Login

Monsters
GP: 29 | W: 15 | L: 13 | OTL: 1 | P: 31
GF: 90 | GA: 90 | PP%: 21.18% | PK%: 80.33%
GM : Jonathan Aubin Beaumier | Morale : 50 | Team Overall : 62
Next Games #438 vs Barracuda
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Game Center
Monsters
15-13-1, 31pts
2
FINAL
4 Wolves
12-12-5, 29pts
Team Stats
W1StreakW2
9-6-0Home Record8-5-2
6-7-1Away Record4-7-3
7-3-0Last 10 Games4-3-3
3.10Goals Per Game3.41
3.10Goals Against Per Game3.59
21.18%Power Play Percentage16.84%
80.33%Penalty Kill Percentage78.99%
Penguins
14-13-2, 30pts
3
FINAL
6 Monsters
15-13-1, 31pts
Team Stats
L2StreakW1
10-3-1Home Record9-6-0
4-10-1Away Record6-7-1
5-5-0Last 10 Games7-3-0
2.83Goals Per Game3.10
3.31Goals Against Per Game3.10
17.58%Power Play Percentage21.18%
78.26%Penalty Kill Percentage80.33%
Monsters
15-13-1, 31pts
2022-12-08
Barracuda
11-14-4, 26pts
Team Stats
W1StreakW1
9-6-0Home Record7-6-1
6-7-1Away Record4-8-3
7-3-0Last 10 Games5-3-2
3.10Goals Per Game2.66
3.10Goals Against Per Game3.52
21.18%Power Play Percentage14.05%
80.33%Penalty Kill Percentage78.57%
Monsters
15-13-1, 31pts
2022-12-10
Crunch
16-9-4, 36pts
Team Stats
W1StreakW1
9-6-0Home Record10-3-2
6-7-1Away Record6-6-2
7-3-0Last 10 Games5-3-2
3.10Goals Per Game4.03
3.10Goals Against Per Game3.38
21.18%Power Play Percentage25.00%
80.33%Penalty Kill Percentage78.89%
Monsters
15-13-1, 31pts
2022-12-13
Reign
18-10-1, 37pts
Team Stats
W1StreakOTL1
9-6-0Home Record9-5-1
6-7-1Away Record9-5-0
7-3-0Last 10 Games6-3-1
3.10Goals Per Game3.34
3.10Goals Against Per Game3.07
21.18%Power Play Percentage18.92%
80.33%Penalty Kill Percentage80.00%
Team Leaders
Michael CarconeGoals
Michael Carcone
10
Connor MacKeyAssists
Connor MacKey
15
Hayden HodgsonPoints
Hayden Hodgson
21
Lukas VejdemoPlus/Minus
Lukas Vejdemo
5
Michael HouserWins
Michael Houser
15
Cory SchneiderSave Percentage
Cory Schneider
0.936

Team Stats
Goals For
90
3.10 GFG
Shots For
889
30.66 Avg
Power Play Percentage
21.2%
18 GF
Offensive Zone Start
37.5%
Goals Against
90
3.10 GAA
Shots Against
1041
35.90 Avg
Penalty Kill Percentage
80.3%
24 GA
Defensive Zone Start
44.9%
Team Info

General ManagerJonathan Aubin Beaumier
CoachJeff Blashill
DivisionPacific
ConferenceAmerican
Captain
Assistant #1
Assistant #2


Arena Info

Capacity3,000
Attendance1,968
Season Tickets0


Roster Info

Pro Team22
Farm Team19
Contract Limit41 / 250
Prospects31


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
1Cole SchneiderXXX100.00663893628085936355646559647277044650322700,000$
2Hayden Hodgson (R)X100.007434616482817765586667596466680506502611,500,000$
3Joel KivirantaXX100.007534846771768266576361586765680506402611,250,000$
4Lukas VejdemoXX100.006738936477767563796264656267680506402611,000,000$
5Michael CarconeX100.006740716263898763605964576768670506202631,000,000$
6Austin Rueschhoff (R)X100.00908565559978845753555864566567050620251900,000$
7Bobby McMann (R)X100.00693892607988845956546360616668050620263800,000$
8Marc Michaelis (R)X100.006636846370776860566160596367690506202731,000,000$
9Liam O'BrienXX100.009072555980737658705657555967680506102851,000,000$
10Jeffrey Truchon-VielX100.008380615781747658555961555665670506102511,000,000$
11Callahan Burke (R)X100.00583782596786855854575655586567050600253800,000$
12Haralds Egle (R)X100.00603791576974675660575854536668050590262750,000$
13Connor MacKey (R)X100.006834616581808364306765625366680506402621,000,000$
14Jack Ahcan (R)X100.00633592656785766430626559536567050630252750,000$
15Kristians Rubins (R)X100.00857459549576735530575659506567050610241700,000$
16Nikolas Brouillard (R)X100.00574363616474865930625756506769047600271750,000$
17Colton Poolman (R)X100.00653792547461855230565155456769050590261750,000$
18Tory Dello (R)X100.00634074557264805430565355466567047580251750,000$
Scratches
1Peter Abbandonato (R)X100.00623688597169725670625657616466050600243800,000$
2Turner Ottenbreit (R)X100.00733974588267885530575356466567047600251750,000$
TEAM AVERAGE100.0070457760767780595060605857666804962
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
1Michael Houser (R)100.0075717276747375747375747084050660302750,000$
2Cory Schneider100.0074717282737274737274738190050650361750,000$
Scratches
TEAM AVERAGE100.007571727974737574737574768705066
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Jeff Blashill79817984726778USA482250,000$


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
1Shane PintoBlue JacketsC24101727-1602610510226769.80%2761625.7005514620113891052.70%79500100.8801000212
2Hayden HodgsonMonsters (Clb)RW29912212140703687257410.34%656619.5412315730111532137.10%6200000.7411000310
3Lukas VejdemoMonsters (Clb)C/LW29811195006838727719.20%1152818.2215616672023441154.17%62400000.7201000210
4Michael CarconeMonsters (Clb)LW29108182140333864184515.63%439813.761123120111160150.00%2000010.9000000220
5Joel KivirantaMonsters (Clb)LW/RW2951318180425410223754.90%356019.3224615710001340034.78%4600000.6400000110
6Connor MacKeyMonsters (Clb)D2921517446010846338356.06%4878026.900001472000087200.00%000000.4400000022
7Jack AhcanMonsters (Clb)D294111528028354310269.30%4180827.8732521750001104100.00%000000.3700000011
8Kristians RubinsMonsters (Clb)D29312154780144202771911.11%3968123.50235964011064200.00%000000.4400000022
9Austin RueschhoffMonsters (Clb)RW1777140180521932103021.88%430117.743361041000051055.17%2900000.9300000032
10Bobby McMannMonsters (Clb)C294812-12010415516287.27%1141914.47101111000000043.54%48000000.5700000010
11Marc MichaelisMonsters (Clb)LW29381150002227112411.11%11976.8000001000190053.33%1500001.1100000000
12Colton PoolmanMonsters (Clb)D28459-2602018137930.77%4559421.22202635000070000.00%000000.3000000000
13Liam O'BrienMonsters (Clb)C/LW29268316047202041510.00%12137.3700000000000144.31%16700000.7500000100
14Haralds EgleMonsters (Clb)RW24628-2007193682116.67%329112.1300012000003037.50%2400000.5500000010
15Peter AbbandonatoMonsters (Clb)C2425714039100920.00%82259.400111120112440042.37%5900000.6200000001
16Cole SchneiderMonsters (Clb)C/LW/RW17055-4009224716330.00%435821.110116410001560043.11%22500000.2800000000
17Jeffrey Truchon-VielMonsters (Clb)LW29134-5601510122128.33%11424.92000290000210036.36%1100000.5600000000
18Nikolas BrouillardMonsters (Clb)D1013414061070814.29%920720.75022322000040000.00%000000.3900000001
19Turner OttenbreitMonsters (Clb)D511258011440025.00%68016.050000300004010.00%000000.5000000000
20Callahan BurkeMonsters (Clb)C241011001123350.00%1271.13000020000150050.00%1000000.7400000000
21Tory DelloMonsters (Clb)D5000-120615210.00%66613.200000000002000.00%000000.0000000000
Team Total or Average4978315223520240064461381522361410.18%279806616.231629451376812571476813548.81%256700110.5813000111611
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
1Michael HouserMonsters (Clb)29151210.9113.22154803839310001.0003290611
2Cory SchneiderMonsters (Clb)50100.9362.102000071100000.0000029000
Team Total or Average34151310.9143.091749039010410001.00032929611


Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Player Name Team NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Force Waivers Contract Type Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Link
Austin RueschhoffMonsters (Clb)RW251997-09-07Yes230 Lbs6 ft7NoNoNo1Pro & Farm900,000$0$0$NoNHL Link
Bobby McMannMonsters (Clb)C261996-06-15Yes203 Lbs6 ft1NoNoNo3Pro & Farm800,000$0$0$No800,000$800,000$NHL Link
Callahan BurkeMonsters (Clb)C251997-03-24Yes185 Lbs5 ft10NoNoNo3Pro & Farm800,000$0$0$No800,000$800,000$NHL Link
Cole SchneiderMonsters (Clb)C/LW/RW321990-08-26No203 Lbs6 ft1NoNoNo2Pro & Farm700,000$0$0$No700,000$NHL Link
Colton PoolmanMonsters (Clb)D261995-12-18Yes200 Lbs6 ft0NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Connor MacKeyMonsters (Clb)D261996-09-12Yes190 Lbs6 ft2NoNoNo2Pro & Farm1,000,000$0$0$No1,000,000$NHL Link
Cory SchneiderMonsters (Clb)G361986-03-18No200 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Haralds EgleMonsters (Clb)RW261996-11-05Yes194 Lbs5 ft10NoNoNo2Pro & Farm750,000$0$0$No750,000$NHL Link
Hayden HodgsonMonsters (Clb)RW261996-03-02Yes207 Lbs6 ft2NoNoNo1Pro & Farm1,500,000$0$0$NoNHL Link
Jack AhcanMonsters (Clb)D251997-05-18Yes178 Lbs5 ft8NoNoNo2Pro & Farm750,000$0$0$No750,000$NHL Link
Jeffrey Truchon-VielMonsters (Clb)LW251997-01-28No197 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$0$0$No
Joel KivirantaMonsters (Clb)LW/RW261996-03-23No176 Lbs5 ft10NoNoNo1Pro & Farm1,250,000$0$0$NoNHL Link
Kristians RubinsMonsters (Clb)D241997-12-11Yes221 Lbs6 ft5NoNoNo1Pro & Farm700,000$0$0$NoNHL Link
Liam O'BrienMonsters (Clb)C/LW281994-07-29No215 Lbs6 ft1NoNoNo5Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$1,000,000$1,000,000$NHL Link
Lukas VejdemoMonsters (Clb)C/LW261996-01-25No196 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$0$0$NoNHL Link
Marc MichaelisMonsters (Clb)LW271995-07-31Yes187 Lbs5 ft11NoNoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$NHL Link
Michael CarconeMonsters (Clb)LW261996-05-19No170 Lbs5 ft9NoNoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$NHL Link
Michael HouserMonsters (Clb)G301992-09-13Yes185 Lbs6 ft1NoNoNo2Pro & Farm750,000$0$0$No750,000$NHL Link
Nikolas BrouillardMonsters (Clb)D271995-02-07Yes168 Lbs5 ft11NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Peter AbbandonatoMonsters (Clb)C241998-03-25Yes194 Lbs5 ft10NoNoNo3Pro & Farm800,000$0$0$No800,000$800,000$NHL Link
Tory DelloMonsters (Clb)D251997-02-14Yes190 Lbs6 ft0NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Turner OttenbreitMonsters (Clb)D251997-07-09Yes192 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2226.64195 Lbs6 ft11.86884,091$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Liam O'BrienCole SchneiderHayden Hodgson40122
2Michael CarconeLukas VejdemoJoel Kiviranta30122
3Marc MichaelisBobby McMannAustin Rueschhoff20122
4Jeffrey Truchon-VielLiam O'BrienHaralds Egle10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Connor MacKeyJack Ahcan40122
2Kristians RubinsNikolas Brouillard30122
3Colton PoolmanTory Dello20122
4Connor MacKeyJack Ahcan10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Joel KivirantaCole SchneiderHayden Hodgson60122
2Michael CarconeLukas VejdemoJoel Kiviranta40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Connor MacKeyJack Ahcan60122
2Kristians RubinsNikolas Brouillard40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Cole SchneiderJoel Kiviranta60122
2Lukas VejdemoMichael Carcone40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Connor MacKeyJack Ahcan60122
2Kristians RubinsNikolas Brouillard40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Cole Schneider60122Connor MacKeyJack Ahcan60122
2Lukas Vejdemo40122Kristians RubinsNikolas Brouillard40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Cole SchneiderJoel Kiviranta60122
2Lukas VejdemoMichael Carcone40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Connor MacKeyJack Ahcan60122
2Kristians RubinsNikolas Brouillard40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Joel KivirantaCole SchneiderHayden HodgsonConnor MacKeyJack Ahcan
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Joel KivirantaCole SchneiderHayden HodgsonConnor MacKeyJack Ahcan
Extra Forwards
Normal PowerPlayPenalty Kill
Austin Rueschhoff, Michael Carcone, Marc MichaelisAustin Rueschhoff, Michael CarconeAustin Rueschhoff
Extra Defensemen
Normal PowerPlayPenalty Kill
Nikolas Brouillard, Colton Poolman, Tory DelloNikolas BrouillardNikolas Brouillard, Colton Poolman
Penalty Shots
Cole Schneider, Hayden Hodgson, Joel Kiviranta, Lukas Vejdemo, Austin Rueschhoff
Goalie
#1 : Michael Houser, #2 : Cory Schneider
Custom OT Lines Forwards
Cole Schneider, Hayden Hodgson, Joel Kiviranta, Lukas Vejdemo, Austin Rueschhoff, Michael Carcone, Michael Carcone, Marc Michaelis, Bobby McMann, Liam O'Brien, Jeffrey Truchon-Viel
Custom OT Lines Defensemen
Connor MacKey, Jack Ahcan, Kristians Rubins, Nikolas Brouillard, Colton Poolman


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
1Admirals31100100711-41100000031220100100410-630.5007121900392324484289290302111052532751119.09%15380.00%148797150.15%550116447.25%23045750.33%650441732218368178
2Americans11000000303110000003030000000000021.00034701392324428289290302112384207114.29%20100.00%048797150.15%550116447.25%23045750.33%650441732218368178
3Barracuda211000009811010000034-11100000064220.5009152400392324480289290302116716184010330.00%8275.00%048797150.15%550116447.25%23045750.33%650441732218368178
4Bruins1010000036-31010000036-30000000000000.00035800392324432289290302112641217300.00%6350.00%048797150.15%550116447.25%23045750.33%650441732218368178
5Gulls321000001082211000009811100000010140.6671018280139232448328929030211913026816233.33%13376.92%148797150.15%550116447.25%23045750.33%650441732218368178
6Heat3110100013112211000009811000100043140.6671322350039232441052892903021110721287610330.00%13376.92%148797150.15%550116447.25%23045750.33%650441732218368178
7Marlies21100000431110000004221010000001-120.50048120039232445028929030211702712464125.00%60100.00%048797150.15%550116447.25%23045750.33%650441732218368178
8Moose10001000211100010002110000000000021.00024600392324425289290302112810629300.00%20100.00%048797150.15%550116447.25%23045750.33%650441732218368178
9Penguins11000000633110000006330000000000021.000612180039232444028929030211381412254250.00%6266.67%048797150.15%550116447.25%23045750.33%650441732218368178
10Rampage504000101218-62020000059-43020001079-220.20012213300392324415128929030211212635510910110.00%22481.82%048797150.15%550116447.25%23045750.33%650441732218368178
11Reign2110000069-3110000005321010000016-520.500610160039232445628929030211932018504125.00%9277.78%048797150.15%550116447.25%23045750.33%650441732218368178
12Rocket11000000404000000000001100000040421.000481201392324434289290302112768233133.33%40100.00%048797150.15%550116447.25%23045750.33%650441732218368178
13Wheat Kings21100000660000000000002110000066020.50061016003923244672892903021172158424125.00%3166.67%048797150.15%550116447.25%23045750.33%650441732218368178
14Wild10001000321100010003210000000000021.00034700392324427289290302113310820200.00%40100.00%048797150.15%550116447.25%23045750.33%650441732218368178
15Wolves1010000024-2000000000001010000024-200.0002460039232442728929030211491320354125.00%9188.89%048797150.15%550116447.25%23045750.33%650441732218368178
Total2911130311090900157602000554781447011103543-8310.53490157247033923244889289290302111041282267688851821.18%1222480.33%348797150.15%550116447.25%23045750.33%650441732218368178
_Since Last GM Reset2911130311090900157602000554781447011103543-8310.53490157247033923244889289290302111041282267688851821.18%1222480.33%348797150.15%550116447.25%23045750.33%650441732218368178
_Vs Conference25812031107481-7125502000433851337011103143-12250.5007412820201392324475528929030211927250231603681420.59%1041981.73%348797150.15%550116447.25%23045750.33%650441732218368178
_Vs Division116901010403737450000028244424010101213-1160.727406910901392324434928929030211386979627633927.27%451077.78%248797150.15%550116447.25%23045750.33%650441732218368178

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
2931W190157247889104128226768803
All Games
GPWLOTWOTL SOWSOLGFGA
29111331109090
Home Games
GPWLOTWOTL SOWSOLGFGA
157620005547
Visitor Games
GPWLOTWOTL SOWSOLGFGA
144711103543
Last 10 Games
WLOTWOTL SOWSOL
630010
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
851821.18%1222480.33%3
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
289290302113923244
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
48797150.15%550116447.25%23045750.33%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
650441732218368178


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
2 - 2022-10-1111Monsters4Heat3AWXBoxScore
3 - 2022-10-1219Monsters4Wheat Kings3AWBoxScore
4 - 2022-10-1328Gulls6Monsters3BLBoxScore
7 - 2022-10-1646Monsters2Rampage4ALBoxScore
8 - 2022-10-1759Heat6Monsters4BLBoxScore
11 - 2022-10-2077Monsters0Marlies1ALBoxScore
13 - 2022-10-2289Moose1Monsters2BWXBoxScore
15 - 2022-10-24107Reign3Monsters5BWBoxScore
16 - 2022-10-25119Monsters1Reign6ALBoxScore
18 - 2022-10-27139Marlies2Monsters4BWBoxScore
21 - 2022-10-30157Monsters1Gulls0AWBoxScore
23 - 2022-11-01172Rampage6Monsters5BLBoxScore
26 - 2022-11-04191Barracuda4Monsters3BLBoxScore
27 - 2022-11-05200Monsters2Wheat Kings3ALBoxScore
29 - 2022-11-07217Bruins6Monsters3BLBoxScore
30 - 2022-11-08222Monsters3Rampage4ALBoxScore
32 - 2022-11-10240Monsters6Barracuda4AWBoxScore
33 - 2022-11-11247Monsters4Admirals5ALXBoxScore
36 - 2022-11-14269Wild2Monsters3BWXBoxScore
39 - 2022-11-17291Monsters4Rocket0AWBoxScore
40 - 2022-11-18298Rampage3Monsters0BLBoxScore
43 - 2022-11-21318Americans0Monsters3BWBoxScore
45 - 2022-11-23334Monsters2Rampage1AWXXBoxScore
47 - 2022-11-25351Admirals1Monsters3BWBoxScore
50 - 2022-11-28368Monsters0Admirals5ALBoxScore
51 - 2022-11-29379Gulls2Monsters6BWBoxScore
54 - 2022-12-02398Heat2Monsters5BWBoxScore
56 - 2022-12-04413Monsters2Wolves4ALBoxScore
58 - 2022-12-06427Penguins3Monsters6BWBoxScore
60 - 2022-12-08438Monsters-Barracuda-
62 - 2022-12-10452Monsters-Crunch-
65 - 2022-12-13472Monsters-Reign-
66 - 2022-12-14479Ice Hogs-Monsters-
68 - 2022-12-16495Monsters-Gulls-
70 - 2022-12-18507Reign-Monsters-
73 - 2022-12-21529Rampage-Monsters-
76 - 2022-12-24550Wheat Kings-Monsters-
77 - 2022-12-25555Monsters-Rampage-
80 - 2022-12-28576Monsters-Swamp Rabbits-
82 - 2022-12-30589Senators-Monsters-
85 - 2023-01-02610Moose-Monsters-
88 - 2023-01-05631Monsters-Gulls-
89 - 2023-01-06643Wild-Monsters-
93 - 2023-01-10665Wolves-Monsters-
95 - 2023-01-12680Monsters-Admirals-
97 - 2023-01-14696Monsters-Aces-
98 - 2023-01-15703Phantoms-Monsters-
101 - 2023-01-18724Wheat Kings-Monsters-
102 - 2023-01-19734Monsters-Aces-
105 - 2023-01-22747Monsters-Devils-
107 - 2023-01-24761Oil Kings-Monsters-
110 - 2023-01-27787Aces-Monsters-
112 - 2023-01-29802Monsters-Wolves-
114 - 2023-01-31818Monsters-Griffins-
115 - 2023-02-01826Sound Tigers-Monsters-
118 - 2023-02-04846Monsters-Barracuda-
119 - 2023-02-05852Moose-Monsters-
122 - 2023-02-08871Monsters-Moose-
124 - 2023-02-10883Wolfpack-Monsters-
126 - 2023-02-12902Monsters-Wheat Kings-
127 - 2023-02-13911Monsters-Wild-
129 - 2023-02-15920Gulls-Monsters-
132 - 2023-02-18943Heat-Monsters-
134 - 2023-02-20956Monsters-Falcons-
136 - 2023-02-22972Swamp Rabbits-Monsters-
138 - 2023-02-24983Monsters-Wild-
141 - 2023-02-271002Reign-Monsters-
142 - 2023-02-281012Monsters-Reign-
145 - 2023-03-031032Marlies-Monsters-
146 - 2023-03-041043Monsters-Marlies-
147 - 2023-03-051052Monsters-Ice Hogs-
Trade Deadline --- Trades can’t be done after this day is simulated!
149 - 2023-03-071069Griffins-Monsters-
150 - 2023-03-081078Monsters-Heat-
153 - 2023-03-111098Barracuda-Monsters-
156 - 2023-03-141118Monsters-Wheat Kings-
158 - 2023-03-161129Barracuda-Monsters-
160 - 2023-03-181146Monsters-Griffins-
162 - 2023-03-201158Monsters-Bears-
163 - 2023-03-211164Ice Hogs-Monsters-
167 - 2023-03-251190Bruins-Monsters-
171 - 2023-03-291211Marlies-Monsters-
172 - 2023-03-301221Monsters-Heat-
177 - 2023-04-041241Thunderbirds-Monsters-
178 - 2023-04-051251Monsters-Marlies-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price200100
Attendance19,8699,649
Attendance PCT66.23%64.33%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
27 1968 - 65.60% 411,558$6,173,375$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
729,285$ 1,945,000$ 1,945,000$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
10,806$ 647,360$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
11,112,075$ 121 12,194$ 1,475,474$




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