Monkeys

GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
GM : Fred Joanis | Morale : 50 | Team Overall : 61
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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 SP
1Michael Dal Colle (R)X100.00505050505050505050505050505050047490
2Maxime Comtois (R)X100.00505050505050505050505050505050047490
3Filip Zadina (R)X100.00505050505050505050505050505050047490
4Trevor Moore (R)X100.00505050505050505050505050505050047490
5Madison Bowey (R)X100.00857081848081546750696572506969071700
6Henri Jokiharju (R)X100.00826491898084427050796167506669062700
7Cale Fleury (R)X100.00505050505050505050505050505050047490
8Mario Ferraro (R)X100.00505050505050505050505050505050047490
Scratches
1Darren HelmXX100.00756893948580657054697179538480079730
2Pontus Aberg (R)XX100.00745592887880637650737865597070076710
3Mirco Mueller (R)X100.00856293858384586750706475506970079720
4Jakob Chychrun (R)X100.00846989838586607450777066537074068720
5Christian Djoos (R)X100.00686098847579486850716467507068061670
TEAM AVERAGE100.0066587270676753615062596151616206061
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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
Scratches
TEAM AVERAGE0.000000000000000000
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary


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PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
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3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
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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")
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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
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# 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


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PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Player Name Team NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Force Waivers Contract Type Current Salary Salary RemainingSalary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Link
Cale FleuryMonkeys (IDS)D211998-11-19 15:04:50Yes205 Lbs6 ft1NoNoNo2Pro & Farm883,333$883,333$0$0$No883,333$
Christian DjoosMonkeys (IDS)D261994-08-06 06:54:54Yes169 Lbs6 ft0NoNoNo0Pro & Farm0$0$NoLink
Darren HelmMonkeys (IDS)LW/RW331987-01-21 09:26:19No196 Lbs6 ft0NoNoNo0Pro & Farm0$0$NoLink
Filip ZadinaMonkeys (IDS)RW201999-11-27 15:09:35Yes189 Lbs6 ft0NoNoNo3Pro & Farm1,775,000$1,775,000$0$0$No1,775,000$1,775,000$
Henri JokiharjuMonkeys (IDS)D211999-06-17 14:47:01Yes195 Lbs6 ft0NoNoNo2Pro & Farm1,279,167$1,279,167$0$0$No1,279,167$
Jakob ChychrunMonkeys (IDS)D221998-03-31 03:26:19Yes210 Lbs6 ft2NoNoNo0Pro & Farm0$0$NoLink
Madison BoweyMonkeys (IDS)D251995-04-22 07:12:12Yes198 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLink
Mario FerraroMonkeys (IDS)D221998-09-17 15:16:04Yes185 Lbs5 ft11NoNoNo3Pro & Farm1,137,500$1,137,500$0$0$No1,137,500$1,137,500$
Maxime ComtoisMonkeys (IDS)LW211999-01-08 04:18:10Yes215 Lbs6 ft2NoNoNo2Pro & Farm925,000$925,000$0$0$No925,000$
Michael Dal ColleMonkeys (IDS)LW241996-06-20 16:09:19Yes204 Lbs6 ft3NoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$
Mirco MuellerMonkeys (IDS)D251995-03-21 09:26:19Yes210 Lbs6 ft3NoNoNo0Pro & Farm0$0$NoLink
Pontus AbergMonkeys (IDS)LW/RW271993-09-23 07:19:24Yes196 Lbs5 ft11NoNoNo0Pro & Farm0$0$NoLink
Trevor MooreMonkeys (IDS)C251995-03-31 15:23:49Yes185 Lbs5 ft10NoNoNo2Pro & Farm775,000$775,000$0$0$No775,000$
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
1324.00197 Lbs6 ft11.31651,923$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
140122
230122
320122
4Henri Jokiharju10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
140122
2Henri JokiharjuMadison Bowey30122
320122
410122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
160122
240122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
160122
2Henri JokiharjuMadison Bowey40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
160122
240122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
160122
2Henri JokiharjuMadison Bowey40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
16012260122
240122Henri JokiharjuMadison Bowey40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
160122
240122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
160122
2Henri JokiharjuMadison Bowey40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Extra Forwards
Normal PowerPlayPenalty Kill
, , ,
Extra Defensemen
Normal PowerPlayPenalty Kill
, Madison Bowey, Madison Bowey,
Penalty Shots
, , , ,
Goalie
#1 : , #2 :


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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
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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
Arena Capacity20001000
Ticket Price3515
Attendance0.00%0.00%
Attendance PCT0.00%0.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
41 0 - 0.00%0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
0$ 847,500$ 847,500$ 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
Playoff
201940400000923-1420200000416-122020000057-2091827004500162625743019345467910220.00%181044.44%0278531.76%298334.94%226931.88%875796355725
201940400000923-1420200000416-122020000057-2091827004500162625743019345467910220.00%181044.44%0278531.76%298334.94%226931.88%875796355725
Total Playoff808000001846-2840400000832-24404000001014-401836540081000324124114860386909215820420.00%362044.44%05417031.76%5816634.94%4413831.88%1751151927011551