Bears

GP: 38 | W: 20 | L: 13 | OTL: 5 | P: 45
GF: 96 | GA: 76 | PP%: 18.18% | PK%: 86.35%
GM : Mathieu Girard | Morale : 50 | Team Overall : 60
Next Games #590 vs Phantoms
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 SP
1Kyle CliffordX98.00955565759985727050646672557174159690
2Tanner GlassX98.00895559678179636350606064558476157640
3Jason DickinsonXX98.00635571707167676480626063555050159610
4Anton BlidhX100.00565565757871545650555660556573150590
5Anthony CamaraX100.00755565637867595550555555557274157580
6Rich CluneX100.00565558627568685550555556555959160570
7Dennis Yan (R)X100.00565555555657575550555555557575157550
8Brett SutterX100.00565555555758585550555555557475157550
9Reid Duke (R)X100.00565555555555555550555555555050157530
10Andrei Mironov (R)X100.00725561815769576625626265556462157630
11Trevor MurphyX100.00645570655875676525616164555353156610
12Sami Niku (R)X100.00615568755677556125606260556262157610
13Kyle Wood (R)X100.00595559615959795925595959557272159590
14Simon DespresX100.00555555605555555525555555557774157560
15Michael Kapla (R)X100.00555555605555695525555555555555139540
Scratches
1Paul ThompsonX100.00845569626866606050606060555050141580
TEAM AVERAGE99.6366556265666662594358586055656515559
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
1Vitek Vanecek100.0064788474666670677070556867159680
2Kristers Gudlevskis100.0060788379646463666862555969137650
Scratches
TEAM AVERAGE100.006278847765656767696655646814867
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Bob Hartley61626269885656CAN5756,300,000$


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 NamePOS GP 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
1Kyle CliffordBears (Was)LW3817203771200153103138499812.32%1796925.51512173817710181905154.99%49100020.7602000821
2Klas DahlbeckWashington CapitalsD268233111495663074284110.81%4555721.468917591170002119110.00%000001.1100001323
3Jason DickinsonBears (Was)C/LW3872128812015799232877.61%1182921.82113142817700031481061.96%72300000.6811000030
4Tanner GlassBears (Was)LW2691221644093509428559.57%864424.792793211500051470149.63%13500010.6501000403
5Trevor MurphyBears (Was)D3851520553564425715518.77%4771918.93358381290002137100.00%000000.5600010022
6Andrei MironovBears (Was)D26713201460703961264511.48%3156521.746713541300110144110.00%000000.7100000024
7Kyle WoodBears (Was)D38512171242045223551514.29%3454314.304262576000165210.00%000000.6300000010
8Paul ThompsonBears (Was)RW3567136315292351115011.76%543812.5223518103000001134.62%2600000.5901010001
9Rich CluneBears (Was)LW38391257582125132812.00%63759.8813441900001041146.07%8900000.6401001111
10Brett SutterBears (Was)C2665113003322791822.22%144417.0820271180000173050.00%48000000.5000000012
11Anton BlidhBears (Was)LW252810-345553436725452.99%342216.8906615600000410063.16%1900000.4700001001
12Sami NikuBears (Was)D264595355352137122110.81%1844817.262352481000281100.00%000000.4000000020
13Anthony CamaraBears (Was)LW26224514010252022010.00%228510.980110110001540051.90%7900000.2800000000
14Simon DespresBears (Was)D26134342028642125.00%152569.8600005000033000.00%000000.3100000000
15Reid DukeBears (Was)C26213-110052582525.00%027810.7100002000011049.57%23400000.2200000001
16Michael KaplaBears (Was)D26022-21601972020.00%131917.3700003000028000.00%000000.2101000000
17Dennis YanBears (Was)LW260004120854060.00%31465.630002300000150048.57%3500000.0000000000
Team Total or Average51084158242755783070457379625958810.55%259811615.913671107344136111224133218754.57%231100030.6017023161619
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
1Juuse SarosWashington Capitals34171250.9151.97201246667770300.6679340314
2Kristers GudlevskisBears (Was)64200.9141.9736521121390101.0003613101
3Vitek VanecekBears (Was)63100.9211.692842081010000.0000434100
Team Total or Average46241550.9151.942662878610170400.750124447515


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
Andrei MironovBears (Was)D221994-07-29Yes198 Lbs6 ft2NoNoNo4ELCPro & Farm300,000$0$0$No
Anthony CamaraBears (Was)LW231993-09-03No192 Lbs6 ft0NoNoNo1RFAPro & Farm300,000$0$0$No
Anton BlidhBears (Was)LW211995-03-14No201 Lbs6 ft0NoNoNo2ELCPro & Farm300,000$0$0$No
Brett SutterBears (Was)C291987-06-01No201 Lbs6 ft0NoNoNo3UFAPro & Farm300,000$0$0$No
Dennis YanBears (Was)LW191997-04-14Yes183 Lbs6 ft1NoNoNo4ELCPro & Farm500,000$0$0$No
Jason DickinsonBears (Was)C/LW211995-07-04No185 Lbs6 ft1NoNoNo2ELCPro & Farm900,000$0$0$No
Kristers GudlevskisBears (Was)G241992-07-31No190 Lbs6 ft4NoNoNo1RFAPro & Farm500,000$0$0$No
Kyle CliffordBears (Was)LW261991-01-13No211 Lbs6 ft2NoNoNo2RFAPro & Farm300,000$0$0$No
Kyle WoodBears (Was)D201996-05-04Yes210 Lbs6 ft5NoNoNo3ELCPro & Farm500,000$0$0$No
Michael KaplaBears (Was)D221994-09-19Yes201 Lbs6 ft0NoNoNo4ELCPro & Farm300,000$0$0$No
Paul ThompsonBears (Was)RW281988-11-29No198 Lbs5 ft11NoNoNo1UFAPro & Farm300,000$0$0$No
Reid DukeBears (Was)C201996-01-28Yes192 Lbs6 ft0NoNoNo4ELCPro & Farm300,000$0$0$No
Rich CluneBears (Was)LW291987-04-24No207 Lbs5 ft10NoNoNo1UFAPro & Farm300,000$0$0$No
Sami NikuBears (Was)D201996-10-10Yes179 Lbs6 ft0NoNoNo4ELCPro & Farm300,000$0$0$No
Simon DespresBears (Was)D251991-07-26No214 Lbs6 ft4NoNoNo3RFAPro & Farm300,000$0$0$No
Tanner GlassBears (Was)LW331983-11-28No210 Lbs6 ft1NoNoNo2UFAPro & Farm300,000$0$0$No
Trevor MurphyBears (Was)D211995-07-16No172 Lbs5 ft10NoNoNo2ELCPro & Farm300,000$0$0$No
Vitek VanecekBears (Was)G211996-01-09No180 Lbs6 ft1NoNoNo3ELCPro & Farm500,000$0$0$No
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
1823.56196 Lbs6 ft12.56377,778$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Kyle CliffordJason Dickinson40122
2Tanner GlassBrett Sutter30122
3Anton BlidhReid DukeKyle Clifford20122
4Anthony CamaraTanner GlassJason Dickinson10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Andrei MironovTrevor Murphy40122
2Sami NikuKyle Wood30122
3Simon DespresMichael Kapla20122
4Andrei MironovTrevor Murphy10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Kyle CliffordJason Dickinson60122
2Tanner GlassBrett Sutter40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Andrei MironovTrevor Murphy60122
2Sami NikuKyle Wood40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Kyle CliffordTanner Glass60122
2Jason DickinsonAnton Blidh40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Andrei MironovTrevor Murphy60122
2Sami NikuKyle Wood40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Kyle Clifford60122Andrei MironovTrevor Murphy60122
2Tanner Glass40122Sami NikuKyle Wood40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Kyle CliffordTanner Glass60122
2Jason DickinsonAnton Blidh40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Andrei MironovTrevor Murphy60122
2Sami NikuKyle Wood40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Kyle CliffordJason DickinsonAndrei MironovTrevor Murphy
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Kyle CliffordJason DickinsonAndrei MironovTrevor Murphy
Extra Forwards
Normal PowerPlayPenalty Kill
Rich Clune, Dennis Yan, Anthony CamaraRich Clune, Dennis YanAnthony Camara
Extra Defensemen
Normal PowerPlayPenalty Kill
Simon Despres, Michael Kapla, Sami NikuSimon DespresMichael Kapla, Sami Niku
Penalty Shots
Kyle Clifford, Tanner Glass, Jason Dickinson, Anton Blidh,
Goalie
#1 : Vitek Vanecek, #2 : Kristers Gudlevskis


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
1Admirals21100000541110000003121010000023-120.50059140030412423031130628618529404911327.27%20195.00%0583114550.92%550124644.14%29153054.91%935647919276444225
2Americans2110000034-11010000003-31100000031220.5003580030412424131130628618481740351317.69%19478.95%0583114550.92%550124644.14%29153054.91%935647919276444225
3Bruins31200000550211000004311010000012-120.333591401304124273311306286186424635812216.67%27196.30%0583114550.92%550124644.14%29153054.91%935647919276444225
4Checkers220000001221000000000000220000001221041.0001223350130412427931130628618491820618225.00%100100.00%0583114550.92%550124644.14%29153054.91%935647919276444225
5Crunch2010010047-31010000024-21000010023-110.250481200304124258311306286183015204116318.75%9366.67%0583114550.92%550124644.14%29153054.91%935647919276444225
6Devils1010000013-21010000013-20000000000000.000123003041242153113062861821141822800.00%9277.78%0583114550.92%550124644.14%29153054.91%935647919276444225
7Griffins22000000624110000003121100000031241.0006121800304124256311306286183911244914428.57%10280.00%0583114550.92%550124644.14%29153054.91%935647919276444225
8IceHogs11000000202000000000001100000020221.000246013041242253113062861822610126233.33%50100.00%0583114550.92%550124644.14%29153054.91%935647919276444225
9Monsters2020000006-62020000006-60000000000000.000000003041242353113062861842163135900.00%14471.43%0583114550.92%550124644.14%29153054.91%935647919276444225
10Penguins85300000181624310000095442200000911-2100.6251833510130412421703113062861820667158151691318.84%64985.94%1583114550.92%550124644.14%29153054.91%935647919276444225
11Phantoms612001021015-52000010135-241200001710-350.41710162600304124215131130628618148549911342511.90%36683.33%0583114550.92%550124644.14%29153054.91%935647919276444225
12Sound Tigers11000000321110000003210000000000021.0003580030412421531130628618301014187228.57%6183.33%0583114550.92%550124644.14%29153054.91%935647919276444225
13Thunderbirds4200110018992200000010192000110088070.875183250013041242121311306286188933628718422.22%29389.66%0583114550.92%550124644.14%29153054.91%935647919276444225
Total38191301302967620201170010147351218860120149418450.59296175271063041242912311306286188783056347822424418.18%2713786.35%1583114550.92%550124644.14%29153054.91%935647919276444225
15Wolf Pack22000000918220000009180000000000041.000917260130412424331130628618381135519333.33%13192.31%0583114550.92%550124644.14%29153054.91%935647919276444225
_Since Last GM Reset38191301302967620201170010147351218860120149418450.59296175271063041242912311306286188783056347822424418.18%2713786.35%1583114550.92%550124644.14%29153054.91%935647919276444225
_Vs Conference251011002025055-5157600101312921035001011926-7240.4805090140033041242560311306286185792114384891722816.28%1782784.83%1583114550.92%550124644.14%29153054.91%935647919276444225
_Vs Division225400100534581232000002522310220010028235110.2505396149033041242508311306286185341903754511522516.45%1522384.87%1583114550.92%550124644.14%29153054.91%935647919276444225

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
3845L19617527191287830563478206
All Games
GPWLOTWOTL SOWSOLGFGA
38191313029676
Home Games
GPWLOTWOTL SOWSOLGFGA
2011701014735
Visitor Games
GPWLOTWOTL SOWSOLGFGA
188612014941
Last 10 Games
WLOTWOTL SOWSOL
531100
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2424418.18%2713786.35%1
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
311306286183041242
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
583114550.92%550124644.14%29153054.91%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
935647919276444225


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
4 - 2018-09-0811Crunch4Bears2LBoxScore
5 - 2018-09-0926Sound Tigers2Bears3WBoxScore
10 - 2018-09-1434Bears3Griffins1WBoxScore
11 - 2018-09-1548Bears2Admirals3LBoxScore
12 - 2018-09-1662Bears2IceHogs0WBoxScore
15 - 2018-09-1966Bears0Penguins2LBoxScore
17 - 2018-09-2170Bears6Checkers2WBoxScore
18 - 2018-09-2284Bears6Checkers0WBoxScore
24 - 2018-09-28109Bears1Penguins4LBoxScore
25 - 2018-09-29118Penguins1Bears2WBoxScore
26 - 2018-09-30134Phantoms3Bears2LXXBoxScore
31 - 2018-10-05145Bears3Americans1WBoxScore
32 - 2018-10-06156Americans3Bears0LBoxScore
33 - 2018-10-07168Wolf Pack1Bears3WBoxScore
39 - 2018-10-13195Thunderbirds1Bears5WBoxScore
40 - 2018-10-14209Bears2Crunch3LXBoxScore
45 - 2018-10-19223Monsters4Bears0LBoxScore
46 - 2018-10-20238Monsters2Bears0LBoxScore
52 - 2018-10-26268Bears3Phantoms2WBoxScore
53 - 2018-10-27282Bears3Penguins2WBoxScore
57 - 2018-10-31300Penguins3Bears0LBoxScore
60 - 2018-11-03323Thunderbirds0Bears5WBoxScore
61 - 2018-11-04335Devils3Bears1LBoxScore
66 - 2018-11-09352Bears2Phantoms3LXXBoxScore
67 - 2018-11-10364Wolf Pack0Bears6WBoxScore
68 - 2018-11-11379Penguins1Bears4WBoxScore
74 - 2018-11-17408Bears1Bruins2LBoxScore
75 - 2018-11-18417Bears4Thunderbirds5LXBoxScore
78 - 2018-11-21427Bears1Phantoms2LBoxScore
80 - 2018-11-23434Penguins0Bears3WBoxScore
81 - 2018-11-24456Phantoms2Bears1LXBoxScore
87 - 2018-11-30479Bears5Penguins3WBoxScore
88 - 2018-12-01488Bruins3Bears2LBoxScore
89 - 2018-12-02501Bruins0Bears2WBoxScore
95 - 2018-12-08536Griffins1Bears3WBoxScore
96 - 2018-12-09549Admirals1Bears3WBoxScore
101 - 2018-12-14566Bears4Thunderbirds3WXBoxScore
102 - 2018-12-15580Bears1Phantoms3LBoxScore
103 - 2018-12-16590Phantoms-Bears-
106 - 2018-12-19598Bears-Devils-
109 - 2018-12-22624Bears-Penguins-
110 - 2018-12-23632Bears-Sound Tigers-
113 - 2018-12-26649Bears-Phantoms-
116 - 2018-12-29672Rocket-Bears-
123 - 2019-01-05700Phantoms-Bears-
124 - 2019-01-06711Senators-Bears-
127 - 2019-01-09718Bears-Thunderbirds-
130 - 2019-01-12737Checkers-Bears-
131 - 2019-01-13755Checkers-Bears-
134 - 2019-01-16762Penguins-Bears-
137 - 2019-01-19781Phantoms-Bears-
138 - 2019-01-20801Bears-Phantoms-
Trade Deadline --- Trades can’t be done after this day is simulated!
143 - 2019-01-25822Bears-Penguins-
144 - 2019-01-26833IceHogs-Bears-
145 - 2019-01-27840Bears-Sound Tigers-
148 - 2019-01-30851Bears-Wolf Pack-
150 - 2019-02-01857Bears-Comets-
151 - 2019-02-02870Sound Tigers-Bears-
157 - 2019-02-08901Bears-Bruins-
158 - 2019-02-09912Bears-Bruins-
159 - 2019-02-10923Bears-Wolf Pack-
162 - 2019-02-13935Thunderbirds-Bears-
164 - 2019-02-15945Marlies-Bears-
165 - 2019-02-16956Sound Tigers-Bears-
168 - 2019-02-19972Penguins-Bears-
172 - 2019-02-23996Bears-Monsters-
173 - 2019-02-241009Bears-Monsters-
179 - 2019-03-021040Bruins-Bears-
180 - 2019-03-031054Bears-Sound Tigers-
184 - 2019-03-071072Bears-Marlies-
185 - 2019-03-081073Bears-Senators-
186 - 2019-03-091083Bears-Rocket-
189 - 2019-03-121105Phantoms-Bears-
192 - 2019-03-151122Bears-Wolf Pack-
193 - 2019-03-161129Comets-Bears-
194 - 2019-03-171146Wolf Pack-Bears-



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

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
18 0 - 0.00% 0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
3,353,917$ 68,000$ 43,940$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 41,536$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 92 32,825$ 3,019,900$




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
13381913013029676202011700101473512188601201494184596175271063041242912311306286188783056347822424418.18%2713786.35%1583114550.92%550124644.14%29153054.91%935647919276444225
Total Regular Season381913013029676202011700101473512188601201494184596175271063041242912311306286188783056347822424418.18%2713786.35%1583114550.92%550124644.14%29153054.91%935647919276444225
Playoff
1240400000313-102020000035-22020000008-803580012004915132101112956852129.52%27485.19%0478952.81%6915245.39%325162.75%8860107304723
1240400000313-102020000035-22020000008-803580012004915132101112956852129.52%27485.19%0478952.81%6915245.39%325162.75%8860107304723
Total Playoff80800000626-2040400000610-440400000016-16061016002400983026420222581121704249.52%54885.19%09417852.81%13830445.39%6410262.75%177120214619446