Bruins

GP: 45 | W: 12 | L: 26 | OTL: 7 | P: 31
GF: 77 | GA: 121 | PP%: 11.22% | PK%: 85.29%
GM : Mika Laakso | Morale : 50 | Team Overall : 56
Next Games #741 vs Devils
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 CzarnikX97.006340998058588762567055602550506550610
2Colby CaveXX100.007368856768839059745756625344446250600
3Janne Kuokkanen (R)XXX99.007269807069666762786457635444446350600
4Anthony Greco (R)XX99.007062886662828862505465626244446550600
5Ben SextonX100.007066806766616163795963626044446350590
6Aleksi Saarela (R)X100.007668956668585861765265646244446450580
7Seth GriffithX100.006541907367578064265559522553536150580
8Kalle KossilaXXX100.006942997564538060666059512545456150580
9Jakob Forsbacka Karlsson (R)X97.007368866468646560755660635744446250580
10Ryan Fitzgerald (R)X100.006661796461676960755362595944446250570
11Joshua WinquistX100.007367876167616261505760635744446250570
12Cameron Hughes (R)X100.007064846564515251645444594244445450530
13Zach Trotman (R)X100.008380897180515251253946684453535650590
14Andrew Nielsen (R)X99.006777426877677151254641573944445150570
15Emil Johansson (R)X99.007469876869657046253740603844445250560
16Chris CastoX100.007976876476515346253739623744445150550
17Kris BindulisX100.007973936573505244253439623744445150550
18Joonas Lyytinen (R)X100.006458776358586246253640553844444950520
Scratches
1Andrew PoturalskiX96.007468896268849062785861645844446550610
2Anton BlidhXX96.007773856973808755504956645345456150590
3Ryan LombergX100.007570866770758057505357635444446150590
4Justin HickmanXX100.007880746580515153664556635344445850550
5Jesse Gabrielle (R)X100.007973936873586149504746634444445550540
6Clarke MacArthurX100.007242877062323050506046644244445850530
7Tyler RandellX100.006772556472687448504446574446465350530
8Mikkel Aagaard (R)XXX100.006864786464484851644156585344445550520
9Tony TurgeonX100.007686516886434444453141603944444950490
10Luc Snuggerud (R)X100.007471826871505053254646614444445550560
11Dmitry Osipov (R)X100.008384816584495145253539643744445150560
12Jeremy Lauzon (R)X100.007675786575586245253639603744445150550
13Linus Arnesson (R)X100.007569896769525543254139593744445050540
TEAM AVERAGE99.42736782677060655449495161454545575056
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
1Adam Carlson (R)99.00524961705352525753533044445350530
2Jack Flinn100.00454455924343505246473044444750510
Scratches
1Ivan Kulbakov (R)100.00476075674247505445463044444950500
TEAM AVERAGE99.6748516476464751544849304444505051
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Charlie Huddy63707259454659CAN554750,000$


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
1Janne KuokkanenBruins (BOS)C/LW/RW4211920-112205080652216.92%885420.35426141321123952153.33%13500010.4701000223
2Colby CaveBruins (BOS)C/LW3251217-62004464392412.82%967721.170442790110510161.78%41600000.5001000114
3Ryan LombergBruins (BOS)LW4251116-151604768453411.11%365015.481459770002200049.31%36100000.4902000132
4Andrew PoturalskiBruins (BOS)C3551015-142604270642127.81%882623.611451412700021031161.07%59600000.3634000202
5Anthony GrecoBruins (BOS)LW/RW4241014-12240487371195.63%1178918.80235221570002970046.20%32900000.3511000110
6Ben SextonBruins (BOS)C394913-1060436762056.45%762015.911451510100031020058.26%35700000.4204000021
7Anton BlidhBruins (BOS)LW/RW448513-1134077756161213.11%1586919.771014520001562048.65%3700000.3000000252
8Seth GriffithBruins (BOS)RW4558130201261432311.63%353711.94000115000032027.78%1800000.4800000110
9Austin CzarnikBruins (BOS)C34448-12601781362411.11%770420.73123710900041240048.17%35500000.2312000111
10Jakob Forsbacka KarlssonBruins (BOS)C44347-11402047367118.33%346410.562029980000291062.22%13500000.3000000100
11Luc SnuggerudBruins (BOS)D1716728025650020.00%1832719.29134446000068000.00%000000.4300000101
12Emil JohanssonBruins (BOS)D45257-113805923131415.38%41100122.2623561180000116010.00%000000.1400000011
13Aleksi SaarelaBruins (BOS)C37606-61201316283421.43%42185.92101416000060064.52%3100000.5500000100
14Andrew NielsenBruins (BOS)D45156-215601251913207.69%43104423.2011271520000136100.00%000000.1100000021
15Kris BindulisBruins (BOS)D441562340602415346.67%2281418.5111271020000113000.00%000000.1500000000
16Chris CastoBruins (BOS)D36145-10320591614107.14%3965418.19101564000072000.00%000000.1500000000
17Jussi JokinenBruinsRW514530021040025.00%08416.9601108000000056.94%7200001.1800000010
18Daniel SprongBruinsRW52133801111100020.00%110020.12000000000230045.45%4400000.6000000010
19Kalle KossilaBruins (BOS)C/LW/RW36213-96062922179.09%02527.03101127000070056.72%6700000.2400000110
20Joonas LyytinenBruins (BOS)D28033-9802152000.00%931511.27000135000032000.00%000000.1900000000
21Colton HargroveBruinsLW911201201018100010.00%515817.630116341011280154.55%3300000.2500000100
22Zach TrotmanBruins (BOS)D45022-284610593419120.00%5597921.7602291360000125000.00%000000.0400011000
23Joshua WinquistBruins (BOS)LW71122003140025.00%0344.920000300002000.00%300001.1600000100
24Dmitry OsipovBruins (BOS)D91122200124100100.00%416117.97101124000029000.00%000000.2500000100
25Ryan FitzgeraldBruins (BOS)C12011100003000.00%0191.6200001000030075.00%800001.0300000000
26Zac RinaldoBruinsLW/RW4011-114012109000.00%15714.3601101000000000.00%200000.3500000000
27Jeremy LauzonBruins (BOS)D1000000010000.00%21515.980000100001000.00%000000.0000000000
28Cameron HughesBruins (BOS)C26000100001000.00%0110.46000000000200100.00%100000.0000000000
Team Total or Average81074123197-18145410877913695398710.65%3181324916.3622365814817352241814559555.10%300000010.30515011182218
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
1Adam CarlsonBruins (BOS)3481950.8872.67197601887790100.846133213400
2Niklas SvedbergBruins104510.8952.5252402222090000.0000109111
3Jack FlinnBruins (BOS)50210.9182.302350091100000.6673323100
Team Total or Average49122670.8922.6127360311910980100.812164545611


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
Adam CarlsonBruins (BOS)G241994-02-13Yes175 Lbs6 ft3NoNoNo1ELCPro & Farm795,000$0$0$NoLink
Aleksi SaarelaBruins (BOS)C221997-01-07Yes198 Lbs5 ft11NoNoNo3ELCPro & Farm700,000$0$0$NoLink
Andrew NielsenBruins (BOS)D221996-11-13Yes227 Lbs6 ft4NoNoNo2ELCPro & Farm750,000$0$0$NoLink
Andrew PoturalskiBruins (BOS)C251994-01-14No181 Lbs5 ft10NoNoNo2ELCPro & Farm850,000$0$0$NoLink
Anthony GrecoBruins (BOS)LW/RW251993-09-30Yes172 Lbs5 ft10NoNoNo2ELCPro & Farm625,000$0$0$NoLink
Anton BlidhBruins (BOS)LW/RW231995-03-14No201 Lbs6 ft0NoNoNo1ELCPro & Farm500,000$0$0$NoLink
Austin CzarnikBruins (BOS)C261992-12-12No160 Lbs5 ft9NoNoNo1ELCPro & Farm675,000$0$0$NoLink
Ben SextonBruins (BOS)C271991-05-06No196 Lbs5 ft11NoNoNo2RFAPro & Farm725,000$0$0$NoLink
Cameron HughesBruins (BOS)C221996-10-09Yes174 Lbs6 ft0NoNoNo3ELCPro & Farm500,000$0$0$NoLink
Chris CastoBruins (BOS)D271991-12-27No200 Lbs6 ft1NoNoNo1RFAPro & Farm650,000$0$0$NoLink
Clarke MacArthurBruins (BOS)LW331985-04-06No192 Lbs6 ft0NoNoNo2UFAPro & Farm4,650,000$0$0$NoLink
Colby CaveBruins (BOS)C/LW241994-12-26No200 Lbs6 ft1NoNoNo1ELCPro & Farm655,000$0$0$NoLink
Dmitry OsipovBruins (BOS)D221996-10-04Yes229 Lbs6 ft4NoNoNo3ELCPro & Farm650,000$0$0$NoLink
Emil JohanssonBruins (BOS)D221996-05-06Yes190 Lbs5 ft11NoNoNo3ELCPro & Farm500,000$0$0$NoLink
Ivan KulbakovBruins (BOS)G221996-09-18Yes183 Lbs6 ft0NoNoNo3ELCPro & Farm650,000$0$0$NoLink
Jack FlinnBruins (BOS)G231995-12-20No223 Lbs6 ft8NoNoNo2ELCPro & Farm625,000$0$0$NoLink
Jakob Forsbacka KarlssonBruins (BOS)C221996-10-31Yes184 Lbs6 ft1NoNoNo3ELCPro & Farm750,000$0$0$NoLink
Janne KuokkanenBruins (BOS)C/LW/RW201998-05-25Yes188 Lbs6 ft1NoNoNo3ELCPro & Farm750,000$0$0$NoLink
Jeremy LauzonBruins (BOS)D211997-04-28Yes204 Lbs6 ft1NoNoNo3ELCPro & Farm800,000$0$0$NoLink
Jesse GabrielleBruins (BOS)LW211997-06-17Yes204 Lbs5 ft11NoNoNo3ELCPro & Farm600,000$0$0$NoLink
Joonas LyytinenBruins (BOS)D231995-04-04Yes172 Lbs6 ft0NoNoNo3ELCPro & Farm500,000$0$0$NoLink
Joshua WinquistBruins (BOS)LW251993-09-06No185 Lbs5 ft11NoNoNo2ELCPro & Farm625,000$0$0$NoLink
Justin HickmanBruins (BOS)C/RW241994-03-18No224 Lbs6 ft2NoNoNo1ELCPro & Farm792,000$0$0$NoLink
Kalle KossilaBruins (BOS)C/LW/RW251993-04-14No175 Lbs5 ft11NoNoNo2ELCPro & Farm1,450,000$0$0$NoLink
Kris BindulisBruins (BOS)D231995-09-17No190 Lbs6 ft3NoNoNo3ELCPro & Farm792,500$0$0$NoLink
Linus ArnessonBruins (BOS)D241994-09-21Yes188 Lbs6 ft1NoNoNo1ELCPro & Farm800,000$0$0$NoLink
Luc SnuggerudBruins (BOS)D231995-09-18Yes184 Lbs6 ft0NoNoNo2ELCPro & Farm500,000$0$0$NoLink
Mikkel AagaardBruins (BOS)C/LW/RW231995-10-27Yes176 Lbs5 ft11NoNoNo2ELCPro & Farm625,000$0$0$NoLink
Ryan FitzgeraldBruins (BOS)C241994-10-19Yes172 Lbs5 ft9NoNoNo3ELCPro & Farm600,000$0$0$NoLink
Ryan LombergBruins (BOS)LW241994-12-09No190 Lbs5 ft9NoNoNo2ELCPro & Farm710,000$0$0$NoLink
Seth GriffithBruins (BOS)RW261993-01-03No191 Lbs5 ft9NoNoNo1ELCPro & Farm650,000$0$0$NoLink
Tony TurgeonBruins (BOS)C221996-02-24No231 Lbs6 ft4NoNoNo2ELCPro & Farm625,000$0$0$NoLink
Tyler RandellBruins (BOS)RW271991-06-14No198 Lbs6 ft1NoNoNo1RFAPro & Farm700,000$0$0$NoLink
Zach TrotmanBruins (BOS)D281990-08-25Yes216 Lbs6 ft3NoNoNo1UFAPro & Farm650,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3423.94193 Lbs6 ft02.06806,456$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Austin CzarnikColby CaveAnthony Greco40122
2Jakob Forsbacka KarlssonJanne KuokkanenBen Sexton30122
3Janne KuokkanenAustin CzarnikSeth Griffith20122
4Colby CaveKalle KossilaAleksi Saarela10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Zach TrotmanAndrew Nielsen40122
2Emil JohanssonChris Casto30122
3Emil JohanssonKris Bindulis20122
4Zach TrotmanAndrew Nielsen10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Colby CaveAustin CzarnikJakob Forsbacka Karlsson60122
2Anthony GrecoJanne KuokkanenBen Sexton40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Zach TrotmanAndrew Nielsen60122
2Emil JohanssonKris Bindulis40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Janne KuokkanenJakob Forsbacka Karlsson60122
2Colby CaveAustin Czarnik40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Zach TrotmanAndrew Nielsen60122
2Emil JohanssonKris Bindulis40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Austin Czarnik60122Zach TrotmanAndrew Nielsen60122
2Jakob Forsbacka Karlsson40122Emil JohanssonKris Bindulis40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Jakob Forsbacka KarlssonJanne Kuokkanen60122
2Austin CzarnikColby Cave40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Zach TrotmanAndrew Nielsen60122
2Kris BindulisEmil Johansson40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Janne KuokkanenAustin CzarnikColby CaveZach TrotmanAndrew Nielsen
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Janne KuokkanenAustin CzarnikColby CaveZach TrotmanAndrew Nielsen
Extra Forwards
Normal PowerPlayPenalty Kill
Jakob Forsbacka Karlsson, Janne Kuokkanen, Austin CzarnikJakob Forsbacka Karlsson, Austin CzarnikAustin Czarnik
Extra Defensemen
Normal PowerPlayPenalty Kill
Emil Johansson, Kris Bindulis, Andrew NielsenEmil JohanssonKris Bindulis, Zach Trotman
Penalty Shots
Janne Kuokkanen, Colby Cave, Aleksi Saarela, Austin Czarnik, Jakob Forsbacka Karlsson
Goalie
#1 : Adam Carlson, #2 : Jack Flinn


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
1Admirals1010000012-11010000012-10000000000000.00012300252029519206239242232381016200.00%5180.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
2Americans2010010035-22010010035-20000000000010.2503690025202953520623924223441624451317.69%10280.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
3Barracuda3110010038-52110000037-41000010001-130.50035800252029541206239242239324425510110.00%20480.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
4Bears2020000047-31010000012-11010000035-200.000481200252029532206239242234317124110110.00%60100.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
5Checkers1000000123-11000000123-10000000000010.5002350025202951820623924223195212700.00%10100.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
6Comets1010000014-3000000000001010000014-300.00012300252029517206239242232551222800.00%6183.33%0613108556.50%676125253.99%36466354.90%10277011160325552273
7Condors2110000045-1110000004311010000002-220.5004812002520295232062392422339918323133.33%8275.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
8Crunch2010010035-21010000012-11000010023-110.2503470025202953220623924223568143310110.00%70100.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
9Devils1010000014-31010000014-30000000000000.0001230025202952320623924223224820300.00%3166.67%0613108556.50%676125253.99%36466354.90%10277011160325552273
10Falcons4130000079-23120000067-11010000012-120.2507101701252029557206239242238120326821419.05%15193.33%0613108556.50%676125253.99%36466354.90%10277011160325552273
11Heat1010000015-41010000015-40000000000000.00012300252029516206239242232810016500.00%000.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
12IceCaps1010000014-3000000000001010000014-300.00011200252029511206239242232941217400.00%60100.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
13Icehogs2010001056-12010001056-10000000000020.500571200252029547206239242234514224813323.08%10460.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
14Moose30300000210-82020000017-61010000013-200.0002460025202953820623924223914028701000.00%13376.92%0613108556.50%676125253.99%36466354.90%10277011160325552273
15Penguins2010010057-2000000000002010010057-210.25051015002520295342062392422350918391317.69%60100.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
16Phantoms2020000024-21010000012-11010000012-100.00024600252029535206239242236424184710110.00%9366.67%0613108556.50%676125253.99%36466354.90%10277011160325552273
17Reign51300010715-82110000054130200010211-940.4007916012520295552062392422311831841011000.00%39684.62%2613108556.50%676125253.99%36466354.90%10277011160325552273
18Senators31100100972110000005142010010046-230.5009152400252029549206239242235915265015533.33%13192.31%0613108556.50%676125253.99%36466354.90%10277011160325552273
19Sound Tigers22000000826000000000002200000082641.000810180025202952620623924223421531388112.50%120100.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
Total459260053277121-4424614001214361-1821312004113460-26310.344771232000325202956952062392422310983184548771962211.22%2043085.29%2613108556.50%676125253.99%36466354.90%10277011160325552273
21Wild31000011541210000103121000000123-150.833561101252029549206239242236720206017211.76%8187.50%0613108556.50%676125253.99%36466354.90%10277011160325552273
22Wolf Pack11000000211000000000001100000021121.00024600252029515206239242233611817100.00%30100.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
23Wolves1010000014-3000000000001010000014-300.00011200252029523206239242232491330300.00%40100.00%0613108556.50%676125253.99%36466354.90%10277011160325552273
_Since Last GM Reset459260053277121-4424614001214361-1821312004113460-26310.344771232000325202956952062392422310983184548771962211.22%2043085.29%2613108556.50%676125253.99%36466354.90%10277011160325552273
_Vs Conference30718004105379-2614410000002436-121638004102943-14200.3335385138022520295437206239242237552183215791211512.40%1461986.99%2613108556.50%676125253.99%36466354.90%10277011160325552273
_Vs Division8310001101621-54360000098140400110713-690.56316264200252029512720623924223188437614542716.67%36391.67%0613108556.50%676125253.99%36466354.90%10277011160325552273

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
4531L177123200695109831845487703
All Games
GPWLOTWOTL SOWSOLGFGA
45926053277121
Home Games
GPWLOTWOTL SOWSOLGFGA
2461401214361
Visitor Games
GPWLOTWOTL SOWSOLGFGA
2131204113460
Last 10 Games
WLOTWOTL SOWSOL
080200
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1962211.22%2043085.29%2
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
206239242232520295
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
613108556.50%676125253.99%36466354.90%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
10277011160325552273


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 - 2018-10-0313Barracuda1Bruins2WBoxScore
3 - 2018-10-0423Bruins0Reign5LBoxScore
6 - 2018-10-0739Reign4Bruins0LBoxScore
9 - 2018-10-1065Falcons0Bruins3WBoxScore
13 - 2018-10-1494Wild1Bruins2WBoxScore
15 - 2018-10-16104Bruins2Reign1WXXBoxScore
16 - 2018-10-17114Bruins2Penguins3LXBoxScore
17 - 2018-10-18125Bruins1Moose3LBoxScore
19 - 2018-10-20140Phantoms2Bruins1LBoxScore
22 - 2018-10-23161Bruins5Sound Tigers1WBoxScore
24 - 2018-10-25171Americans3Bruins2LXBoxScore
27 - 2018-10-28191Barracuda6Bruins1LBoxScore
31 - 2018-11-01218Reign0Bruins5WBoxScore
33 - 2018-11-03236Bruins0Condors2LBoxScore
35 - 2018-11-05250Bruins3Sound Tigers1WBoxScore
36 - 2018-11-06255Icehogs2Bruins0LBoxScore
39 - 2018-11-09282Crunch2Bruins1LBoxScore
41 - 2018-11-11292Bruins1Comets4LBoxScore
44 - 2018-11-14313Wild0Bruins1WXXBoxScore
48 - 2018-11-18342Senators1Bruins5WBoxScore
50 - 2018-11-20358Bruins1Phantoms2LBoxScore
52 - 2018-11-22371Bruins1Wolves4LBoxScore
53 - 2018-11-23379Icehogs4Bruins5WXXBoxScore
56 - 2018-11-26404Checkers3Bruins2LXXBoxScore
58 - 2018-11-28419Bruins3Penguins4LBoxScore
61 - 2018-12-01436Moose4Bruins0LBoxScore
63 - 2018-12-03447Bruins0Reign5LBoxScore
65 - 2018-12-05465Falcons3Bruins1LBoxScore
67 - 2018-12-07480Bruins0Barracuda1LXBoxScore
69 - 2018-12-09492Bruins2Wild3LXXBoxScore
70 - 2018-12-10500Condors3Bruins4WBoxScore
73 - 2018-12-13524Bruins1IceCaps4LBoxScore
74 - 2018-12-14530Americans2Bruins1LBoxScore
76 - 2018-12-16546Bruins2Wolf Pack1WBoxScore
78 - 2018-12-18561Falcons4Bruins2LBoxScore
83 - 2018-12-23591Bears2Bruins1LBoxScore
85 - 2018-12-25598Bruins1Falcons2LBoxScore
87 - 2018-12-27619Bruins3Bears5LBoxScore
88 - 2018-12-28623Devils4Bruins1LBoxScore
92 - 2019-01-01648Bruins3Senators4LBoxScore
93 - 2019-01-02656Admirals2Bruins1LBoxScore
95 - 2019-01-04676Bruins2Crunch3LXBoxScore
96 - 2019-01-05684Heat5Bruins1LBoxScore
99 - 2019-01-08710Bruins1Senators2LXBoxScore
100 - 2019-01-09716Moose3Bruins1LBoxScore
103 - 2019-01-12741Bruins-Devils-
104 - 2019-01-13746Penguins-Bruins-
108 - 2019-01-17770Bruins-Penguins-
109 - 2019-01-18779Reign-Bruins-
111 - 2019-01-20800Bruins-Crunch-
112 - 2019-01-21807Gulls-Bruins-
117 - 2019-01-26839Wolves-Bruins-
119 - 2019-01-28856Bruins-Gulls-
121 - 2019-01-30870Wolf Pack-Bruins-
123 - 2019-02-01881Bruins-Bears-
125 - 2019-02-03901Wolf Pack-Bruins-
126 - 2019-02-04910Bruins-Moose-
127 - 2019-02-05920Bruins-Barracuda-
129 - 2019-02-07934Phantoms-Bruins-
132 - 2019-02-10951Bruins-Reign-
134 - 2019-02-12964Bruins-Monsters-
135 - 2019-02-13970Barracuda-Bruins-
138 - 2019-02-16987Bruins-Devils-
140 - 2019-02-181001Comets-Bruins-
142 - 2019-02-201012Bruins-Gulls-
143 - 2019-02-211025Bruins-Marlies-
Trade Deadline --- Trades can’t be done after this day is simulated!
145 - 2019-02-231036Sound Tigers-Bruins-
147 - 2019-02-251051Bruins-Falcons-
148 - 2019-02-261058Bruins-Griffins-
151 - 2019-03-011074Bruins-Pirates-
152 - 2019-03-021080Monsters-Bruins-
155 - 2019-03-051103Wolves-Bruins-
158 - 2019-03-081118Bruins-Stars-
160 - 2019-03-101137Monsters-Bruins-
163 - 2019-03-131152Bruins-Moose-
166 - 2019-03-161166Rampage-Bruins-



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
14 0 - 0.00% 0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
2,142,311$ 2,741,950$ 2,753,728$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 1,686,299$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 67 20,662$ 1,384,354$




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
2018459260053277121-4424614001214361-1821312004113460-2631771232000325202956952062392422310983184548771962211.22%2043085.29%2613108556.50%676125253.99%36466354.90%10277011160325552273
Total Regular Season459260053277121-4424614001214361-1821312004113460-2631771232000325202956952062392422310983184548771962211.22%2043085.29%2613108556.50%676125253.99%36466354.90%10277011160325552273