Monsters
GP: 0 | W: 0 | L: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
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.

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
1Charles HudonXX100.00824499746659646433575854755959625000263650,000$
2Eric Cornel (R)XX100.00797296647279865670475866555151625000243925,000$
3Nicolas RoyX100.00794590687859826272647163254747694600231815,000$
4Kevin Stenlund (R)XX100.00674391658066817554617161254747694900233925,000$
5Nick Moutrey (R)X100.00818082658069744961464764454444565000252925,000$
6Pascal Laberge (R)X100.00706582646552515670466160584444595000223863,333$
7Rasmus Asplund (R)XXX100.00694292686457866155575685254646655000223925,000$
8Tyler Benson (R)X100.00737079717075786350665763544444645000223863,333$
9Paul Bittner (R)X100.00808079688066705150475164484444575000233863,333$
10Michael McCarronXX100.007888536588616259745062665949496150002511,075,833$
11Sonny MilanoXX100.006542868373646366257464592552536750002411,263,333$
12Connor Dewar (R)XX100.00706387656369735468535060484444575000213925,000$
13Brendan GuhleX100.00694289756971755725505474255858635000223946,083$
14Cale Fleury (R)X100.00904694777464735325394769254747595000213883,333$
15Gabriel CarlssonX100.00797589787569755025424165395252565000232894,166$
16Markus NutivaaraX100.0073439682716876622552495925626360500X02632,700,000$
17Slater KoekkoekX100.00804472767270596325554780255758625000261800,000$
18Ben HuttonX100.007143928176758463255348792567676445002731,725,002$
19Mike ReillyX100.0073438478737568732566476725606063500X02631,500,000$
Scratches
1Antoine Morand (R)X100.00716683676670755063494759454444554500213927,500$
2Ryan Collins (R)X100.00828184528155574825384264404444535000243925,000$
3Ville Heinola (R)X100.007666998066505050254739623744445350001931,137,500$
TEAM AVERAGE100.0075588671736671584453536639505061490
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 SP
1Calvin Pickard100.0054587377535852585756305757564900
2Oscar Dansk100.0060688579586556646160304444615100
Scratches
1Jakub Skarek (R)100.0049526579474850544848304444505000
TEAM AVERAGE100.005459747853575359555530484856500
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Rick Tocchet84927887817667CAN5731,500,000$


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
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


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)C211999-02-18Yes185 Lbs5 ft10NoNoNo3Pro & Farm927,500$927,500$0$0$No927,500$927,500$
Ben HuttonMonsters (CLB)D271993-04-20No207 Lbs6 ft2NoNoNo3Pro & Farm1,725,002$1,500,000$0$0$No1,500,000$1,500,000$Link
Brendan GuhleMonsters (CLB)D221997-07-29No186 Lbs6 ft1NoNoNo3Pro & Farm946,083$888,833$0$0$No888,833$888,833$Link
Cale FleuryMonsters (CLB)D211998-11-19Yes203 Lbs6 ft1NoNoNo3Pro & Farm883,333$883,333$0$0$No883,333$883,333$
Calvin PickardMonsters (CLB)G281992-04-14No207 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLink
Charles HudonMonsters (CLB)LW/RW261994-06-23No188 Lbs5 ft10NoNoNo3Pro & Farm650,000$725,000$0$0$No650,000$650,000$Link
Connor DewarMonsters (CLB)C/LW211999-06-26Yes176 Lbs5 ft10NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$
Eric CornelMonsters (CLB)C/RW241996-04-11Yes194 Lbs6 ft2NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$
Gabriel CarlssonMonsters (CLB)D231997-01-02No192 Lbs6 ft5NoNoNo2Pro & Farm894,166$894,166$0$0$No894,166$Link
Jakub SkarekMonsters (CLB)G201999-11-10Yes196 Lbs6 ft3NoNoNo3Pro & Farm927,500$927,500$0$0$No927,500$927,500$
Kevin StenlundMonsters (CLB)C/RW231996-09-20Yes210 Lbs6 ft4NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$
Markus NutivaaraMonsters (CLB)D261994-06-06No191 Lbs6 ft1NoYesNo3Pro & Farm2,700,000$2,700,000$0$0$No2,700,000$2,700,000$Link
Michael McCarronMonsters (CLB)C/RW251995-03-06No231 Lbs6 ft6NoNoNo1Pro & Farm1,075,833$1,075,833$0$0$NoLink
Mike ReillyMonsters (CLB)D261993-07-12No195 Lbs6 ft2NoYesNo3Pro & Farm1,500,000$1,500,000$0$0$No1,500,000$1,500,000$Link
Nick MoutreyMonsters (CLB)C251995-06-23Yes218 Lbs6 ft3NoNoNo2Pro & Farm925,000$925,000$0$0$No925,000$
Nicolas RoyMonsters (CLB)C231997-02-05No208 Lbs6 ft4NoNoNo1Pro & Farm815,000$815,000$0$0$NoLink
Oscar DanskMonsters (CLB)G261994-02-28No195 Lbs6 ft3NoNoNo2Pro & Farm675,000$675,000$0$0$No675,000$Link
Pascal LabergeMonsters (CLB)C221998-04-08Yes173 Lbs6 ft1NoNoNo3Pro & Farm863,333$863,333$0$0$No863,333$863,333$
Paul BittnerMonsters (CLB)LW231996-11-03Yes214 Lbs6 ft4NoNoNo3Pro & Farm863,333$863,333$0$0$No863,333$863,333$
Rasmus AsplundMonsters (CLB)C/LW/RW221997-12-02Yes176 Lbs5 ft11NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$
Ryan CollinsMonsters (CLB)D241996-05-06Yes212 Lbs6 ft5NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$
Slater KoekkoekMonsters (CLB)D261994-02-18No193 Lbs6 ft2NoNoNo1Pro & Farm800,000$800,000$0$0$NoLink
Sonny MilanoMonsters (CLB)LW/RW241996-05-11No195 Lbs6 ft2NoNoNo1Pro & Farm1,263,333$1,263,333$0$0$NoLink
Tyler BensonMonsters (CLB)LW221998-03-15Yes192 Lbs6 ft0NoNoNo3Pro & Farm863,333$863,333$0$0$No863,333$863,333$
Ville HeinolaMonsters (CLB)D192001-03-02Yes181 Lbs5 ft11NoNoNo3Pro & Farm1,137,500$1,137,500$0$0$No1,137,500$1,137,500$
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2523.56197 Lbs6 ft22.481,042,410$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Sonny MilanoNicolas RoyKevin Stenlund35122
2Charles HudonRasmus AsplundMichael McCarron30122
3Tyler BensonEric CornelPaul Bittner25122
4Paul BittnerPascal LabergeSonny Milano10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Mike ReillyBen Hutton35122
2Markus NutivaaraSlater Koekkoek30122
3Brendan GuhleCale Fleury25122
4Gabriel CarlssonMike Reilly10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Sonny MilanoNicolas RoyKevin Stenlund60122
2Charles HudonRasmus AsplundMichael McCarron40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Mike ReillyBen Hutton60122
2Markus NutivaaraSlater Koekkoek40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Sonny MilanoNicolas Roy60122
2Kevin StenlundCharles Hudon40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Mike ReillyBen Hutton60122
2Markus NutivaaraSlater Koekkoek40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Sonny Milano60122Mike ReillyBen Hutton60122
2Nicolas Roy40122Markus NutivaaraSlater Koekkoek40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Sonny MilanoNicolas Roy60122
2Kevin StenlundCharles Hudon40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Mike ReillyBen Hutton60122
2Markus NutivaaraSlater Koekkoek40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Sonny MilanoNicolas RoyKevin StenlundMike ReillyBen Hutton
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Sonny MilanoNicolas RoyKevin StenlundMike ReillyBen Hutton
Extra Forwards
Normal PowerPlayPenalty Kill
Nick Moutrey, Connor Dewar, Tyler BensonNick Moutrey, Connor DewarTyler Benson
Extra Defensemen
Normal PowerPlayPenalty Kill
Brendan Guhle, Cale Fleury, Gabriel CarlssonBrendan GuhleCale Fleury, Gabriel Carlsson
Penalty Shots
Sonny Milano, Nicolas Roy, Kevin Stenlund, Charles Hudon, Rasmus Asplund
Goalie
#1 : Oscar Dansk, #2 : Calvin Pickard


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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
00N/A0000000000
All Games
GPWLOTWOTL SOWSOLGFGA
000000000
Home Games
GPWLOTWOTL SOWSOLGFGA
000000000
Visitor Games
GPWLOTWOTL SOWSOLGFGA
000000000
Last 10 Games
WLOTWOTL SOWSOL
000000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
000.00%000.00%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
00000000
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
000.00%000.00%000.00%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
000000


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



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3515
Attendance0.00%0.00%
Attendance PCT0.00%0.00%

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

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
0$ 2,606,023$ 2,585,298$ 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$




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
202082254600065161204-4341181600052998910417300001362115-536716127443517625241161295427421435551526439114514834624910.61%4826885.89%61092211551.63%1038219547.29%591113851.93%2018137619416061015522
Total Regular Season82254600065161204-4341181600052998910417300001362115-536716127443517625241161295427421435551526439114514834624910.61%4826885.89%61092211551.63%1038219547.29%591113851.93%2018137619416061015522