Marlies

GP: 48 | W: 22 | L: 22 | OTL: 4 | P: 48
GF: 311 | GA: 325 | PP%: 56.31% | PK%: 54.90%
GM : Sebastian Bravo | Morale : 50 | Team Overall : 59
Next Games #731 vs Senators
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# 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
1Adrian KempeXX99.007654828175659264727172547557577150650
2Dmitrij JaskinX100.009246937373638164306258694565666650630
3Phil VaroneXX100.007266856866848867806962645944446750630
4Ivan BarbashevXX100.007843978267629258496064612555556750620
5Nicholas Merkley (R)XX100.007368836768686868806568656544446850620
6Matt ReadXXX99.007643968366587560365057765770716450620
7Nikita SoshnikovXX100.008144917866586556255758756355556450610
8Frederik GauthierX100.008381897081768253664951674847476050590
9Nic PetanXXX100.006140877759528264475064652556566450590
10Adam ErneXX100.008175857278576260565464592548486450580
11Eric Cornel (R)XX100.007772896272747954684756635344446050570
12Travis DermottX99.007844927370697864256648672547476350630
13Martin MarincinX100.008077886677575953254641693961615550600
14Roland McKeownX100.006197507475628854256547552544445750580
Scratches
1Ty RattieX100.007142957365706569257275572548487650630
2Ryan MacInnisX100.007570886070727850634648614644445550540
3Matt TennysonX60.467344847076757673254047692558585950630
4Oliver KylingtonX100.007467917267717654255242624044445650590
5Jack Dougherty (R)X100.007469846669758346253739603744445250570
6Joe HickettsX100.007161946661788746253641583944445350570
7Sergei Boikov (R)X100.007273706473738048255041593944445350570
8Timothy Liljegren (R)X100.007570857270575950254739613744445350560
9Petteri LindbohmX100.007474756974565945253440603847475150550
10Reece Willcox (R)X100.007570876470636747253940603844445250550
11Adam Ollas Mattsson (R)X100.008178876578505341252839623744445050540
TEAM AVERAGE98.30756386717166755640525263415050605059
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3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
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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
1Eric Comrie100.00647290626468566763623044446450610
2Dan Vladar100.00624354816761656966663044446250610
Scratches
1Samuel Montembeault (R)100.00537088784956505851513044445550560
2Jack Flinn100.00454455924343505246473044444750510
TEAM AVERAGE100.0056577278565755625757304444575057
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary


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3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
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8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
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# Player Name Team 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
1Adrian KempeMarlies (Tor)LW/RW486891159440101078534610821419.65%34118424.6916203627733255603162.21%17210929192.68110111265
2Dmitrij JaskinMarlies (Tor)RW487659135840817232811217323.17%49100220.881914333474000266243.40%5356370102.6901000878
3Phil VaroneMarlies (Tor)C/LW48234669-1748207863149359215.44%2583117.324913539101251060.42%8162716001.6601121033
4Ty RattieMarlies (Tor)RW41303363-1612105723152388919.74%1367716.5375121035000002024.49%494712011.8600200141
5Matt TennysonMarlies (Tor)D4864753-464115848911639465.17%130136428.4321315770022463100.00%01866000.7800111012
6Matt ReadMarlies (Tor)C/LW/RW48163652-16556841125378312.80%2482317.15077140000001033.33%423426001.2600010201
7Travis DermottMarlies (Tor)D4844044-372515776810433313.85%93128126.6929111171033664100.00%02058000.6900012000
8Nicholas MerkleyMarlies (Tor)C/RW48191938-151755445114395816.67%1662613.06101110000021157.23%3322616011.2100010211
9Ivan BarbashevMarlies (Tor)C/LW48101929-1200504011052639.09%1565813.71000002029540166.04%534517000.8800000002
10Nikita SoshnikovMarlies (Tor)LW/RW48121325-1240684657173421.05%2158112.1210111000001036.84%191117000.8600000000
11Oliver KylingtonMarlies (Tor)D350191919161034475719200.00%3776121.77022139022743000.00%01023000.5000101000
12Nic PetanMarlies (Tor)C/LW/RW487512-32017254292216.67%62815.8700000000002053.70%1081410000.8500000000
13Adam ErneMarlies (Tor)LW/RW48257-31951620238158.70%52785.8000000000000050.00%4124000.5000100000
14Frederik GauthierMarlies (Tor)C48123-475349198215.26%62495.200110120002170048.15%2752000.2400100000
15Roland McKeownMarlies (Tor)D48033-112610321714680.00%1150810.600000300007000.00%0013000.1200101000
Team Total or Average700274437711-161266110857690175656096915.60%4851111215.8752801329847469153732619556.96%16754343461211.2813877252223
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PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Dan VladarMarlies (Tor)73210.8763.964090127218122000.000077001
Team Total or Average73210.8763.964090127218122000.000077001


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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 ErneMarlies (Tor)LW/RW231995-04-20No210 Lbs6 ft1NoNoNo1RFAPro & Farm850,000$0$0$NoLink
Adam Ollas MattssonMarlies (Tor)D221996-07-30Yes216 Lbs6 ft5NoNoNo3RFAPro & Farm500,000$0$0$NoLink
Adrian KempeMarlies (Tor)LW/RW221996-09-13No202 Lbs6 ft2NoNoNo1RFAPro & Farm900,000$0$0$NoLink
Dan VladarMarlies (Tor)G211997-08-20No185 Lbs6 ft5NoNoNo2RFAPro & Farm650,000$0$0$NoLink
Dmitrij JaskinMarlies (Tor)RW241994-03-23No196 Lbs6 ft2NoNoNo1RFAPro & Farm1,000,000$0$0$NoLink
Eric ComrieMarlies (Tor)G231995-07-05No175 Lbs6 ft1NoNoNo1RFAPro & Farm800,000$0$0$NoLink
Eric CornelMarlies (Tor)C/RW221996-04-10Yes194 Lbs6 ft2NoNoNo2RFAPro & Farm850,000$0$0$NoLink
Frederik GauthierMarlies (Tor)C231995-04-26No238 Lbs6 ft5NoNoNo1RFAPro & Farm900,000$0$0$NoLink
Ivan BarbashevMarlies (Tor)C/LW231995-12-14No180 Lbs6 ft0NoNoNo1RFAPro & Farm850,000$0$0$NoLink
Jack DoughertyMarlies (Tor)D221996-05-24Yes186 Lbs6 ft1NoNoNo2RFAPro & Farm800,000$0$0$NoLink
Jack FlinnMarlies (Tor)G231995-12-20No223 Lbs6 ft8NoNoNo1RFAPro & Farm650,000$0$0$NoLink
Joe HickettsMarlies (Tor)D221996-05-03No175 Lbs5 ft8NoNoNo1RFAPro & Farm650,000$0$0$NoLink
Martin MarincinMarlies (Tor)D261992-02-18No210 Lbs6 ft4NoNoNo1RFAPro & Farm1,250,000$0$0$NoLink
Matt ReadMarlies (Tor)C/LW/RW311987-06-14No185 Lbs5 ft10NoNoNo1UFAPro & Farm3,625,000$0$0$NoLink
Matt Tennyson (Out of Payroll)Marlies (Tor)D271991-04-23No205 Lbs6 ft2NoNoNo2RFAPro & Farm650,000$0$0$YesLink
Nic PetanMarlies (Tor)C/LW/RW231995-03-21No179 Lbs5 ft9NoNoNo1RFAPro & Farm850,000$0$0$NoLink
Nicholas MerkleyMarlies (Tor)C/RW211997-05-23Yes194 Lbs5 ft10NoNoNo3RFAPro & Farm900,000$0$0$NoLink
Nikita SoshnikovMarlies (Tor)LW/RW251993-10-14No190 Lbs5 ft11NoNoNo2RFAPro & Farm800,000$0$0$NoLink
Oliver KylingtonMarlies (Tor)D211997-05-19No183 Lbs6 ft0NoNoNo1RFAPro & Farm800,000$0$0$NoLink
Petteri LindbohmMarlies (Tor)D251993-09-22No198 Lbs6 ft3NoNoNo1RFAPro & Farm1,000,000$0$0$NoLink
Phil VaroneMarlies (Tor)C/LW281990-12-03No193 Lbs5 ft10NoNoNo2UFAPro & Farm650,000$0$0$NoLink
Reece WillcoxMarlies (Tor)D241994-03-19Yes184 Lbs6 ft3NoNoNo2RFAPro & Farm500,000$0$0$NoLink
Roland McKeownMarlies (Tor)D231996-01-19No195 Lbs6 ft1NoNoNo2RFAPro & Farm800,000$0$0$NoLink
Ryan MacInnisMarlies (Tor)C221996-02-13No185 Lbs6 ft3NoNoNo2RFAPro & Farm850,000$0$0$NoLink
Samuel MontembeaultMarlies (Tor)G221996-10-30Yes192 Lbs6 ft3NoNoNo3RFAPro & Farm700,000$0$0$NoLink
Sergei BoikovMarlies (Tor)D221996-01-23Yes195 Lbs6 ft2NoNoNo2RFAPro & Farm500,000$0$0$NoLink
Timothy LiljegrenMarlies (Tor)D191999-04-30Yes192 Lbs6 ft0NoNoNo3ELCPro & Farm900,000$0$0$NoLink
Travis DermottMarlies (Tor)D221996-12-21No215 Lbs6 ft0NoNoNo2RFAPro & Farm850,000$0$0$NoLink
Ty RattieMarlies (Tor)RW251993-02-05No178 Lbs6 ft0NoNoNo1RFAPro & Farm700,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2923.31195 Lbs6 ft11.66887,069$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Adrian KempeDmitrij Jaskin40122
2Matt ReadPhil Varone30122
3Ivan BarbashevNicholas MerkleyNikita Soshnikov20122
4Adam ErneNic PetanAdrian Kempe10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Travis Dermott40122
230122
3Roland McKeown20122
4Travis Dermott10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Adrian KempeDmitrij Jaskin60122
2Matt ReadPhil Varone40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Travis Dermott60122
240122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Adrian Kempe60122
2Dmitrij JaskinPhil Varone40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Travis Dermott60122
240122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Adrian Kempe60122Travis Dermott60122
24012240122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Adrian Kempe60122
2Dmitrij JaskinPhil Varone40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Travis Dermott60122
240122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Adrian KempeDmitrij JaskinTravis Dermott
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Adrian KempeDmitrij JaskinTravis Dermott
Extra Forwards
Normal PowerPlayPenalty Kill
Frederik Gauthier, Nicholas Merkley, Ivan BarbashevFrederik Gauthier, Nicholas MerkleyIvan Barbashev
Extra Defensemen
Normal PowerPlayPenalty Kill
Roland McKeown, , Roland McKeown,
Penalty Shots
Adrian Kempe, , Dmitrij Jaskin, Phil Varone,
Goalie
#1 : , #2 :


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3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
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
1Americans43100000402614321000003120111100000096360.750406610600741251104172595615654161284324985360.00%7271.43%140986547.28%37075349.14%456108641.99%1038618975411877434
2Barracuda10100000410-60000000000010100000410-600.000461000741251104385956156541647181472150.00%220.00%040986547.28%37075349.14%456108641.99%1038618975411877434
3Bears303000001525-101010000079-220200000816-800.000152540007412511048759561565416147611449000.00%7442.86%040986547.28%37075349.14%456108641.99%1038618975411877434
4Bruins513001002432-82110000010100302001001422-830.300243862007412511042215956156541616757241059444.44%7271.43%040986547.28%37075349.14%456108641.99%1038618975411877434
5Checkers11000000826110000008260000000000021.0008132100741251104375956156541642144173266.67%20100.00%140986547.28%37075349.14%456108641.99%1038618975411877434
6Condors11000000743000000000001100000074321.000712190074125110439595615654163414613100.00%3166.67%040986547.28%37075349.14%456108641.99%1038618975411877434
7Crunch413000001823-51010000057-2312000001316-320.25018314900741251104132595615654161445212978562.50%6183.33%040986547.28%37075349.14%456108641.99%1038618975411877434
8Devils321000002422211000000743211000001718-140.667243660107412511041235956156541612555176010660.00%6350.00%140986547.28%37075349.14%456108641.99%1038618975411877434
9Falcons1100000010910000000000011000000109121.000101727007412511044559561565416502411142150.00%3166.67%140986547.28%37075349.14%456108641.99%1038618975411877434
10Heat1100000010821100000010820000000000021.000101828007412511043259561565416441961522100.00%3166.67%040986547.28%37075349.14%456108641.99%1038618975411877434
11IceCaps43001000291712220000001459210010001512381.00029487701741251104145595615654168627301129444.44%10640.00%040986547.28%37075349.14%456108641.99%1038618975411877434
12IceHogs1010000069-31010000069-30000000000000.0006814007412511044159561565416501725202150.00%550.00%040986547.28%37075349.14%456108641.99%1038618975411877434
13Monsters1010000059-41010000059-40000000000000.0005914007412511044559561565416461512212150.00%110.00%040986547.28%37075349.14%456108641.99%1038618975411877434
14Penguins1010000038-51010000038-50000000000000.00035800741251104405956156541630101023300.00%000.00%040986547.28%37075349.14%456108641.99%1038618975411877434
15Phantoms211000001214-200000000000211000001214-220.50012213300741251104865956156541672208435480.00%4250.00%040986547.28%37075349.14%456108641.99%1038618975411877434
16Pirates22000000177101100000012571100000052341.000172845007412511048059561565416551723439777.78%40100.00%140986547.28%37075349.14%456108641.99%1038618975411877434
17Reign11000000981110000009810000000000021.000913220074125110439595615654164410102422100.00%5260.00%140986547.28%37075349.14%456108641.99%1038618975411877434
18Senators301001011317-41010000046-220000101911-220.3331322350074125110410759561565416108254617228.57%20100.00%040986547.28%37075349.14%456108641.99%1038618975411877434
19Sound Tigers211000001719-210100000711-411000000108220.500172946007412511049059561565416974220265480.00%10730.00%140986547.28%37075349.14%456108641.99%1038618975411877434
Total48202202301311325-1423111100100161148132591102201150177-27480.5003115148251174125110418765956156541617946163299871035856.31%1024654.90%740986547.28%37075349.14%456108641.99%1038618975411877434
21Wild11000000954110000009540000000000021.000914230074125110451595615654161884213133.33%2150.00%040986547.28%37075349.14%456108641.99%1038618975411877434
22Wolf Pack403001001732-15302001001422-810100000310-710.12517304700741251104145595615654161543837868337.50%11372.73%040986547.28%37075349.14%456108641.99%1038618975411877434
23Wolves10100000511-60000000000010100000511-600.00051015007412511043859561565416651912164375.00%110.00%040986547.28%37075349.14%456108641.99%1038618975411877434
24Wolves10001000981000000000001000100098121.00091524007412511044359561565416411121622100.00%110.00%040986547.28%37075349.14%456108641.99%1038618975411877434
_Since Last GM Reset48202202301311325-1423111100100161148132591102201150177-27480.5003115148251174125110418765956156541617946163299871035856.31%1024654.90%740986547.28%37075349.14%456108641.99%1038618975411877434
_Vs Conference38151801301237244-718890010012210913207901201115135-20360.474237392629117412511041465595615654161355461227820814454.32%763060.53%540986547.28%37075349.14%456108641.99%1038618975411877434
_Vs Division227501201141122191053000007653231222012016569-4190.4321412333740174125110485759561565416688221117516472553.19%361169.44%240986547.28%37075349.14%456108641.99%1038618975411877434

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
4848OTL13115148251876179461632998711
All Games
GPWLOTWOTL SOWSOLGFGA
4820222301311325
Home Games
GPWLOTWOTL SOWSOLGFGA
2311110100161148
Visitor Games
GPWLOTWOTL SOWSOLGFGA
259112201150177
Last 10 Games
WLOTWOTL SOWSOL
440101
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1035856.31%1024654.90%7
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
59561565416741251104
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
40986547.28%37075349.14%456108641.99%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1038618975411877434


Last Played Games
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DayGame Visitor Team Score Home Team Score ST OT SO RI Link
2 - 2018-10-0310Wolf Pack9Marlies4LBoxScore
4 - 2018-10-0526Marlies1Crunch5LBoxScore
6 - 2018-10-0739IceCaps0Marlies7WBoxScore
8 - 2018-10-0954Marlies5Pirates2WBoxScore
10 - 2018-10-1174Devils4Marlies7WBoxScore
11 - 2018-10-1285Marlies3Bruins6LBoxScore
13 - 2018-10-14100Marlies4Senators5LXBoxScore
14 - 2018-10-15101Marlies7Crunch4WBoxScore
17 - 2018-10-18123Senators6Marlies4LBoxScore
20 - 2018-10-21145Americans8Marlies7LBoxScore
21 - 2018-10-22155Marlies9Americans6WBoxScore
23 - 2018-10-24169Marlies8IceCaps7WXBoxScore
25 - 2018-10-26181IceCaps5Marlies7WBoxScore
28 - 2018-10-29204Americans7Marlies11WBoxScore
30 - 2018-10-31221Marlies3Wolf Pack10LBoxScore
32 - 2018-11-02235Wolf Pack5Marlies3LBoxScore
34 - 2018-11-04245Marlies9Devils11LBoxScore
36 - 2018-11-06260Marlies7IceCaps5WBoxScore
38 - 2018-11-08272Bears9Marlies7LBoxScore
40 - 2018-11-10287Marlies5Wolves11LBoxScore
42 - 2018-11-12303Penguins8Marlies3LBoxScore
45 - 2018-11-15321Marlies6Bruins7LXBoxScore
48 - 2018-11-18335Checkers2Marlies8WBoxScore
50 - 2018-11-20350Marlies7Condors4WBoxScore
52 - 2018-11-22367Wild5Marlies9WBoxScore
54 - 2018-11-24381Marlies8Devils7WBoxScore
56 - 2018-11-26391Marlies2Phantoms6LBoxScore
58 - 2018-11-28401Monsters9Marlies5LBoxScore
60 - 2018-11-30418Marlies5Crunch7LBoxScore
62 - 2018-12-02432Heat8Marlies10WBoxScore
64 - 2018-12-04448Marlies4Barracuda10LBoxScore
65 - 2018-12-05461Reign8Marlies9WBoxScore
67 - 2018-12-07475Marlies10Phantoms8WBoxScore
70 - 2018-12-10493Sound Tigers11Marlies7LBoxScore
72 - 2018-12-12507Marlies10Sound Tigers8WBoxScore
74 - 2018-12-14522Marlies4Bears8LBoxScore
75 - 2018-12-15528Crunch7Marlies5LBoxScore
78 - 2018-12-18551Marlies10Falcons9WBoxScore
79 - 2018-12-19557Pirates5Marlies12WBoxScore
82 - 2018-12-22571Marlies5Bruins9LBoxScore
85 - 2018-12-25589IceHogs9Marlies6LBoxScore
88 - 2018-12-28611Marlies9Wolves8WXBoxScore
89 - 2018-12-29619Bruins5Marlies6WBoxScore
92 - 2019-01-01643Marlies4Bears8LBoxScore
93 - 2019-01-02651Bruins5Marlies4LBoxScore
97 - 2019-01-06680Americans5Marlies13WBoxScore
100 - 2019-01-09701Marlies5Senators6LXXBoxScore
102 - 2019-01-11710Wolf Pack8Marlies7LXBoxScore
105 - 2019-01-14731Marlies-Senators-
106 - 2019-01-15739Rampage-Marlies-
109 - 2019-01-18758Marlies-Wolf Pack-
111 - 2019-01-20768Moose-Marlies-
113 - 2019-01-22783Marlies-Checkers-
114 - 2019-01-23792Marlies-Penguins-
116 - 2019-01-25806Senators-Marlies-
118 - 2019-01-27825Marlies-Crunch-
120 - 2019-01-29836Checkers-Marlies-
124 - 2019-02-02858Marlies-Penguins-
125 - 2019-02-03866Crunch-Marlies-
129 - 2019-02-07896IceCaps-Marlies-
130 - 2019-02-08907Marlies-Gulls-
133 - 2019-02-11927Phantoms-Marlies-
135 - 2019-02-13944Marlies-Moose-
137 - 2019-02-15956Admirals-Marlies-
139 - 2019-02-17970Marlies-Pirates-
141 - 2019-02-19985Griffins-Marlies-
143 - 2019-02-21998Marlies-Moose-
Trade Deadline --- Trades can’t be done after this day is simulated!
145 - 2019-02-231018Phantoms-Marlies-
147 - 2019-02-251033Marlies-Pirates-
149 - 2019-02-271047Sound Tigers-Marlies-
151 - 2019-03-011057Marlies-Americans-
154 - 2019-03-041080Comets-Marlies-
158 - 2019-03-081110Senators-Marlies-
163 - 2019-03-131136Devils-Marlies-
166 - 2019-03-161159Devils-Marlies-
169 - 2019-03-191172Marlies-Stars-



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
15 0 - 0.00% 0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
1,532,704$ 2,507,500$ 1,912,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 1,530,364$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 69 14,664$ 1,011,816$




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
201848202202301311325-1423111100100161148132591102201150177-27483115148251174125110418765956156541617946163299871035856.31%1024654.90%740986547.28%37075349.14%456108641.99%1038618975411877434
Total Regular Season48202202301311325-1423111100100161148132591102201150177-27483115148251174125110418765956156541617946163299871035856.31%1024654.90%740986547.28%37075349.14%456108641.99%1038618975411877434