 - 2022-10-1850Comets1Monsters3BWBoxScore
14 - 2022-10-2063Chill2Monsters3BWBoxScore
16 - 2022-10-2282Manchots1Monsters4BWBoxScore
17 - 2022-10-2389Monsters4Wolf Pack3AWBoxScore
19 - 2022-10-2598Jayhawks3Monsters0BLBoxScore
22 - 2022-10-28122Bruins1Monsters4BWBoxScore
24 - 2022-10-30139Monsters2Spiders4ALBoxScore
29 - 2022-11-04174Monsters3Monsters2AWXXBoxScore
30 - 2022-11-05176Monsters4Monsters2BLBoxScore
35 - 2022-11-10214Phantoms1Monsters4BWBoxScore
37 - 2022-11-12231Monsters0Sound Tigers5ALBoxScore
40 - 2022-11-15250Phantoms3Monsters5BWBoxScore
42 - 2022-11-17263Rocket6Monsters4BLBoxScore
44 - 2022-11-19280Cougars3Monsters5BWBoxScore
45 - 2022-11-20289Cabaret Lady Mary Ann3Monsters6BWBoxScore
48 - 2022-11-23307Rocket5Monsters3BLBoxScore
50 - 2022-11-25326Sound Tigers5Monsters7BWBoxScore
51 - 2022-11-26338Monsters5Chill2AWBoxScore
53 - 2022-11-28349Las Vegas4Monsters5BWXXBoxScore
57 - 2022-12-02378Monsters2Oceanics5ALBoxScore
59 - 2022-12-04394Cougars6Monsters7BWXXBoxScore
61 - 2022-12-06404Monsters2Manchots5ALBoxScore
62 - 2022-12-07412Crunch2Monsters4BWBoxScore
64 - 2022-12-09424Heat4Monsters3BLXBoxScore
66 - 2022-12-11443Monarchs4Monsters5BWXBoxScore
68 - 2022-12-13455Monsters3Cabaret Lady Mary Ann1AWBoxScore
70 - 2022-12-15470Monsters5Thunder3AWBoxScore
72 - 2022-12-17484Monsters4Bruins3AWXBoxScore
74 - 2022-12-19502Stars2Monsters1BLXBoxScore
75 - 2022-12-20510Monsters5Phantoms2AWBoxScore
78 - 2022-12-23540Monsters3Baby Hawks7ALBoxScore
82 - 2022-12-27547Crunch3Monsters2BLBoxScore
84 - 2022-12-29567Monsters3Sound Tigers4ALXXBoxScore
86 - 2022-12-31584Baby Hawks3Monsters4BWXBoxScore
89 - 2023-01-03601Monsters2Senators1AWBoxScore
91 - 2023-01-05617Bears6Monsters4BLBoxScore
93 - 2023-01-07629Caroline2Monsters4BWBoxScore
94 - 2023-01-08639Monsters4Bears1AWBoxScore
96 - 2023-01-10648Monsters2Thunder1AWXXBoxScore
98 - 2023-01-12662Caroline3Monsters2BLBoxScore
100 - 2023-01-14679Monsters4Cougars1AWBoxScore
102 - 2023-01-16701Wolf Pack2Monsters3BWBoxScore
105 - 2023-01-19717Admirals3Monsters1BLBoxScore
107 - 2023-01-21736Sharks2Monsters6BWBoxScore
109 - 2023-01-23754Monsters5Heat3AWBoxScore
111 - 2023-01-25768Monsters4Oil Kings3AWBoxScore
113 - 2023-01-27787Monsters2Comets5ALBoxScore
114 - 2023-01-28797Monsters5Seattle4AWBoxScore
117 - 2023-01-31804Bears2Monsters3BWXXBoxScore
127 - 2023-02-10829Marlies3Monsters5BWBoxScore
128 - 2023-02-11840Monsters4Marlies3AWBoxScore
131 - 2023-02-14857Spiders4Monsters3BLXXBoxScore
133 - 2023-02-16872Oceanics2Monsters0BLBoxScore
135 - 2023-02-18887Monsters0Stars1ALBoxScore
136 - 2023-02-19901Monsters4Jayhawks3AWBoxScore
140 - 2023-02-23924Minnesota1Monsters3BWBoxScore
142 - 2023-02-25936Oil Kings4Monsters2BLBoxScore
143 - 2023-02-26948Monsters2Minnesota4ALBoxScore
145 - 2023-02-28958Monsters4Crunch3AWXBoxScore
148 - 2023-03-03984Seattle2Monsters1BLBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
149 - 2023-03-04996Monsters3Senators1AWBoxScore
152 - 2023-03-071013Monsters1Manchots5ALBoxScore
156 - 2023-03-111045Chiefs4Monsters3BLBoxScore
159 - 2023-03-141074Monsters4Sharks6ALBoxScore
161 - 2023-03-161089Monsters4Monarchs3AWBoxScore
162 - 2023-03-171094Monsters3Admirals1AWBoxScore
164 - 2023-03-191110Monsters4Las Vegas3AWBoxScore
166 - 2023-03-211121Monsters5Bears1AWBoxScore
169 - 2023-03-241147Sound Tigers4Monsters3BLXBoxScore
170 - 2023-03-251159Monsters4Rocket3AWBoxScore
173 - 2023-03-281176Monsters4Wolf Pack5ALXBoxScore
175 - 2023-03-301189Monsters4Bruins5ALXXBoxScore
177 - 2023-04-011208Cabaret Lady Mary Ann3Monsters6BWBoxScore
178 - 2023-04-021220Senators5Monsters3BLBoxScore
180 - 2023-04-041230Monsters4Marlies5ALXXBoxScore
182 - 2023-04-061243Monsters2Spiders7ALBoxScore
184 - 2023-04-081264Wolf Pack2Monsters3BWBoxScore
187 - 2023-04-111287Monsters3Phantoms4ALXXBoxScore
189 - 2023-04-131303Manchots2Monsters7BWBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3515
Attendance78,23739,002
Attendance PCT95.41%95.13%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 2859 - 95.32% 81,057$3,323,325$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
1,740,595$ 1,683,131$ 1,683,131$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
8,859$ 1,740,595$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 8,859$ 0$




Monsters 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

Monsters Goalies Stat Leaders (Regular Season)

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

Monsters 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

Monsters 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

Monsters Goalies Stat Leaders (Play-Off)

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