Login

Monsters
GP: 24 | W: 16 | L: 8
GF: 59 | GA: 49 | PP%: 14.47% | PK%: 87.74%
GM : Yvon Poulin | Morale : 50 | Team Overall : N/A
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Game Center
Monsters
16-8-0, 32pts
2
FINAL
1 Sound Tigers
14-7-0, 28pts
Team Stats
W2StreakL2
7-4-0Home Record7-4-0
9-4-0Away Record7-3-0
8-1-1Last 10 Games6-2-2
2.46Goals Per Game2.52
2.04Goals Against Per Game1.86
14.47%Power Play Percentage11.27%
87.74%Penalty Kill Percentage94.66%
Sound Tigers
14-7-0, 28pts
0
FINAL
1 Monsters
16-8-0, 32pts
Team Stats
L2StreakW2
7-4-0Home Record7-4-0
7-3-0Away Record9-4-0
6-2-2Last 10 Games8-1-1
2.52Goals Per Game2.46
1.86Goals Against Per Game2.04
11.27%Power Play Percentage14.47%
94.66%Penalty Kill Percentage87.74%
Team Leaders
Goals
Kevin Stenlund
13
Assists
Mike Reilly
19
Points
Mike Reilly
22
Plus/Minus
Kevin Stenlund
8
Wins
Ilya Sorokin
16
Save Percentage
Ilya Sorokin
0.911

Team Stats
Goals For
59
2.46 GFG
Shots For
466
19.42 Avg
Power Play Percentage
14.5%
23 GF
Offensive Zone Start
39.1%
Goals Against
49
2.04 GAA
Shots Against
553
23.04 Avg
Penalty Kill Percentage
87.7%
19 GA
Defensive Zone Start
41.5%
Team Info

General ManagerYvon Poulin
CoachRick Tocchet
DivisionDivision 2
ConferenceConference 1
CaptainRiley Stillman
Assistant #1Sonny Milano
Assistant #2Rasmus Asplund


Arena Info

Capacity3,000
Attendance0
Season Tickets300


Roster Info

Pro Team29
Farm Team20
Contract Limit49 / 60
Prospects20


Team History

This Season16-8
History45-31-8 (0.536%)
Playoff Appearances0
Playoff Record (W-L)16-8
Stanley Cup0


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
1Jan Jenik (R)0X100.00696285666258585974555860554444615000203902,500$
2Jesse Ylonen (R)0X100.00736983666965666150556263594444625000213925,000$
3Bryce Misley (R)0X100.00777192627149495164504862464444595000213450,000$
4Jack Badini (R)0XX100.00797394637353554556414462424444585000233815,000$
5Kevin Stenlund0XX100.00664391658165737262627160255253635000242925,000$
6Nick Moutrey0X100.00818082658065654961454764454444615000261925,000$
7Pascal Laberge0X100.00726589646554565568456061554444605000232863,333$
8Rasmus Asplund (A)0XXX100.00674296776760716046606679255050615000232925,000$
9Tyler Benson0X100.00737078717073716550676064604444645000232863,333$
10Antoine Morand0X100.00716681676670745467535160514444615000222927,500$
11Connor Dewar0XX100.00716487656568675974565862624444635000222925,000$
12Brendan Guhle0X100.00715880757366635625504869405858595000232888,833$
13Cale Fleury0X100.00876295747762625125424368374747595000222883,333$
14Gabriel Carlsson0X100.00755990787867565425494566255555585000241894,166$
15John Ludvig (R)0X100.00747572637558595725514962474444575000203925,000$
16Riley Stillman (C)0X100.00866683697272666025454885255051605000232900,000$
17Mike Reilly0X100.0076448678727780732569477225626263460X02721,500,000$
Scratches
1Michael McCarron0XX100.00768652658860555872496165255050615000262750,000$
2Sonny Milano (A)0X100.006856798370605564387454624253546149002541,700,000$
3Ryan Jones (R)0X100.00757085687056594825404061384444555000253450,000$
4Donovan Sebrango (R)0X100.007571836771636845253639603744445550001931,150,000$
5Kaedan Korczak (R)0X100.00767479597455584625383961374444545000203905,000$
6Markus Nutivaara0X100.0075449282716860632559486125636460500X02722,700,000$
7Ville Heinola0X100.007365918064545854254846625045455750002021,137,500$
TEAM AVERAGE100.0074648470726263574452516541484860500
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
1Ilya Sorokin (R)100.00746663787870927683749546467250002532,000,000$
2Christopher Gibson100.00615771826564566562613045455950002811,030,555$
Scratches
1Colton Point (R)100.00505366954950505549493044445350002311,097,625$
2Oscar Dansk100.0057637881556153615857304444575000271675,000$
3Jakub Skarek (R)100.0049536781474850544848304444515000212927,500$
TEAM AVERAGE100.005858698359596062605843454558500
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Rick Tocchet84927887817667CAN5821,500,000$


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
1Mike ReillyMonsters (CLB)D243192232001837397277.69%2461125.50268371370220122100.00%000000.7200000021
2Kevin StenlundMonsters (CLB)C/RW24138218140325560233721.67%556723.662682012210131162253.88%70900100.7400000430
3Riley StillmanMonsters (CLB)D2441216530055294914218.16%3158224.29437441250110108000.00%000000.5500000016
4Rasmus AsplundMonsters (CLB)C/LW/RW156612640192032123018.75%533722.473369780002783041.67%2400000.7100000320
5Tyler BensonMonsters (CLB)LW2475122415343449123114.29%147119.6413410541012733055.10%4900000.5100100102
6Brendan GuhleMonsters (CLB)D242911-118040282711157.41%2056523.57246221260000109000.00%000000.3900000002
7Gabriel CarlssonMonsters (CLB)D24291112002621298126.90%2354222.60246231170000100100.00%000000.4100000010
8Connor DewarMonsters (CLB)C/LW244711-1100265827111814.81%044218.4513410120000072260.42%42700000.5000000210
9Jesse YlonenMonsters (CLB)RW2436942355213437406.98%243418.10213141330001240045.16%3100000.4100001021
10Jan JenikMonsters (CLB)C24448010013423091713.33%037615.70000040000342053.46%31800000.4200000001
11Sonny MilanoMonsters (CLB)LW1135848016251461321.43%124121.971342540110401041.86%4300000.6600000200
12Cale FleuryMonsters (CLB)D24156124032611169.09%1840016.68011218000126000.00%000000.3000000002
13Michael McCarronMonsters (CLB)C/RW322423554241250.00%04013.642133150000010100.00%100001.9600100000
14Antoine MorandMonsters (CLB)C24134-31803525211494.76%043017.92022562000000054.02%8700000.1900000000
15John LudvigMonsters (CLB)D24033342036106130.00%1940716.98000111000043000.00%000000.1500000000
16Pascal LabergeMonsters (CLB)C2421301401710861325.00%025310.56000015000090051.28%3900000.2400000110
17Bryce MisleyMonsters (CLB)C24202-1606762133.33%31184.961013221011520047.37%5700000.3400000000
18Jack BadiniMonsters (CLB)C/LW24011-42151675280.00%22048.5201121000010069.23%1300000.1000001000
19Nick MoutreyMonsters (CLB)C24011060023030.00%0512.14011321000040054.55%1100000.3900000000
Team Total or Average41359106165293642047743146314730612.74%154708117.1523426521012443471095416454.67%180900100.4700202131315
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
1Ilya SorokinMonsters (CLB)2416710.9111.88156343495530100.0000240310
Team Total or Average2416710.9111.88156343495530100.0000240310


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 AverageSalary 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
Antoine MorandMonsters (CLB)C221999-02-18No184 Lbs5 ft11NoNoNo2Pro & Farm927,500$927,500$0$0$No927,500$Link
Brendan GuhleMonsters (CLB)D231997-07-29No197 Lbs6 ft2NoNoNo2Pro & Farm888,833$888,833$0$0$No888,833$Link
Bryce MisleyMonsters (CLB)C211999-09-05Yes194 Lbs6 ft1NoNoNo3Pro & Farm450,000$450,000$0$0$No450,000$450,000$
Cale FleuryMonsters (CLB)D221998-11-18No213 Lbs6 ft1NoNoNo2Pro & Farm883,333$883,333$0$0$No883,333$Link
Christopher GibsonMonsters (CLB)G281992-12-27No217 Lbs6 ft2NoNoNo1Pro & Farm1,030,555$1,000,000$0$0$NoLink
Colton PointMonsters (CLB)G231998-03-04Yes230 Lbs6 ft5NoNoNo1Pro & Farm1,097,625$1,000,000$0$0$NoLink
Connor DewarMonsters (CLB)C/LW221999-06-26No182 Lbs5 ft10NoNoNo2Pro & Farm925,000$925,000$0$0$No925,000$Link
Donovan SebrangoMonsters (CLB)D192002-01-12Yes190 Lbs6 ft1NoNoNo3Pro & Farm1,150,000$925,000$0$0$No925,000$925,000$Link
Gabriel CarlssonMonsters (CLB)D241997-01-02No203 Lbs6 ft5NoNoNo1Pro & Farm894,166$894,166$0$0$NoLink
Ilya SorokinMonsters (CLB)G251995-08-03Yes190 Lbs6 ft3NoNoNo3Pro & Farm2,000,000$2,000,000$0$0$No2,000,000$2,000,000$
Jack BadiniMonsters (CLB)C/LW231998-01-19Yes203 Lbs6 ft0NoNoNo3Pro & Farm815,000$805,000$0$0$No815,000$815,000$
Jakub SkarekMonsters (CLB)G211999-11-10Yes202 Lbs6 ft3NoNoNo2Pro & Farm927,500$927,500$0$0$No927,500$Link
Jan JenikMonsters (CLB)C202000-09-15Yes161 Lbs6 ft1NoNoNo3Pro & Farm902,500$795,000$0$0$No902,500$902,500$
Jesse YlonenMonsters (CLB)RW211999-10-03Yes187 Lbs6 ft1NoNoNo3Pro & Farm925,000$880,833$0$0$No925,000$925,000$
John LudvigMonsters (CLB)D202000-08-02Yes205 Lbs6 ft1NoNoNo3Pro & Farm925,000$853,333$0$0$No925,000$925,000$
Kaedan KorczakMonsters (CLB)D202001-01-29Yes192 Lbs6 ft4NoNoNo3Pro & Farm905,000$795,000$0$0$No905,000$905,000$
Kevin StenlundMonsters (CLB)C/RW241996-09-20No215 Lbs6 ft4NoNoNo2Pro & Farm925,000$925,000$0$0$No925,000$Link
Markus NutivaaraMonsters (CLB)D271994-06-06No191 Lbs6 ft1NoYesNo2Pro & Farm2,700,000$2,700,000$0$0$No2,700,000$Link
Michael McCarronMonsters (CLB)C/RW261995-03-07No232 Lbs6 ft6NoNoNo2Pro & Farm750,000$750,000$0$0$No750,000$Link
Mike ReillyMonsters (CLB)D271993-07-13No199 Lbs6 ft1NoYesNo2Pro & Farm1,500,000$1,500,000$0$0$No1,500,000$Link
Nick MoutreyMonsters (CLB)C261995-06-23No218 Lbs6 ft3NoNoNo1Pro & Farm925,000$925,000$0$0$NoLink
Oscar DanskMonsters (CLB)G271994-02-28No204 Lbs6 ft3NoNoNo1Pro & Farm675,000$675,000$0$0$NoLink
Pascal LabergeMonsters (CLB)C231998-04-09No172 Lbs6 ft1NoNoNo2Pro & Farm863,333$863,333$0$0$No863,333$Link
Rasmus AsplundMonsters (CLB)C/LW/RW231997-12-03No189 Lbs5 ft11NoNoNo2Pro & Farm925,000$925,000$0$0$No925,000$Link
Riley StillmanMonsters (CLB)D231998-03-09No196 Lbs6 ft1NoNoNo2Pro & Farm900,000$900,000$0$0$No900,000$Link
Ryan JonesMonsters (CLB)D251996-05-26Yes185 Lbs6 ft2NoNoNo3Pro & Farm450,000$450,000$0$0$No450,000$450,000$
Sonny MilanoMonsters (CLB)LW251996-05-12No194 Lbs6 ft0NoNoNo4Pro & Farm1,700,000$1,700,000$0$0$No1,700,000$1,700,000$1,700,000$Link
Tyler BensonMonsters (CLB)LW231998-03-15No192 Lbs6 ft0NoNoNo2Pro & Farm863,333$863,333$0$0$No863,333$Link
Ville HeinolaMonsters (CLB)D202001-03-02No178 Lbs5 ft11NoNoNo2Pro & Farm1,137,500$1,137,500$0$0$No1,137,500$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2923.21197 Lbs6 ft22.211,033,144$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Rasmus AsplundKevin StenlundJesse Ylonen35122
2Connor DewarAntoine Morand30122
3Tyler BensonJan JenikPascal Laberge25122
4Jack BadiniAntoine MorandKevin Stenlund10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Mike ReillyRiley Stillman35122
2Brendan GuhleGabriel Carlsson30122
3Cale FleuryJohn Ludvig25122
4Mike ReillyRiley Stillman10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Rasmus AsplundKevin StenlundJesse Ylonen60122
2Connor DewarAntoine Morand40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Mike ReillyRiley Stillman60122
2Brendan GuhleGabriel Carlsson40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Kevin StenlundRasmus Asplund60122
2Tyler Benson40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Mike ReillyRiley Stillman60122
2Brendan GuhleGabriel Carlsson40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Kevin Stenlund60122Mike ReillyRiley Stillman60122
2Rasmus Asplund40122Brendan GuhleGabriel Carlsson40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Kevin StenlundRasmus Asplund60122
2Tyler Benson40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Mike ReillyRiley Stillman60122
2Brendan GuhleGabriel Carlsson40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Rasmus AsplundKevin StenlundJesse YlonenMike ReillyRiley Stillman
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Rasmus AsplundKevin StenlundJesse YlonenMike ReillyRiley Stillman
Extra Forwards
Normal PowerPlayPenalty Kill
Bryce Misley, Nick Moutrey, Jan JenikBryce Misley, Nick MoutreyJan Jenik
Extra Defensemen
Normal PowerPlayPenalty Kill
Cale Fleury, John Ludvig, Brendan GuhleCale FleuryJohn Ludvig, Brendan Guhle
Penalty Shots
Kevin Stenlund, Rasmus Asplund, , Tyler Benson, Jesse Ylonen
Goalie
#1 : Ilya Sorokin, #2 : Christopher Gibson


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
1Bruins743000001719-23210000067-1422000001112-180.57117314800201519513313515813736190619715138615.79%44490.91%041872058.06%39276551.24%19535754.62%619417626193318160
2Crunch743000002316731200000752431000001611580.5712343660120151951591351581373616841136117491122.45%48785.42%141872058.06%39276551.24%19535754.62%619417626193318160
3Penguins44000000954220000005322200000042281.0009162501201519563135158137367925488027311.11%23386.96%041872058.06%39276551.24%19535754.62%619417626193318160
4Sound Tigers642000001091321000004313210000066080.6671016260120151951111351581373611630871304536.67%40587.50%241872058.06%39276551.24%19535754.62%619417626193318160
Total24168000005949101174000002218413940000037316320.66759106165032015195466135158137365531573684781592314.47%1551987.74%341872058.06%39276551.24%19535754.62%619417626193318160
_Since Last GM Reset24168000005949101174000002218413940000037316320.66759106165032015195466135158137365531573684781592314.47%1551987.74%341872058.06%39276551.24%19535754.62%619417626193318160
_Vs Conference181260000049409853000001815310730000031256240.6674990139022015195355135158137364371272813481142017.54%1151487.83%141872058.06%39276551.24%19535754.62%619417626193318160
_Vs Division104000000191455200000096352000000108280.40019325102201519517413515813736195551352107268.33%63887.30%241872058.06%39276551.24%19535754.62%619417626193318160

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
2432W25910616546655315736847803
All Games
GPWLOTWOTL SOWSOLGFGA
2416800005949
Home Games
GPWLOTWOTL SOWSOLGFGA
117400002218
Visitor Games
GPWLOTWOTL SOWSOLGFGA
139400003731
Last 10 Games
WLOTWOTL SOWSOL
810100
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1592314.47%1551987.74%3
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
135158137362015195
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
41872058.06%39276551.24%19535754.62%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
619417626193318160


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 - 2022-03-164Monsters6Crunch2AWBoxScore
2 - 2022-03-1712Monsters4Crunch3AWBoxScore
3 - 2022-03-1820Crunch0Monsters4BWBoxScore
4 - 2022-03-1928Crunch1Monsters0BLBoxScore
5 - 2022-03-2036Monsters1Crunch3ALBoxScore
6 - 2022-03-2144Crunch4Monsters3BLBoxScore
7 - 2022-03-2252Monsters5Crunch3AWBoxScore
8 - 2022-03-2357Monsters3Bruins4ALBoxScore
9 - 2022-03-2461Monsters3Bruins2AWBoxScore
10 - 2022-03-2565Bruins3Monsters0BLBoxScore
11 - 2022-03-2669Bruins2Monsters3BWBoxScore
12 - 2022-03-2773Monsters0Bruins4ALBoxScore
13 - 2022-03-2877Bruins2Monsters3BWXBoxScore
14 - 2022-03-2981Monsters5Bruins2AWBoxScore
15 - 2022-03-3085Monsters1Penguins0AWBoxScore
16 - 2022-03-3187Monsters3Penguins2AWXBoxScore
17 - 2022-04-0189Penguins2Monsters3BWXBoxScore
18 - 2022-04-0291Penguins1Monsters2BWBoxScore
22 - 2022-04-0699Monsters1Sound Tigers3ALBoxScore
23 - 2022-04-07100Monsters3Sound Tigers2AWXBoxScore
24 - 2022-04-08101Sound Tigers2Monsters3BWXBoxScore
25 - 2022-04-09102Sound Tigers1Monsters0BLXBoxScore
26 - 2022-04-10103Monsters2Sound Tigers1AWBoxScore
27 - 2022-04-11104Sound Tigers0Monsters1BWBoxScore



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

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
-11 0 - 0.00% 0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
0$ 2,996,116$ 2,926,465$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 0$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 0$ 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
1Riley Stillman82183250-51431898412814.06%86176721.551416301060112620.00%00.5700
2Kevin Stenlund70242448938706712918.60%5145020.7269154410156251.75%00.6649
3Rasmus Asplund53133043518451099713.40%7114921.68514192710175046.27%00.7519
4Mike Reilly7673239-570116101917.69%58182324.0041014780110030.00%00.4300
5Sonny Milano6892938-103883948910.11%10135619.94513182400053237.84%00.5613

Monsters Goalies Stat Leaders (Regular Season)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1Ilya Sorokin80442960.8922.17475361017215920410.78642
2Christopher Gibson71200.8892.12227018720000.0000

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
Regular Season
20218235310317519218664120150004298926411516031339494096192335527110745157131497500476501601665462119815934697014.93%5095689.00%41213228253.16%1210239350.56%605117251.62%2044139619146111027525
Total Regular Season8235310317519218664120150004298926411516031339494096192335527110745157131497500476501601665462119815934697014.93%5095689.00%41213228253.16%1210239350.56%605117251.62%2044139619146111027525
2021241680000059491011740000022184139400000373163259106165032015195466135158137365531573684781592314.47%1551987.74%341872058.06%39276551.24%19535754.62%619417626193318160
Total Playoff241680000059491011740000022184139400000373163259106165032015195466135158137365531573684781592314.47%1551987.74%341872058.06%39276551.24%19535754.62%619417626193318160

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
1Mike Reilly24319223201837397.69%2461125.50268370220100.00%00.7200
2Kevin Stenlund241382181432556021.67%556723.662682010132253.88%00.7400
3Riley Stillman24412165305529498.16%3158224.29437440110000.00%00.5500
4Tyler Benson24751224134344914.29%147119.641341010123055.10%00.5100
5Rasmus Asplund1566126419203218.75%533722.47336900023041.67%00.7100

Monsters Goalies Stat Leaders (Play-Off)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1Ilya Sorokin2416710.9111.88156343495530100.0000