Toronto Marlies

GP: 76 | W: 48 | L: 20 | OTL: 8 | P: 104
GF: 248 | GA: 182 | PP%: 22.00% | PK%: 83.07%
GM : Guillaume Poulin | Morale : 74 | Team Overall : 63
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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
1Michael AmadioX97.00636090697871716381636867787373049650
2Troy TerryXX100.00616092707266666370636869786969060640
3Victor EjdsellXX100.00666078657261616273656568756262068630
4Sam SteelX100.00636074686663636476656766776060063630
5Nicolas RoyX100.00726078647160606078626565756161080620
6Sam CarrickX100.00616076656760606067626566756363063610
7Mason ShawX100.00504550605050506050606060605050075550
8Alex TrueX100.00504550605050506050606060605050033550
9Oscar FantenbergX99.00806393727770706765686673768888089690
10Joshua Mahura (R)X98.00646087747367677065736872787878065680
11Tucker PoolmanX100.00656078716966666665666670767373089650
12Dysin MayoX100.00504560655050506050605560555050084560
13Kale ClagueX100.00504550655050506050605560555050076550
14Logan StanleyX100.00504550655050506050605560555050084550
Scratches
1Jason ChimeraXX100.00816486718298986779687072809999013720
2Shawn MatthiasXX100.00716288688678786578656976798787020690
3Matt BeleskeyX100.00889571687775756275646670768686017670
4Johan FranzenXX100.00626093658660606265646665769595022650
5Dominic ToninatoX100.00676086677676766180646569757272031650
6Corey TroppXXHO676095687460606065626565758080020630
7Henrik SamuelssonXXXHO616077647160606062626260727272020610
8Hayden VerbeekX100.00504550605050506050606060605050030550
9Jeremiah AddisonX100.00504550605050506050606060605050019550
10Chase LangXXX100.00504550605050506050606060605050019550
11Matheson IacopelliX100.00504550605050506050606060605050068550
12Noah RodXXX100.00504550605050506050606060605050035550
13Niko MikkolaX100.00504550655050506050605560555050042550
14Axel AnderssonX100.00504550655050506050605560555050020550
TEAM AVERAGE99.7960557066646060626263636568656504861
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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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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
1Alexandar Georgiev98.0086848486868786878786807070084840
2Garret Sparks100.0082818186848484848484827373028820
Scratches
1Nick Schneider100.0074747476747474747474746060030730
TEAM AVERAGE99.338180808381828182828179686804780
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Joel Bouchard70646670726778CAN443500,000$


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1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
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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
# 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
1Oscar FantenbergToronto Marlies (TOR)D764450944625619014812725211211817.46%143188824.841315286421343710227810.00%013594131.001110523685
2Tucker PoolmanToronto Marlies (TOR)D7647449156129751011292379911219.83%115162821.4399185919643714204830.00%012286031.120031111357
3Joshua MahuraToronto Marlies (TOR)D78362965108135701061888210419.15%110149619.18104146014440441431140.00%18570030.8712033843
4Troy TerryToronto Marlies (TOR)C/RW78253863121025088962026111712.38%43146418.7861319292090003584149.58%1199036000.8601127324
5Michael AmadioToronto Marlies (TOR)C559354481355987166441155.42%26111020.193710261360118971054.37%85910014010.7902001102
6Sam SteelToronto Marlies (TOR)C5819244315967092991534511112.42%21103817.9031417560112691348.40%6269230000.8303275214
7Victor EjdsellToronto Marlies (TOR)C/LW6116264254915108961534910410.46%42125020.5029112416103381334253.88%4516528010.6703012144
8Nicolas RoyToronto Marlies (TOR)C761323361716711513811617356987.51%30130817.2214514920113442252.84%58110030000.55012417014
9Dominic ToninatoToronto Marlies (TOR)C326293577538739527766.32%2375523.61077128004441201050.36%7034918000.9301001225
10Sam CarrickToronto Marlies (TOR)C59111425178975678712036729.17%1293915.921011140112421243.02%1795926000.53002211024
11Johan FranzenToronto Marlies (TOR)LW/RW2851520120026316621587.58%1164122.93167178102221090145.61%573513010.6225000111
12Matheson IacopelliToronto Marlies (TOR)RW65613191538067748135537.41%12115117.72246161110001151149.12%572621000.3300000000
13Dysin MayoToronto Marlies (TOR)D76015151738057885524230.00%74153620.22044151650110169000.00%0945000.2000000010
14Jordan NolanToronto Maple LeafsC/LW/RW194913-3614537175021328.00%737419.7113412510000301053.57%56303000.6902621111
15Hayden VerbeekToronto Marlies (TOR)C433811733541456715374.48%1476217.740222440000262043.66%2842814000.2901001000
16Matt BeleskeyToronto Marlies (TOR)LW1935841224050275315265.66%1238320.191126450112541149.06%106226000.4213323010
17Noah RodToronto Marlies (TOR)C/LW/RW37178-338048396013361.67%1373319.8203312930001300025.93%542416000.2200000001
18Jeremiah AddisonToronto Marlies (TOR)LW23156215532302916163.45%1039817.320003210000150051.85%27178000.3000010000
19Niko MikkolaToronto Marlies (TOR)D44145-112032522512144.00%3767315.3000004300025400100.00%1828000.1500000000
20Mason ShawToronto Marlies (TOR)C661454471542394013302.50%95738.690112250000170136.08%97129000.1701012000
21Chase LangToronto Marlies (TOR)C/LW/RW29055-320046295115230.00%652618.15011865000180053.85%262415000.1900000000
22Logan StanleyToronto Marlies (TOR)D75044-744039773719240.00%52101313.51000120000017000.00%11626000.0800000000
23Alex TrueToronto Marlies (TOR)C430442200382111990.00%53307.680001110000110026.09%13869000.2400000000
24Kale ClagueToronto Marlies (TOR)D66123-640046573616212.78%4196714.66000022000154100.00%21046000.0600000000
25Axel AnderssonToronto Marlies (TOR)D23011-36014193210.00%62249.750000200007000.00%018000.0900000000
Team Total or Average13052524136652301523745152416612403857143010.49%8742317117.7653941474012111122133681766472249.36%442511656991120.57526293188383345
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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
1Juuse SarosToronto Maple Leafs51331250.9302.203031211111580908410.76221515585
2Alexandar GeorgievToronto Marlies (TOR)2413730.9222.4213652155708387210.800102254421
3Garret SparksToronto Marlies (TOR)42100.8912.8221320109252000.0000317001
4Nick SchneiderToronto Marlies (TOR)30000.69411.795600113614000.0000041000
Team Total or Average82482080.9232.4146666218724161361620.77431761179107


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1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
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
Alex TrueToronto Marlies (TOR)C211997-07-17 3:32:57 PMNo200 Lbs6 ft5NoNoNo1ELCPro & Farm763,333$0$0$No
Alexandar GeorgievToronto Marlies (TOR)G231996-02-10 1:12:18 PMNo176 Lbs6 ft1NoNoNo3RFAPro & Farm792,500$0$0$No
Axel AnderssonToronto Marlies (TOR)D192000-02-10 3:36:40 AMNo174 Lbs6 ft0NoNoNo3ELCPro & Farm825,833$0$0$No
Chase LangToronto Marlies (TOR)C/LW/RW221996-09-13 3:51:52 PMNo187 Lbs6 ft1NoNoNo1ELCPro & Farm686,666$0$0$No
Corey TroppToronto Marlies (TOR)LW/RW291989-07-25 5:28:37 AMNo185 Lbs6 ft0NoNoYes1UFAPro & Farm1$0$0$No
Dominic ToninatoToronto Marlies (TOR)C251994-03-09 3:18:24 PMNo165 Lbs6 ft1NoNoNo1RFAPro & Farm925,000$0$0$No
Dysin MayoToronto Marlies (TOR)D221996-08-17 3:53:12 PMNo185 Lbs6 ft0NoNoYes1ELCPro & Farm678,333$0$0$No
Garret SparksToronto Marlies (TOR)G251993-06-28 9:47:34 AMNo201 Lbs6 ft2NoNoYes3RFAPro & Farm675,000$0$0$No
Hayden VerbeekToronto Marlies (TOR)C211997-10-17 3:17:44 AMNo177 Lbs5 ft9NoNoNo1ELCPro & Farm753,333$0$0$No
Henrik SamuelssonToronto Marlies (TOR)C/LW/RW251994-02-07 11:21:20 AMNo209 Lbs6 ft3NoNoYes2RFAPro & Farm1$0$0$No
Jason ChimeraToronto Marlies (TOR)LW/RW391979-05-02 6:29:38 PMNo216 Lbs6 ft3NoNoYes1UFAPro & Farm1$0$0$No
Jeremiah AddisonToronto Marlies (TOR)LW221996-10-21 1:10:25 PMNo183 Lbs6 ft0NoNoNo2ELCPro & Farm720,000$0$0$No
Johan FranzenToronto Marlies (TOR)LW/RW391979-12-23 6:29:38 PMNo231 Lbs6 ft2NoNoYes1UFAPro & Farm3,954,545$0$0$No
Joshua MahuraToronto Marlies (TOR)D201998-05-05 2:33:28 PMYes179 Lbs6 ft0NoNoNo3ELCPro & Farm745,000$0$0$No
Kale ClagueToronto Marlies (TOR)D201998-06-05 8:14:53 AMNo176 Lbs6 ft0NoNoNo3ELCPro & Farm761,666$0$0$No
Logan StanleyToronto Marlies (TOR)D201998-05-26 3:35:35 AMNo216 Lbs6 ft6NoNoNo3ELCPro & Farm863,333$0$0$No
Mason ShawToronto Marlies (TOR)C201998-11-03 3:40:17 AMNo181 Lbs5 ft9NoNoNo3ELCPro & Farm792,500$0$0$No
Matheson IacopelliToronto Marlies (TOR)RW241994-05-15 1:14:30 PMNo207 Lbs6 ft2NoNoNo1RFAPro & Farm742,500$0$0$No
Matt BeleskeyToronto Marlies (TOR)LW301988-06-07 12:29:38 AMNo203 Lbs6 ft0NoNoYes1UFAPro & Farm3,800,000$0$0$No
Michael AmadioToronto Marlies (TOR)C221996-05-13 2:05:51 PMNo227 Lbs6 ft3NoNoNo1ELCPro & Farm717,500$0$0$No
Nick SchneiderToronto Marlies (TOR)G211997-07-21 5:05:23 AMNo181 Lbs6 ft2NoNoNo1ELCFarm Only675,000$0$0$No
Nicolas RoyToronto Marlies (TOR)C221997-02-05 1:06:37 PMNo195 Lbs6 ft4NoNoNo2ELCPro & Farm720,000$0$0$No
Niko MikkolaToronto Marlies (TOR)D221996-04-27 8:16:00 AMNo185 Lbs6 ft4NoNoNo2ELCPro & Farm842,500$0$0$No
Noah RodToronto Marlies (TOR)C/LW/RW221996-06-07 3:44:09 PMNo192 Lbs6 ft1NoNoYes2ELCPro & Farm763,333$0$0$No
Oscar FantenbergToronto Marlies (TOR)D271991-10-07 1:13:02 PMNo203 Lbs6 ft0NoNoYes1RFAPro & Farm650,000$0$0$No
Sam CarrickToronto Marlies (TOR)C271992-02-04 3:52:11 PMNo187 Lbs6 ft0NoNoYes1RFAPro & Farm650,000$0$0$No
Sam SteelToronto Marlies (TOR)C211998-02-03 8:13:19 AMNo176 Lbs5 ft11NoNoNo3ELCPro & Farm863,333$0$0$No
Shawn MatthiasToronto Marlies (TOR)C/LW311988-02-19 12:29:38 AMNo231 Lbs6 ft4NoNoYes1UFAPro & Farm1$0$0$No
Troy TerryToronto Marlies (TOR)C/RW211997-09-10 2:48:00 PMNo161 Lbs5 ft11NoNoNo2ELCPro & Farm925,000$0$0$No
Tucker PoolmanToronto Marlies (TOR)D251993-06-08 1:09:29 PMNo198 Lbs6 ft2NoNoNo2RFAPro & Farm775,000$0$0$No
Victor EjdsellToronto Marlies (TOR)C/LW231995-06-06 1:03:43 PMNo214 Lbs6 ft5NoNoNo1RFAPro & Farm833,750$0$0$No
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3124.19194 Lbs6 ft11.74867,579$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Michael Amadio40122
2Troy TerrySam Steel30122
3Nicolas RoyVictor EjdsellSam Carrick20122
4Nicolas Roy10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Oscar FantenbergJoshua Mahura40122
2Tucker PoolmanDysin Mayo30122
3Logan StanleyKale Clague20122
4Oscar FantenbergJoshua Mahura10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Michael Amadio60122
2Victor EjdsellTroy Terry40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Oscar FantenbergJoshua Mahura60122
2Tucker PoolmanDysin Mayo40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
160122
2Michael AmadioTroy Terry40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Oscar FantenbergJoshua Mahura60122
2Tucker PoolmanDysin Mayo40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
160122Oscar FantenbergJoshua Mahura60122
240122Tucker PoolmanDysin Mayo40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
160122
2Michael AmadioTroy Terry40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Oscar FantenbergJoshua Mahura60122
2Tucker PoolmanDysin Mayo40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Michael AmadioOscar FantenbergJoshua Mahura
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Michael AmadioOscar FantenbergJoshua Mahura
Extra Forwards
Normal PowerPlayPenalty Kill
Alex True, Mason Shaw, Sam SteelAlex True, Mason ShawSam Steel
Extra Defensemen
Normal PowerPlayPenalty Kill
Logan Stanley, Kale Clague, Tucker PoolmanLogan StanleyKale Clague, Tucker Poolman
Penalty Shots
, , Michael Amadio, Troy Terry, Sam Steel
Goalie
#1 : Alexandar Georgiev, #2 : Garret Sparks
Custom OT Lines Forwards
, , Michael Amadio, Troy Terry, Sam Steel, Victor Ejdsell, Victor Ejdsell, Nicolas Roy, Sam Carrick, , Alex True
Custom OT Lines Defensemen
Oscar Fantenberg, Joshua Mahura, Tucker Poolman, Dysin Mayo, Logan Stanley


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
1Belleville Senators1272001113523126600000022913612001111314-1180.75035528701828474123807557887515236712123424235822.86%37586.49%1764148751.38%759157148.31%46694049.57%162498717416601248618
2Binghamton Devils624000001322-93210000098130300000414-1040.3331318310082847412179755788751521866912011830516.67%20670.00%0764148751.38%759157148.31%46694049.57%162498717416601248618
3Bridgeport Sound Tigers20100010550100000102111010000034-120.500561100828474126675578875152562133459111.11%9188.89%0764148751.38%759157148.31%46694049.57%162498717416601248618
4Charlotte Checkers431000001798211000009722200000082660.750172340108284741210975578875152119451077011327.27%11372.73%0764148751.38%759157148.31%46694049.57%162498717416601248618
5Cleveland Monsters843000102621543100000189941200010812-4100.62526396510828474122457557887515225410218114920420.00%28292.86%0764148751.38%759157148.31%46694049.57%162498717416601248618
6Hartford Wolf Pack211000003301010000013-21100000020220.500358018284741260755788751525710184110110.00%40100.00%1764148751.38%759157148.31%46694049.57%162498717416601248618
7Hershey Bears22000000862110000005411100000032141.0008142200828474126975578875152723559447342.86%7271.43%0764148751.38%759157148.31%46694049.57%162498717416601248618
8Laval Rocket10300320225214530010011611550002201910-1160.800254166008284741229275578875152306105160183411024.39%35682.86%3764148751.38%759157148.31%46694049.57%162498717416601248618
9Lehigh Valley Phantoms2110000068-2110000005321010000015-420.5006101600828474125275578875152693432344125.00%5260.00%0764148751.38%759157148.31%46694049.57%162498717416601248618
10Manitoba Moose40200110814-6200001105502020000039-630.3758101800828474121307557887515211843617016318.75%13284.62%0764148751.38%759157148.31%46694049.57%162498717416601248618
11Providence Bruins22000000835110000004131100000042241.0008122000828474127175578875152722859397114.29%12375.00%0764148751.38%759157148.31%46694049.57%162498717416601248618
12Rochester Americans650010003212203300000015411320010001789121.0003250820082847412167755788751521806814011717423.53%22481.82%2764148751.38%759157148.31%46694049.57%162498717416601248618
13Springfield Thunderbirds21000001642110000004131000000123-130.7506101600828474126575578875152602037527114.29%11190.91%0764148751.38%759157148.31%46694049.57%162498717416601248618
14Syracuse Crunch651000003212203300000015411321000001789100.8333248800082847412172755788751522066411911814535.71%22386.36%3764148751.38%759157148.31%46694049.57%162498717416601248618
Total7640200444424818266382850112114277653812150332310610511040.68424838062822828474122314755788751522382848150614572505522.00%2544383.07%12764148751.38%759157148.31%46694049.57%162498717416601248618
16Utica Comets63300000181443210000086231200000108260.50018314900828474121767557887515220868769513430.77%13284.62%1764148751.38%759157148.31%46694049.57%162498717416601248618
17Wilkes-Barre/Scranton Penguins21100000651110000004131010000024-220.5006111700828474128175578875152521570409111.11%5180.00%1764148751.38%759157148.31%46694049.57%162498717416601248618
_Since Last GM Reset7640200444424818266382850112114277653812150332310610511040.68424838062822828474122314755788751522382848150614572505522.00%2544383.07%12764148751.38%759157148.31%46694049.57%162498717416601248618
_Vs Conference603314043241971385930243010111105654309110331387825850.70819730850502828474121830755788751521891658115711682034522.17%2023682.18%12764148751.38%759157148.31%46694049.57%162498717416601248618
_Vs Division3825100431313875631919201001763046196803312624517660.868138213351018284741211477557887515211914067497511212923.97%1392284.17%9764148751.38%759157148.31%46694049.57%162498717416601248618

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
76104W2248380628231423828481506145722
All Games
GPWLOTWOTL SOWSOLGFGA
7640204444248182
Home Games
GPWLOTWOTL SOWSOLGFGA
38285112114277
Visitor Games
GPWLOTWOTL SOWSOLGFGA
3812153323106105
Last 10 Games
WLOTWOTL SOWSOL
630010
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2505522.00%2544383.07%12
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
7557887515282847412
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
764148751.38%759157148.31%46694049.57%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
162498717416601248618


Last Played Games
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DayGame Visitor Team Score Home Team Score ST OT SO RI Link
3 - 2018-09-181Toronto Marlies7Utica Comets2WBoxScore
4 - 2018-09-1917Toronto Marlies2Binghamton Devils3LBoxScore
6 - 2018-09-2127Cleveland Monsters2Toronto Marlies3WBoxScore
11 - 2018-09-2645Utica Comets2Toronto Marlies4WBoxScore
12 - 2018-09-2760Utica Comets3Toronto Marlies1LBoxScore
17 - 2018-10-0274Toronto Marlies6Rochester Americans2WBoxScore
18 - 2018-10-0383Hartford Wolf Pack3Toronto Marlies1LBoxScore
21 - 2018-10-06100Laval Rocket4Toronto Marlies5WXBoxScore
24 - 2018-10-09107Syracuse Crunch1Toronto Marlies3WBoxScore
31 - 2018-10-16141Toronto Marlies2Cleveland Monsters1WBoxScore
38 - 2018-10-23183Toronto Marlies0Belleville Senators2LBoxScore
39 - 2018-10-24196Toronto Marlies3Belleville Senators4LBoxScore
42 - 2018-10-27212Toronto Marlies2Laval Rocket1WXBoxScore
45 - 2018-10-30225Toronto Marlies4Belleville Senators1WBoxScore
46 - 2018-10-31240Binghamton Devils3Toronto Marlies1LBoxScore
47 - 2018-11-01250Binghamton Devils4Toronto Marlies5WBoxScore
52 - 2018-11-06266Toronto Marlies4Cleveland Monsters3WXXBoxScore
54 - 2018-11-08293Cleveland Monsters3Toronto Marlies1LBoxScore
57 - 2018-11-11301Toronto Marlies1Cleveland Monsters4LBoxScore
60 - 2018-11-14320Wilkes-Barre/Scranton Penguins1Toronto Marlies4WBoxScore
61 - 2018-11-15334Lehigh Valley Phantoms3Toronto Marlies5WBoxScore
64 - 2018-11-18341Providence Bruins1Toronto Marlies4WBoxScore
67 - 2018-11-21363Laval Rocket1Toronto Marlies2WBoxScore
68 - 2018-11-22378Belleville Senators2Toronto Marlies5WBoxScore
71 - 2018-11-25384Syracuse Crunch2Toronto Marlies3WBoxScore
73 - 2018-11-27397Toronto Marlies1Manitoba Moose6LBoxScore
74 - 2018-11-28405Toronto Marlies2Manitoba Moose3LBoxScore
78 - 2018-12-02425Binghamton Devils1Toronto Marlies3WBoxScore
80 - 2018-12-04441Toronto Marlies2Laval Rocket1WXBoxScore
81 - 2018-12-05450Toronto Marlies2Laval Rocket3LXBoxScore
85 - 2018-12-09464Belleville Senators3Toronto Marlies7WBoxScore
87 - 2018-12-11481Toronto Marlies5Rochester Americans4WXBoxScore
90 - 2018-12-14504Charlotte Checkers1Toronto Marlies5WBoxScore
94 - 2018-12-18521Toronto Marlies1Binghamton Devils4LBoxScore
95 - 2018-12-19535Toronto Marlies1Syracuse Crunch2LBoxScore
96 - 2018-12-20548Charlotte Checkers6Toronto Marlies4LBoxScore
99 - 2018-12-23552Utica Comets1Toronto Marlies3WBoxScore
101 - 2018-12-25568Toronto Marlies6Rochester Americans2WBoxScore
102 - 2018-12-26574Rochester Americans1Toronto Marlies8WBoxScore
109 - 2019-01-02618Toronto Marlies5Charlotte Checkers1WBoxScore
110 - 2019-01-03631Toronto Marlies3Charlotte Checkers1WBoxScore
113 - 2019-01-06647Toronto Marlies1Cleveland Monsters4LBoxScore
115 - 2019-01-08656Toronto Marlies2Belleville Senators3LXXBoxScore
116 - 2019-01-09674Toronto Marlies2Belleville Senators3LXBoxScore
122 - 2019-01-15686Laval Rocket2Toronto Marlies1LXXBoxScore
123 - 2019-01-16697Laval Rocket3Toronto Marlies5WBoxScore
126 - 2019-01-19714Belleville Senators1Toronto Marlies2WBoxScore
130 - 2019-01-23735Springfield Thunderbirds1Toronto Marlies4WBoxScore
131 - 2019-01-24753Belleville Senators2Toronto Marlies5WBoxScore
134 - 2019-01-27763Toronto Marlies2Hartford Wolf Pack0WBoxScore
136 - 2019-01-29773Toronto Marlies4Providence Bruins2WBoxScore
137 - 2019-01-30788Toronto Marlies2Springfield Thunderbirds3LXXBoxScore
139 - 2019-02-01805Syracuse Crunch1Toronto Marlies9WBoxScore
141 - 2019-02-03808Manitoba Moose2Toronto Marlies3WXXBoxScore
143 - 2019-02-05817Toronto Marlies12Syracuse Crunch4WBoxScore
144 - 2019-02-06832Toronto Marlies4Syracuse Crunch2WBoxScore
148 - 2019-02-10850Manitoba Moose3Toronto Marlies2LXBoxScore
151 - 2019-02-13868Cleveland Monsters3Toronto Marlies9WBoxScore
155 - 2019-02-17893Toronto Marlies2Laval Rocket3LXXBoxScore
157 - 2019-02-19899Toronto Marlies1Laval Rocket2LXBoxScore
159 - 2019-02-21927Bridgeport Sound Tigers1Toronto Marlies2WXXBoxScore
160 - 2019-02-22931Belleville Senators0Toronto Marlies1WBoxScore
164 - 2019-02-26945Toronto Marlies3Hershey Bears2WBoxScore
165 - 2019-02-27963Toronto Marlies1Lehigh Valley Phantoms5LBoxScore
166 - 2019-02-28968Toronto Marlies2Wilkes-Barre/Scranton Penguins4LBoxScore
169 - 2019-03-03977Toronto Marlies3Bridgeport Sound Tigers4LBoxScore
172 - 2019-03-06994Rochester Americans2Toronto Marlies3WBoxScore
173 - 2019-03-071011Rochester Americans1Toronto Marlies4WBoxScore
178 - 2019-03-121029Toronto Marlies1Utica Comets2LBoxScore
179 - 2019-03-131044Laval Rocket1Toronto Marlies3WBoxScore
184 - 2019-03-181072Hershey Bears4Toronto Marlies5WBoxScore
185 - 2019-03-191074Toronto Marlies2Utica Comets4LBoxScore
186 - 2019-03-201093Toronto Marlies1Binghamton Devils7LBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
190 - 2019-03-241108Toronto Marlies2Belleville Senators1WXXBoxScore
193 - 2019-03-271128Belleville Senators1Toronto Marlies2WBoxScore
194 - 2019-03-281145Cleveland Monsters1Toronto Marlies5WBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price4028
Attendance64,32732,155
Attendance PCT84.64%84.62%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
0 2539 - 84.63% 132,538$5,036,459$3000110

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
2,631,513$ 2,689,494$ 1,416,957$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
13,863$ 2,131,462$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 16,441$ 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
Regular Season
20187640200444424818266382850112114277653812150332310610518024838062822828474122314755788751522382848150614572505522.00%2544383.07%12764148751.38%759157148.31%46694049.57%162498717416601248618
201876402004444248182663828501121142776538121503323106105110424838062822828474122314755788751522382848150614572505522.00%2544383.07%12764148751.38%759157148.31%46694049.57%162498717416601248618
Total Regular Season15280400888849636413276561002242284154130762430066462122102184496760125644164168148244628151015761502104476416963012291450011022.00%5088683.07%241528297451.38%1518314248.31%932188049.57%324919753482132024961236