Bears

GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
GM : Mathieu Girard | Morale : 50 | Team Overall : 62
Next Games #17 vs Senators

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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.
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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 SP
1Nick Ritchie0X100.009072776691828567576668556571697150660
2Gage Quinney0XX100.006337916672917963696664626568703650650
3Joe Snively0X100.005635916365817765776667616468693750640
4Tim Gettinger0XX100.008363806097817962636158656065675450640
5Anton Blidh0XX100.008040736277797863576259646068704150630
6Reese Johnson0XX100.009047836076777959816058705864664250630
7Cooper Marody0X100.006037756571807864726760596367694250630
8Mavrik Bourque0X100.005736926766857268706361576961637850620
9Curtis Douglas0X100.009083595699788455655657635663656050620
10Hendrix Lapierre0X100.006038786670807164655662586561638250610
11Jimmy Huntington0X100.006640756075738159696257586165674250610
12Brett Sutter0X100.006540795774798556595758565776782450600
13Paul Thompson0X100.006846595777767756575559545875772350590
14Maxim Marushev0X100.006437915873768259625655575564664850590
15James Greenway0X100.008650575395676652575350594965676350580
16Kirill Tyutyayev0X100.005936945667686654575553525863654950560
17Ben Harpur0X100.008653736299807559306558644968705050670
18Thomas Harley0X100.007139846784818566306459615062648350660
19Brandt Clarke0X100.006538826777826164306558625060628950630
20Ilya Solovyov0X100.007641835485668253305553584663654950610
21Luke Martin0X100.007540815584706554305752584665676950600
Scratches
1Ben Meyers0X100.006137916371807362806460616365674250620
2Navrin Mutter0X100.007244655381656952585354565362644350560
TEAM AVERAGE100.00714579617977766058605860576667535062
Filter Tips
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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
1Erik Kallgren100.00757976837473757473757467775450730
Scratches
TEAM AVERAGE100.0075797683747375747375746777545073
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Jay Leach65656966666182USA4491,000,000$


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 StatusType Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Link
Anton BlidhLW/RW281995-03-14No197 Lbs6 ft1NoNoNo4UFAPro & Farm300,000$0$0$NoLink / NHL Link
Ben HarpurD281995-01-12No231 Lbs6 ft6NoNoNo2UFAPro & Farm500,000$0$0$NoLink / NHL Link
Ben MeyersC241998-11-15No194 Lbs5 ft11NoNoNo2RFAPro & Farm300,000$0$0$NoLink
Brandt ClarkeD202003-02-09No185 Lbs6 ft2NoNoNo4ELCPro & Farm900,000$0$0$NoLink
Brett SutterLW361987-06-02No200 Lbs6 ft0NoNoNo1UFAPro & Farm300,000$0$0$NoLink / NHL Link
Cooper MarodyC261996-12-20No184 Lbs6 ft0NoNoNo3RFAPro & Farm300,000$0$0$NoLink / NHL Link
Curtis DouglasC232000-03-06No235 Lbs6 ft9NoNoNo2RFAPro & Farm300,000$0$0$NoLink
Erik KallgrenG261996-10-14No200 Lbs6 ft3NoNoNo3RFAPro & Farm500,000$0$0$NoLink / NHL Link
Gage QuinneyC/LW281995-07-29No200 Lbs5 ft11NoNoNo3UFAPro & Farm300,000$0$0$NoLink / NHL Link
Hendrix LapierreC212002-02-09No180 Lbs6 ft0NoNoNo4ELCPro & Farm900,000$0$0$NoLink
Ilya SolovyovD232000-07-20No208 Lbs6 ft3NoNoNo3RFAPro & Farm300,000$0$0$NoLink
James GreenwayLW251998-04-27No211 Lbs6 ft6NoNoNo2RFAPro & Farm300,000$0$0$NoLink
Jimmy HuntingtonC241998-11-18No204 Lbs6 ft0NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Joe SnivelyC271996-01-01No176 Lbs5 ft9NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Kirill TyutyayevLW232000-08-08No176 Lbs5 ft11NoNoNo4RFAPro & Farm300,000$0$0$NoLink
Luke MartinD251998-09-20No219 Lbs6 ft2NoNoNo4RFAPro & Farm300,000$0$0$NoLink
Mavrik BourqueC212002-01-08No178 Lbs5 ft10NoNoNo4ELCPro & Farm900,000$0$0$NoLink
Maxim MarushevC241999-01-01No176 Lbs6 ft1NoNoNo3RFAPro & Farm300,000$0$0$NoLink
Navrin MutterLW222001-03-15No190 Lbs6 ft3NoNoNo2ELCPro & Farm300,000$0$0$NoLink
Nick RitchieLW271995-12-05No236 Lbs6 ft3NoNoNo2RFAPro & Farm850,000$0$0$NoLink / NHL Link
Paul ThompsonRW341988-11-30No200 Lbs6 ft1NoNoNo2UFAPro & Farm300,000$0$0$NoLink / NHL Link
Reese JohnsonC/RW251998-07-10No193 Lbs6 ft1NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Thomas HarleyD222001-08-19No205 Lbs6 ft3NoNoNo3ELCPro & Farm900,000$0$0$NoLink
Tim GettingerLW/RW251998-04-14No220 Lbs6 ft6NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2425.29200 Lbs6 ft22.63439,583$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
140122
230122
320122
410122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
140122
230122
320122
410122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
160122
240122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
160122
240122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
160122
240122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
160122
240122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
16012260122
24012240122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
160122
240122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
160122
240122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Extra Forwards
Normal PowerPlayPenalty Kill
, , Joe Snively, Joe Snively
Extra Defensemen
Normal PowerPlayPenalty Kill
, , ,
Penalty Shots
, , , ,
Goalie
#1 : , #2 :


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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

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
5 - 2023-08-1417Senators-Bears-
6 - 2023-08-1529Monsters-Bears-
11 - 2023-08-2037Bears-Bruins-
12 - 2023-08-2153Bears-Bruins-
13 - 2023-08-2259Bears-Islanders-
16 - 2023-08-2568Bears-Penguins-
19 - 2023-08-2888Phantoms-Bears-
20 - 2023-08-2999Penguins-Bears-
25 - 2023-09-03117Bears-Penguins-
26 - 2023-09-04126Islanders-Bears-
33 - 2023-09-11166Bears-Phantoms-
34 - 2023-09-12174Phantoms-Bears-
37 - 2023-09-15187Bears-Penguins-
39 - 2023-09-17192Islanders-Bears-
40 - 2023-09-18208Bears-Islanders-
44 - 2023-09-22230Penguins-Bears-
47 - 2023-09-25255Wild-Bears-
48 - 2023-09-26264Wild-Bears-
51 - 2023-09-29272Bears-Penguins-
53 - 2023-10-01277Bears-Checkers-
54 - 2023-10-02291Bears-Checkers-
60 - 2023-10-08315Bears-Crunch-
61 - 2023-10-09332Monsters-Bears-
62 - 2023-10-10347Checkers-Bears-
65 - 2023-10-13350Bruins-Bears-
68 - 2023-10-16372Rocket-Bears-
69 - 2023-10-17385Thunderbirds-Bears-
74 - 2023-10-22407Bears-Thunderbirds-
75 - 2023-10-23416Bruins-Bears-
79 - 2023-10-27427Penguins-Bears-
81 - 2023-10-29444Bears-Americans-
82 - 2023-10-30457Bears-Phantoms-
86 - 2023-11-03472Checkers-Bears-
89 - 2023-11-06491Wolfpack-Bears-
90 - 2023-11-07503Phantoms-Bears-
96 - 2023-11-13538Bears-Phantoms-
98 - 2023-11-15549Bears-Islanders-
102 - 2023-11-19564Bears-Wolfpack-
103 - 2023-11-20578Penguins-Bears-
107 - 2023-11-24598Thunderbirds-Bears-
110 - 2023-11-27623Bears-Penguins-
111 - 2023-11-28640Marlies-Bears-
114 - 2023-12-01647Bears-Phantoms-
116 - 2023-12-03659Bears-Phantoms-
117 - 2023-12-04673Islanders-Bears-
123 - 2023-12-10689Bears-Bruins-
124 - 2023-12-11705Bears-Thunderbirds-
128 - 2023-12-15718Phantoms-Bears-
131 - 2023-12-18735Bears-Marlies-
133 - 2023-12-20756Bears-Senators-
135 - 2023-12-22762Bears-Rocket-
137 - 2023-12-24770Penguins-Bears-
138 - 2023-12-25787Americans-Bears-
145 - 2024-01-01833Comets-Bears-
146 - 2024-01-02844Bears-Phantoms-
151 - 2024-01-07858Bears-Checkers-
152 - 2024-01-08870Bears-Checkers-
Trade Deadline --- Trades can’t be done after this day is simulated!
158 - 2024-01-14906Bears-Comets-
159 - 2024-01-15918Crunch-Bears-
160 - 2024-01-16933Wolfpack-Bears-
164 - 2024-01-20950Bears-Monsters-
166 - 2024-01-22964Bears-Monsters-
169 - 2024-01-25983Bruins-Bears-
173 - 2024-01-291011Bears-Wolfpack-
176 - 2024-02-011023Phantoms-Bears-
179 - 2024-02-041042Bears-Wild-
180 - 2024-02-051051Bears-Wild-
186 - 2024-02-111077Phantoms-Bears-
187 - 2024-02-121092Bears-Penguins-
188 - 2024-02-131106Penguins-Bears-
191 - 2024-02-161110Checkers-Bears-
194 - 2024-02-191132Checkers-Bears-



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
36 0 - 0.00%0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
0$ 105,500$ 0$ 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$ 195 5,669$ 1,105,455$




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
128244230264327817610241211302212132874541231000431146895710927844672401001089173249308288028382069556112116574988817.67%4336784.53%81425253856.15%1282250451.20%636118253.81%223416731832545909462
128244230264327817610241211302212132874541231000431146895710927844672401001089173249308288028382069556112116574988817.67%4336784.53%81425253856.15%1282250451.20%636118253.81%223416731832545909462
13763924026142021515138201401201936924381910014131098227942023585600100747352196906326966251707551133014994587416.16%5326787.41%31341237956.37%1162235149.43%613106857.40%191213291783553907461
13763924026142021515138201401201936924381910014131098227942023585600100747352196906326966251707551133014994587416.16%5326787.41%31341237956.37%1162235149.43%613106857.40%191213291783553907461
1476332505544199155443813120343310180213820130211198752393199319518114072615721100685715681211162389212673585515.36%3373988.43%11110227348.83%1093253543.12%508101250.20%181213201943525863412
1476332505544199155443813120343310180213820130211198752393199319518114072615721100685715681211162389212673585515.36%3373988.43%11110227348.83%1093253543.12%508101250.20%181213201943525863412
158240310223425219557411819011111271002741221201123125953096252460712390979258245707828538042181647104415764257417.41%4336884.30%41223257847.44%1029254640.42%549121545.19%208415081922559955482
158240310223425219557411819011111271002741221201123125953096252460712390979258245707828538042181647104415764257417.41%4336884.30%41223257847.44%1029254640.42%549121545.19%208415081922559955482
1682165701314249395-1464192800112127198-714172901202122197-75432494086572001007968245407928458002766832106317193825614.66%44913170.82%4907247736.62%852235336.21%532135439.29%183413152227556891418
1682165701314249395-1464192800112127198-714172901202122197-75432494086572001007968245407928458002766832106317193825614.66%44913170.82%4907247736.62%852235336.21%532135439.29%183413152227556891418
1772175201002216360-14436102500001115175-603672701001101185-84382163615771008779492403073582583627447737551491294279.18%3257576.92%1803214837.38%749221333.85%440121036.36%147210562077492782340
1772175201002216360-14436102500001115175-603672701001101185-84382163615771008779492403073582583627447737551491294279.18%3257576.92%1803214837.38%749221333.85%440121036.36%147210562077492782340
Total Regular Season94037842402644264227922864-7247018222201420122013901418-2847019620201224142214021446-449462792470474961486010769507142777208908947291682715679641241018418483074815.49%501889482.18%42136182878647.31%123342900442.53%65561408246.56%2270116407235726464106205156
Playoff
1240400000313-102020000035-22020000008-803580001204901513211112956852129.52%27485.19%0478952.81%6915245.39%325162.75%8860107304723
1240400000313-102020000035-22020000008-803580001204901513211112956852129.52%27485.19%0478952.81%6915245.39%325162.75%8860107304723
Total Playoff80800000626-2040400000610-440400000016-16061016000240980302642222581121704249.52%54885.19%09417852.81%13830445.39%6410262.75%177120214619446