Bruins

GP: 4 | W: 0 | L: 4 | OTL: 0 | P: 0
GF: 7 | GA: 20 | PP%: 14.29% | PK%: 60.00%
GM : Danick Payment | Morale : 49 | Team Overall : 60
Next Games vs Condors
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
1Austin CzarnikX99.006340998058588762567055602550506549620
2Luke Kunin (R)XX100.008378807771646861506060712547476649620
3Justin BaileyX97.008144947573598154265876632549497149620
4Kevin RoyX99.006341917161668365265475642546466949620
5Vinni Lettieri (R)XX100.007743997265627666386657612546466449610
6Nicolas Roy (R)X100.008078846878747859745954665144446249610
7Zack MacEwen (R)XX100.007777766677778259745856645344446249610
8Liam O'BrienX100.008279886879778356504662665945456449610
9Filip Chytil (R)X100.007065806565636363796260625745456349600
10Ian McCoshenX99.008460817781677157254349712547476049640
11Oscar Fantenberg (R)X100.008167877674646071256149612546466149630
12MacKenzie WeegarX100.008365846868657763255048642551516049620
13Rasmus AnderssonX100.005942877977687571254047622545455849620
14Kyle Wood (R)X100.008381896881687351254741653944445649610
Scratches
1Jake DebruskX94.007553917667688873387974537552527249670
2Sean KuralyXX94.008459847277628660776058792555556649650
3Matthew Highmore (R)XX100.006942997066628662315068712545456749610
4Daniel O'ReganX100.005940967262566158666555632546466149590
5Jesse Gabrielle (R)X100.007973936873586149504746634444445549550
6Cameron Hughes (R)X100.007064846564515251645444594244445449540
7Vincent Dunn (R)XX100.006670555770555750635244574244445149520
8Reid Duke (R)X100.007670896570505244553844604244445149520
9Haydn FleuryX94.007844927277718456255147682552526049640
10Dysin MayoX100.007472806572535547253741603944445149550
TEAM AVERAGE99.00756087717163725946545564364747614960
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
1Kristers Gudlevskis100.00536683804957515854533044455549570
2Maxime Lagace97.00465453735042434850466545454849500
Scratches
TEAM AVERAGE98.5050606877505047535250484545524954
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary


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
1Zack MacEwenBruins (BOS)C/RW42352602282425.00%46315.8700001000070040.00%522001.5800000000
2Vinni LettieriBruins (BOS)C/RW42131003351240.00%05513.8310111000000025.00%1610001.0800000000
3Kevin RoyBruins (BOS)LW4123-6206494611.11%27218.0110141000004000.00%200000.8300000000
4Austin CzarnikBruins (BOS)C4022-600792130.00%16616.6401109000000050.00%4010000.6000000000
5Sean KuralyBruins (BOS)C/LW4022-82041011280.00%29724.330112110001140056.31%10337000.4100000000
6Ian McCoshenBruins (BOS)D4112-10431531221050.00%69122.76000010000010000.00%002000.4400111000
7Liam O'BrienBruins (BOS)LW4202012103531266.67%05112.95000000000000100.00%102000.7700002000
8Haydn FleuryBruins (BOS)D4022-1000555110.00%710927.35022112000016000.00%034000.3700000000
9Luke KuninBruins (BOS)C/RW4101-634209382512.50%16616.63000210101150075.00%432000.3000112000
10Justin BaileyBruins (BOS)RW4011-62010118310.00%07518.810001901126000.00%310000.2700000000
11Rasmus AnderssonBruins (BOS)D4011-100363110.00%87919.9000019000010000.00%021000.2500000000
12Jake DebruskBruins (BOS)LW4101-940510133127.69%29624.130002110000130038.71%3151000.2100000000
13Kyle WoodBruins (BOS)D4011-200350010.00%15614.210000000005000.00%001000.3500000000
14Oscar FantenbergBruins (BOS)D4000-195622110.00%48320.7800011000009000.00%010000.0000001000
15Filip ChytilBruins (BOS)C4000155220000.00%0287.1000001000010050.00%200000.0000001000
16Nicolas RoyBruins (BOS)C4000-3175221000.00%0164.0600000000000050.00%402000.0000010000
17MacKenzie WeegarBruins (BOS)D4000-175330100.00%35714.380000000002000.00%001000.0000010000
Team Total or Average68101626-6514365769480244712.50%41116717.162461511311241060048.82%2112225000.4500247000
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
1Kristers GudlevskisBruins (BOS)40300.7506.9613800166433000.000040000
2Maxime LagaceBruins (BOS)30100.8227.7210100137346000.000004000
Team Total or Average70400.7887.25240002913779000.000044000


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 CONT StatusType Current Salary Salary Year 2 Salary Year 3 Salary Year 4 Salary Year 5 Salary Year 6 Salary Year 7 Salary Year 8 Salary Year 9 Salary Year 10 Link
Austin CzarnikBruins (BOS)C251992-12-12No160 Lbs5 ft9NoNoNo2RFAPro & Farm900,000$900,000$Link
Cameron HughesBruins (BOS)C211996-10-09Yes174 Lbs6 ft0NoNoNo3RFAPro & Farm500,000$500,000$500,000$Link
Daniel O'ReganBruins (BOS)C241994-01-30No180 Lbs5 ft9NoNoNo2RFAPro & Farm500,000$500,000$Link
Dysin MayoBruins (BOS)D221996-08-16No195 Lbs6 ft2NoNoNo2RFAPro & Farm500,000$500,000$Link
Filip ChytilBruins (BOS)C191999-09-05Yes178 Lbs6 ft1NoNoNo3ELCPro & Farm900,000$900,000$900,000$Link
Haydn FleuryBruins (BOS)D221996-07-07No221 Lbs6 ft3NoNoNo2RFAPro & Farm950,000$950,000$Link
Ian McCoshenBruins (BOS)D231995-08-04No217 Lbs6 ft3NoNoNo2RFAPro & Farm850,000$850,000$Link
Jake DebruskBruins (BOS)LW211996-10-16No183 Lbs6 ft0NoNoNo2RFAPro & Farm950,000$950,000$Link
Jesse GabrielleBruins (BOS)LW211997-06-17Yes204 Lbs5 ft11NoNoNo3RFAPro & Farm600,000$600,000$600,000$Link
Justin BaileyBruins (BOS)RW231995-07-01No214 Lbs6 ft3NoNoNo1RFAPro & Farm800,000$Link
Kevin RoyBruins (BOS)LW251993-05-19No174 Lbs5 ft9NoNoNo2RFAPro & Farm650,000$650,000$Link
Kristers GudlevskisBruins (BOS)C261992-07-31No218 Lbs6 ft3NoNoNo4RFAPro & Farm650,000$650,000$650,000$650,000$Link
Kyle WoodBruins (BOS)D221996-05-03Yes235 Lbs6 ft7NoNoNo2RFAPro & Farm700,000$700,000$Link
Liam O'BrienBruins (BOS)LW241994-07-29No215 Lbs6 ft1NoNoNo1RFAPro & Farm925,000$Link
Luke KuninBruins (BOS)C/RW201997-12-04Yes191 Lbs6 ft0NoNoNo3ELCPro & Farm950,000$950,000$950,000$Link
MacKenzie WeegarBruins (BOS)D241994-01-07No212 Lbs6 ft0NoNoNo1RFAPro & Farm850,000$Link
Matthew HighmoreBruins (BOS)LW/RW221996-02-27Yes181 Lbs5 ft11NoNoNo2RFAPro & Farm975,000$975,000$Link
Maxime LagaceBruins (BOS)D251993-01-11No190 Lbs6 ft2NoNoNo1RFAPro & Farm720,000$Link
Nicolas RoyBruins (BOS)C211997-02-05Yes208 Lbs6 ft4NoNoNo3RFAPro & Farm650,000$650,000$650,000$Link
Oscar FantenbergBruins (BOS)D261991-10-07Yes203 Lbs6 ft0NoNoNo4RFAPro & Farm1,000,000$1,000,000$1,000,000$1,000,000$Link
Rasmus AnderssonBruins (BOS)D211996-10-26No214 Lbs6 ft1NoNoNo2RFAPro & Farm800,000$800,000$Link
Reid DukeBruins (BOS)C221996-01-28Yes191 Lbs6 ft0NoNoNo3RFAPro & Farm500,000$500,000$500,000$Link
Sean KuralyBruins (BOS)C/LW251993-01-20No205 Lbs6 ft2NoNoNo3RFAPro & Farm700,000$700,000$700,000$Link
Vincent DunnBruins (BOS)C/LW231995-09-14Yes190 Lbs6 ft0NoNoNo3RFAPro & Farm500,000$500,000$500,000$Link
Vinni LettieriBruins (BOS)C/RW231995-02-06Yes195 Lbs5 ft11NoNoNo2RFAPro & Farm925,000$925,000$Link
Zack MacEwenBruins (BOS)C/RW221996-07-08Yes212 Lbs6 ft3NoNoNo3RFAPro & Farm925,000$925,000$925,000$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2622.77198 Lbs6 ft12.35764,231$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Luke Kunin40122
2Kevin RoyAustin CzarnikJustin Bailey30122
3Liam O'BrienVinni LettieriZack MacEwen20122
4Nicolas Roy10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ian McCoshen40122
2Oscar FantenbergRasmus Andersson30122
3MacKenzie WeegarKyle Wood20122
4Ian McCoshen10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Luke Kunin60122
2Kevin RoyAustin CzarnikJustin Bailey40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Ian McCoshen60122
2Oscar FantenbergRasmus Andersson40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
160122
2Luke KuninJustin Bailey40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Ian McCoshen60122
2Oscar FantenbergRasmus Andersson40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
160122Ian McCoshen60122
240122Oscar FantenbergRasmus Andersson40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
160122
2Luke KuninJustin Bailey40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ian McCoshen60122
2Oscar FantenbergRasmus Andersson40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Luke KuninIan McCoshen
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Luke KuninIan McCoshen
Extra Forwards
Normal PowerPlayPenalty Kill
Filip Chytil, Vinni Lettieri, Zack MacEwenFilip Chytil, Vinni LettieriZack MacEwen
Extra Defensemen
Normal PowerPlayPenalty Kill
MacKenzie Weegar, Kyle Wood, Oscar FantenbergMacKenzie WeegarKyle Wood, Oscar Fantenberg
Penalty Shots
, , Luke Kunin, Justin Bailey, Austin Czarnik
Goalie
#1 : Kristers Gudlevskis, #2 : Maxime Lagace


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
1Condors1010000013-21010000013-20000000000000.00012300352073437901352184125.00%10100.00%0306943.48%276442.19%467858.97%723386398040
2IceCaps10100000410-610100000410-60000000000000.000461000352023343790511167175120.00%6433.33%0306943.48%276442.19%467858.97%723386398040
3Marlies1010000027-51010000027-50000000000000.000246003520233437903481625300.00%8275.00%0306943.48%276442.19%467858.97%723386398040
4Rampage1010000039-6000000000001010000039-600.0003470035202734379039176016200.00%5260.00%1306943.48%276442.19%467858.97%723386398040
Since Last GM Reset404000001029-1930300000720-131010000039-600.00010162600352080343790137411457614214.29%20860.00%1306943.48%276442.19%467858.97%723386398040
Total404000001029-1930300000720-131010000039-600.00010162600352080343790137411457614214.29%20860.00%1306943.48%276442.19%467858.97%723386398040
Vs Conference20200000617-1120200000617-110000000000000.0006101600352046343790851983428112.50%14657.14%0306943.48%276442.19%467858.97%723386398040
Vs Division20200000617-1120200000617-110000000000000.0006101600352046343790851983428112.50%14657.14%0306943.48%276442.19%467858.97%723386398040

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
40L410162680137411457600
All Games
GPWLOTWOTL SOWSOLGFGA
40400001029
Home Games
GPWLOTWOTL SOWSOLGFGA
3030000720
Visitor Games
GPWLOTWOTL SOWSOLGFGA
101000039
Last 10 Games
WLOTWOTL SOWSOL
040000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
14214.29%20860.00%1
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
3437903520
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
306943.48%276442.19%467858.97%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
723386398040


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
2 - 2018-09-1817Condors3Bruins1LBoxScore
3 - 2018-09-1932Marlies7Bruins2LBoxScore
4 - 2018-09-2041Bruins3Rampage9LBoxScore
6 - 2018-09-2267IceCaps10Bruins4LBoxScore
8 - 2018-09-2481Bruins-Americans-
11 - 2018-09-27101Senators-Bruins-
12 - 2018-09-28112Bruins-Marlies-
Trade Deadline --- Trades can’t be done after this day is simulated!
14 - 2018-09-30128Americans-Bruins-
15 - 2018-10-01135Bruins-Senators-
16 - 2018-10-02143Bruins-IceCaps-



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
2 0 - 0.00% 0$0$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches Salaries
1,987,000$ 1,542,000$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To Date
0$ 0$ 0$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 12 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