TORONTO Marlies

GP: 79 | W: 41 | L: 36 | OTL: 2 | P: 84
GF: 331 | GA: 207 | PP%: 22.41% | PK%: 85.71%
GM : Maxime Joseph | Morale : 99 | Team Overall : 60
Next Games #1031 vs PROVIDENCE Bruins
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
1Tommy Wingels0XX100.008444736971789265586465667068613981710
2Jordan Szwarz0X100.006043736369718165316463636352515381650
3Brandon Mashinter0X100.007243706087568157505857605753523581630
4Justin Bailey0X100.006343756284696658305561666352517184630
5Jean-Sebastien Dea0X100.005346636062639262306260606150504386620
6Luke Johnson0X100.006045646069659057675657605750504386620
7Mark McNeill0XX100.006443696080596658675661606150508080610
8Yannick Veilleux0X100.006447606078556952505252605250505980580
9Jiri Sekac0X100.005938806970464758315550595360497183570
10Lucas Lessio0X100.005737746775454557315154615958477980560
11Louis-Marc Aubry0X100.005441666484504554435051515264615588560
12Derrick Pouliot0X100.006843806774818871306461616556538588680
13Matt Bartkowski0X100.007140836372743566305757636260553981610
14Chris Butler0X100.006142755273588459305149635666583883610
15Jamie McBain0X100.005943725072617757305146605364575483590
16Zach Trotman0X100.006742745183616957304950605753524180590
17Philip Samuelsson0X100.006244675074519355304945605251515780580
18Julian Melchiori0X100.006241765086516655304946605351515489570
Scratches
1Phil Lane (R)0X100.005540656581484052304649505160437166530
2Sebastian Collberg (R)0X100.004635807067454052304946505156518774530
TEAM AVERAGE100.00624272617659685838545460575652588260
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
1Reto Berra100.00746982887577757575737156654780670
2Vitek Vanecek (R)100.00666666746864696767666450584480590
Scratches
1Magnus Hellberg100.00545469896557616160595864565527560
TEAM AVERAGE100.0065637284696668686766645760496261
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Bob Hartley71717474797954CAN5841,267,000$


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
1Jean-Sebastien DeaTORONTO Marlies (TOR)C7950571076026106314135310126914.16%34150919.1139122513410181987152.20%199600071.4200101558
2Jordan SzwarzTORONTO Marlies (TOR)RW795248100572001318839811829213.07%17129416.395712481430000114455.56%9000021.5400000862
3Matt BartkowskiTORONTO Marlies (TOR)D791673894184018988212451337.55%113167721.246915731430220184400.00%000001.0600000372
4Brandon MashinterTORONTO Marlies (TOR)LW7934518561640192723219620310.59%16148618.8146102913601171716070.43%11500111.1400000358
5Luke JohnsonTORONTO Marlies (TOR)C7933457864120451642738917112.09%16123215.61291135138202112113268.90%174300031.2700000244
6Mark McNeillTORONTO Marlies (TOR)C/RW7936367229280911353469724210.40%21121615.407613291330001673066.71%76900011.1800000353
7Justin BaileyTORONTO Marlies (TOR)RW642331544916051431976214211.68%1085213.32000030005995350.00%4800001.2702000262
8Chris ButlerTORONTO Marlies (TOR)D7993948413801124912040707.50%81152819.35257321220112170000.00%000000.6300000101
9Derrick PouliotTORONTO Marlies (TOR)D569354464535744178284011.54%47123322.03369321110110188100.00%000000.7100010214
10Yannick VeilleuxTORONTO Marlies (TOR)LW79202444302609455205461579.76%13100212.6946103013402271932161.97%7100000.8800000023
11Philip SamuelssonTORONTO Marlies (TOR)D79103141604951153782205212.20%66119915.18101523000051100.00%000000.6800001021
12Tommy WingelsTORONTO Marlies (TOR)C/RW322414383332052261764511013.64%341913.1101125000031087.18%3900021.8100000241
13Lucas LessioTORONTO Marlies (TOR)LW4212253737601740148431258.11%954212.9200001000041068.42%3800001.3600000001
14Zach TrotmanTORONTO Marlies (TOR)D757293642595127429732707.22%72124016.54033746000188300.00%100000.5800001112
15Jamie McBainTORONTO Marlies (TOR)D75231333244089349232542.17%74142619.02156261370003162000.00%000000.4600000000
16Julian MelchioriTORONTO Marlies (TOR)D355232840200511536132213.89%2861817.6610112000382100.00%000000.9100000011
17Jiri SekacTORONTO Marlies (TOR)LW3310172722140642814434926.94%549815.11011260000122144.74%3800001.0800000103
18Brett ConnollyTORONTO Maple LeafsRW1431316141007176416474.69%322416.03033827000060150.00%1200001.4300000201
19Brian GibbonsTORONTO Maple LeafsC/LW148715122015329425878.51%334824.860117340001591054.01%37400000.8600000022
20Louis-Marc AubryTORONTO Marlies (TOR)C123361401516393197.69%216013.4010111000011056.73%17100000.7500000010
21Phil LaneTORONTO Marlies (TOR)RW1015624088234104.35%210010.0210110000000071.43%700001.2000000000
22Sebastian CollbergTORONTO Marlies (TOR)RW12132000141550.00%01414.420000000000100.00%000004.1600000000
Team Total or Average1174369638100779361125160211723502990241210.54%6351982816.89417711839314893710491968471360.63%5512001161.0202113355249
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
1Reto BerraTORONTO Marlies (TOR)58263020.9172.72348610315819000210.00005832832
Team Total or Average58263020.9172.72348610315819000210.00005832832


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
Brandon MashinterTORONTO Marlies (TOR)LW299/20/1988No96 Kg193 CMNoNoNo1UFAPro & Farm575,000$0$0$NoLink
Chris ButlerTORONTO Marlies (TOR)D3110/27/1986No89 Kg185 CMNoNoNo2UFAPro & Farm650,000$0$0$NoLink
Derrick PouliotTORONTO Marlies (TOR)D241/16/1994No95 Kg183 CMNoNoNo3RFAPro & Farm1,100,000$0$0$NoLink
Jamie McBainTORONTO Marlies (TOR)D302/25/1988No82 Kg185 CMNoNoNo2UFAPro & Farm650,000$0$0$NoLink
Jean-Sebastien DeaTORONTO Marlies (TOR)C242/8/1994No80 Kg180 CMNoNoNo3RFAPro & Farm750,000$0$0$NoLink
Jiri SekacTORONTO Marlies (TOR)LW266/10/1992No84 Kg185 CMNoNoNo3RFAPro & Farm1,000,000$0$0$No
Jordan SzwarzTORONTO Marlies (TOR)RW275/14/1991No91 Kg180 CMNoNoNo1RFAPro & Farm750,000$0$0$NoLink
Julian MelchioriTORONTO Marlies (TOR)D2612/6/1991No97 Kg196 CMNoNoNo3RFAPro & Farm750,000$0$0$NoLink
Justin BaileyTORONTO Marlies (TOR)RW237/1/1995No97 Kg193 CMNoNoNo2RFAPro & Farm750,000$0$0$NoLink
Louis-Marc AubryTORONTO Marlies (TOR)C2611/11/1991No99 Kg193 CMNoNoNo1RFAPro & Farm750,000$0$0$No
Lucas LessioTORONTO Marlies (TOR)LW251/23/1993No96 Kg185 CMNoNoNo5RFAPro & Farm750,000$0$0$No
Luke JohnsonTORONTO Marlies (TOR)C239/19/1994No90 Kg155 CMNoNoNo5RFAPro & Farm925,000$0$0$NoLink
Magnus HellbergTORONTO Marlies (TOR)G274/4/1991No95 Kg198 CMNoNoNo1RFAPro & Farm750,000$0$0$No
Mark McNeillTORONTO Marlies (TOR)C/RW252/22/1993No97 Kg188 CMNoNoNo1RFAPro & Farm600,000$0$0$NoLink
Matt BartkowskiTORONTO Marlies (TOR)D306/4/1988No89 Kg185 CMNoNoNo1UFAPro & Farm1,000,000$0$0$NoLink
Phil LaneTORONTO Marlies (TOR)RW265/29/1992Yes99 Kg191 CMNoNoNo3RFAPro & Farm750,000$0$0$No
Philip SamuelssonTORONTO Marlies (TOR)D277/26/1991No88 Kg188 CMNoNoNo1RFAPro & Farm1,950,000$0$0$NoLink
Reto BerraTORONTO Marlies (TOR)G311/3/1987No99 Kg193 CMNoNoNo1UFAPro & Farm1,660,000$0$0$NoLink
Sebastian CollbergTORONTO Marlies (TOR)RW242/23/1994Yes89 Kg180 CMNoNoNo1RFAPro & Farm750,000$0$0$No
Tommy WingelsTORONTO Marlies (TOR)C/RW304/12/1988No91 Kg183 CMNoNoNo2UFAPro & Farm1,750,000$0$0$NoLink
Vitek VanecekTORONTO Marlies (TOR)G221/9/1996Yes82 Kg185 CMNoNoNo3RFAPro & Farm750,000$0$0$NoLink
Yannick VeilleuxTORONTO Marlies (TOR)LW252/22/1993No89 Kg188 CMNoNoNo5RFAPro & Farm750,000$0$0$NoLink
Zach TrotmanTORONTO Marlies (TOR)D288/26/1990No99 Kg191 CMNoNoNo5UFAPro & Farm750,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2326.4892 Kg185 CM2.39906,957$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Brandon MashinterJean-Sebastien Dea33023
2Jiri SekacJordan Szwarz30023
3Lucas LessioLuke JohnsonTommy Wingels27023
4Yannick VeilleuxMark McNeill10032
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Chris ButlerMatt Bartkowski36023
2Jamie McBainZach Trotman31023
3Julian MelchioriPhilip Samuelsson28023
4Chris ButlerMatt Bartkowski5032
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Brandon MashinterJean-Sebastien DeaJordan Szwarz50005
2Yannick VeilleuxLuke JohnsonMark McNeill50005
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Jamie McBainMatt Bartkowski50014
2Chris ButlerJamie McBain50014
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Jean-Sebastien DeaBrandon Mashinter50041
2Luke JohnsonYannick Veilleux50041
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Julian MelchioriMatt Bartkowski50050
2Chris ButlerJamie McBain50050
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Jean-Sebastien Dea50050Julian MelchioriMatt Bartkowski50050
2Luke Johnson50050Chris ButlerJamie McBain50050
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Jean-Sebastien DeaBrandon Mashinter50014
2Luke JohnsonYannick Veilleux50014
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jamie McBainMatt Bartkowski50023
2Chris ButlerJamie McBain50023
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Brandon MashinterJean-Sebastien DeaJordan SzwarzJulian MelchioriMatt Bartkowski
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Brandon MashinterJean-Sebastien DeaJordan SzwarzJamie McBainMatt Bartkowski
Extra Forwards
Normal PowerPlayPenalty Kill
Jiri Sekac, Tommy Wingels, Mark McNeill, Jean-Sebastien DeaMark McNeill
Extra Defensemen
Normal PowerPlayPenalty Kill
Zach Trotman, Philip Samuelsson, Julian MelchioriZach TrotmanZach Trotman, Philip Samuelsson
Penalty Shots
Jordan Szwarz, Brandon Mashinter, Jean-Sebastien Dea, Luke Johnson, Mark McNeill
Goalie
#1 : , #2 : Reto Berra
Custom OT Lines Forwards
Jordan Szwarz, Brandon Mashinter, Jean-Sebastien Dea, Luke Johnson, Mark McNeill, Yannick Veilleux, Yannick Veilleux, , Tommy Wingels, , Jiri Sekac
Custom OT Lines Defensemen
Julian Melchiori, Matt Bartkowski, Chris Butler, Jamie McBain, Zach Trotman


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 Senators725000001425-1140400000617-113210000088040.2861426400016110067320210161067109215249714613714321.43%22481.82%01480257157.57%1197251047.69%646124751.80%208215751795476876446
2BRIDGEPORT Sound Tigers2200000015510110000008351100000072541.000152641001611006737510161067109215501212254250.00%5340.00%11480257157.57%1197251047.69%646124751.80%208215751795476876446
3BROOKLYN Wolfpack22000000242221100000011110110000001311241.000244367001611006732141016106710921591248100.00%10100.00%11480257157.57%1197251047.69%646124751.80%208215751795476876446
4CHICAGO Wolves21000100440110000002111000010023-130.750481200161100673551016106710921568188333133.33%30100.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
5CLEVELAND Monsters41200100812-42010010049-52110000043130.3758132100161100673971016106710921516150438410220.00%18383.33%01480257157.57%1197251047.69%646124751.80%208215751795476876446
6COLORADO Eagles21100000660110000003121010000035-220.5006101610161100673531016106710921556251444500.00%6183.33%01480257157.57%1197251047.69%646124751.80%208215751795476876446
7CORNWALL Aces99000000981682330000003543166000000631251181.00098179277021611006736141016106710921516244261876350.00%13284.62%01480257157.57%1197251047.69%646124751.80%208215751795476876446
8HERSEY Bears312000001011-11100000031220200000710-320.33310203000161100673871016106710921512230467215533.33%20480.00%11480257157.57%1197251047.69%646124751.80%208215751795476876446
9HOLLYWOOD Oscar3300000014311110000007072200000073461.000142438011611006732391016106710921527916103000.00%8187.50%01480257157.57%1197251047.69%646124751.80%208215751795476876446
10IOWA Wild2020000057-21010000023-11010000034-100.00051015001611006736110161067109215861110427228.57%5260.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
11LAVAL Rockets2110000056-11010000024-21100000032120.500591400161100673471016106710921587238388337.50%40100.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
12LEHIGH VALLEY Phantoms2020000039-61010000024-21010000015-400.000369001611006733610161067109215701118384125.00%9277.78%01480257157.57%1197251047.69%646124751.80%208215751795476876446
13MANITOBA Moose2200000013013110000008081100000050541.000132134021611006732261016106710921532443000.00%10100.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
14MILWAUKEE Admirals2020000013-21010000012-11010000001-100.00011200161100673591016106710921574231435400.00%70100.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
15MONT-LAURIER Sommet21001000853100010004311100000042241.0008142200161100673471016106710921578251625200.00%8187.50%01480257157.57%1197251047.69%646124751.80%208215751795476876446
16PROVIDENCE Bruins2110000056-1110000004311010000013-220.5005914001611006733810161067109215561812334125.00%5180.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
17PV Sharapovas623010001617-13210000096330201000711-460.5001625410116110067315710161067109215212685810223521.74%26484.62%01480257157.57%1197251047.69%646124751.80%208215751795476876446
18ROCKFORD IceHogs20101000550100010002111010000034-120.5005712001611006735010161067109215662514316116.67%50100.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
19SAN DIEGO Gulls2110000045-11010000002-21100000043120.50048120016110067358101610671092155623640600.00%30100.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
20STOCKTON Flames2020000059-41010000034-11010000025-300.00051015001611006733510161067109215751420412150.00%10370.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
21SYRACUSE Crunch7520000040162443100000218133210000019811100.71440721120116110067337410161067109215172488615118738.89%31196.77%01480257157.57%1197251047.69%646124751.80%208215751795476876446
22TUSCON Roadrunners50500000518-1330300000210-82020000038-500.00059140016110067378101610671092152184738801500.00%19384.21%01480257157.57%1197251047.69%646124751.80%208215751795476876446
Total793836032003312071243918180210015597584020180110017611066840.53233159292328161100673319010161067109215236465256715311743922.41%2523685.71%31480257157.57%1197251047.69%646124751.80%208215751795476876446
24UTICA Comets2020000037-41010000024-21010000013-200.000358001611006733810161067109215661918215120.00%8187.50%01480257157.57%1197251047.69%646124751.80%208215751795476876446
25VICTORIAVILLE Tigres2020000047-31010000035-21010000012-100.0004711101611006734310161067109215922814308112.50%60100.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
26WILKIES-BARRIE Penguins330000001631322000000111101100000052361.00016304601161100673207101610671092154971848400.00%90100.00%01480257157.57%1197251047.69%646124751.80%208215751795476876446
_Since Last GM Reset793836032003312071243918180210015597584020180110017611066840.53233159292328161100673319010161067109215236465256715311743922.41%2523685.71%31480257157.57%1197251047.69%646124751.80%208215751795476876446
_Vs Conference4924230200022513293241013010001026438251410010001236855520.531225403628171611006732112101610671092151444378352979992323.23%1582385.44%01480257157.57%1197251047.69%646124751.80%208215751795476876446
_Vs Division1618150100076423488900000391920810601000372314381.188761382140116110067371610161067109215461111139315381026.32%621280.65%31480257157.57%1197251047.69%646124751.80%208215751795476876446

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
7984W133159292331902364652567153128
All Games
GPWLOTWOTL SOWSOLGFGA
7938363200331207
Home Games
GPWLOTWOTL SOWSOLGFGA
391818210015597
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4020181100176110
Last 10 Games
WLOTWOTL SOWSOL
630100
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1743922.41%2523685.71%3
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
10161067109215161100673
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1480257157.57%1197251047.69%646124751.80%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
208215751795476876446


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
1 - 2019-01-234SYRACUSE Crunch1TORONTO Marlies11WR3BoxScore
2 - 2019-01-2414TORONTO Marlies12CORNWALL Aces5WBoxScore
4 - 2019-01-2631BELLEVILLE Senators7TORONTO Marlies2LBoxScore
6 - 2019-01-2847TORONTO Marlies10CORNWALL Aces3WBoxScore
7 - 2019-01-2957CORNWALL Aces2TORONTO Marlies12WBoxScore
9 - 2019-01-3173TORONTO Marlies12CORNWALL Aces1WBoxScore
10 - 2019-02-0187BELLEVILLE Senators4TORONTO Marlies2LBoxScore
11 - 2019-02-0295TORONTO Marlies2BELLEVILLE Senators1WBoxScore
13 - 2019-02-04108TORONTO Marlies1TUSCON Roadrunners4LBoxScore
14 - 2019-02-05121PV Sharapovas2TORONTO Marlies3WBoxScore
15 - 2019-02-06134TORONTO Marlies8CORNWALL Aces0WBoxScore
17 - 2019-02-08145SYRACUSE Crunch1TORONTO Marlies4WR3BoxScore
18 - 2019-02-09154TORONTO Marlies4SYRACUSE Crunch5LBoxScore
20 - 2019-02-11173SYRACUSE Crunch5TORONTO Marlies3LR3BoxScore
22 - 2019-02-13189TORONTO Marlies4PV Sharapovas3WXBoxScore
23 - 2019-02-14196TUSCON Roadrunners2TORONTO Marlies1LBoxScore
24 - 2019-02-15215CHICAGO Wolves1TORONTO Marlies2WBoxScore
26 - 2019-02-17225TORONTO Marlies1VICTORIAVILLE Tigres2LBoxScore
27 - 2019-02-18234TORONTO Marlies6BELLEVILLE Senators5WBoxScore
29 - 2019-02-20248BELLEVILLE Senators2TORONTO Marlies1LBoxScore
31 - 2019-02-22267WILKIES-BARRIE Penguins1TORONTO Marlies6WBoxScore
32 - 2019-02-23280TORONTO Marlies1PROVIDENCE Bruins3LBoxScore
33 - 2019-02-24287TORONTO Marlies10CORNWALL Aces1WBoxScore
34 - 2019-02-25304MILWAUKEE Admirals2TORONTO Marlies1LBoxScore
36 - 2019-02-27317TORONTO Marlies3ROCKFORD IceHogs4LBoxScore
37 - 2019-02-28325TORONTO Marlies3HERSEY Bears5LR3BoxScore
39 - 2019-03-02341SYRACUSE Crunch1TORONTO Marlies3WR3BoxScore
41 - 2019-03-04356CLEVELAND Monsters5TORONTO Marlies1LBoxScore
42 - 2019-03-05366TORONTO Marlies4SYRACUSE Crunch3WR3BoxScore
43 - 2019-03-06379TORONTO Marlies4MONT-LAURIER Sommet2WBoxScore
45 - 2019-03-08390PV Sharapovas4TORONTO Marlies3LBoxScore
46 - 2019-03-09404LAVAL Rockets4TORONTO Marlies2LBoxScore
48 - 2019-03-11424SAN DIEGO Gulls2TORONTO Marlies0LBoxScore
49 - 2019-03-12434TORONTO Marlies3IOWA Wild4LBoxScore
51 - 2019-03-14447TUSCON Roadrunners2TORONTO Marlies1LBoxScore
52 - 2019-03-15463TORONTO Marlies0CLEVELAND Monsters1LBoxScore
53 - 2019-03-16474IOWA Wild3TORONTO Marlies2LBoxScore
54 - 2019-03-17482TORONTO Marlies1UTICA Comets3LBoxScore
56 - 2019-03-19500CORNWALL Aces0TORONTO Marlies11WBoxScore
57 - 2019-03-20507TORONTO Marlies2STOCKTON Flames5LBoxScore
59 - 2019-03-22525MONT-LAURIER Sommet3TORONTO Marlies4WXBoxScore
61 - 2019-03-24537TORONTO Marlies2CHICAGO Wolves3LXBoxScore
62 - 2019-03-25550TORONTO Marlies2PV Sharapovas3LBoxScore
63 - 2019-03-26561VICTORIAVILLE Tigres5TORONTO Marlies3LBoxScore
65 - 2019-03-28578ROCKFORD IceHogs1TORONTO Marlies2WXBoxScore
67 - 2019-03-30592TORONTO Marlies2TUSCON Roadrunners4LBoxScore
68 - 2019-03-31603TORONTO Marlies1PV Sharapovas5LBoxScore
69 - 2019-04-01613UTICA Comets4TORONTO Marlies2LBoxScore
70 - 2019-04-02630PV Sharapovas0TORONTO Marlies3WBoxScore
71 - 2019-04-03641TORONTO Marlies13BROOKLYN Wolfpack1WBoxScore
73 - 2019-04-05654TORONTO Marlies7BRIDGEPORT Sound Tigers2WBoxScore
74 - 2019-04-06664BRIDGEPORT Sound Tigers3TORONTO Marlies8WBoxScore
76 - 2019-04-08679BELLEVILLE Senators4TORONTO Marlies1LBoxScore
78 - 2019-04-10695TORONTO Marlies5MANITOBA Moose0WBoxScore
79 - 2019-04-11709MANITOBA Moose0TORONTO Marlies8WBoxScore
80 - 2019-04-12724TORONTO Marlies3LAVAL Rockets2WBoxScore
81 - 2019-04-13734STOCKTON Flames4TORONTO Marlies3LBoxScore
83 - 2019-04-15747TORONTO Marlies3COLORADO Eagles5LBoxScore
84 - 2019-04-16759BROOKLYN Wolfpack1TORONTO Marlies11WBoxScore
85 - 2019-04-17773TORONTO Marlies0MILWAUKEE Admirals1LBoxScore
87 - 2019-04-19786PROVIDENCE Bruins3TORONTO Marlies4WBoxScore
88 - 2019-04-20799TORONTO Marlies11SYRACUSE Crunch0WR3BoxScore
90 - 2019-04-22812WILKIES-BARRIE Penguins0TORONTO Marlies5WBoxScore
92 - 2019-04-24826TORONTO Marlies5WILKIES-BARRIE Penguins2WBoxScore
93 - 2019-04-25838COLORADO Eagles1TORONTO Marlies3WBoxScore
95 - 2019-04-27852TORONTO Marlies4CLEVELAND Monsters2WBoxScore
96 - 2019-04-28862TORONTO Marlies1LEHIGH VALLEY Phantoms5LBoxScore
97 - 2019-04-29871TUSCON Roadrunners6TORONTO Marlies0LBoxScore
98 - 2019-04-30888TORONTO Marlies11CORNWALL Aces2WBoxScore
100 - 2019-05-02900TORONTO Marlies0BELLEVILLE Senators2LBoxScore
101 - 2019-05-03909CLEVELAND Monsters4TORONTO Marlies3LXBoxScore
103 - 2019-05-05925CORNWALL Aces2TORONTO Marlies12WBoxScore
104 - 2019-05-06938TORONTO Marlies4HOLLYWOOD Oscar1WBoxScore
106 - 2019-05-08952HOLLYWOOD Oscar0TORONTO Marlies7WBoxScore
108 - 2019-05-10974HERSEY Bears1TORONTO Marlies3WR3BoxScore
109 - 2019-05-11983TORONTO Marlies4HERSEY Bears5LBoxScore
110 - 2019-05-12990TORONTO Marlies3HOLLYWOOD Oscar2WBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
112 - 2019-05-141008LEHIGH VALLEY Phantoms4TORONTO Marlies2LBoxScore
113 - 2019-05-151017TORONTO Marlies4SAN DIEGO Gulls3WBoxScore
115 - 2019-05-171031PROVIDENCE Bruins-TORONTO Marlies-
117 - 2019-05-191050TORONTO Marlies-TUSCON Roadrunners-
119 - 2019-05-211065CORNWALL Aces-TORONTO Marlies-



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
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
2,691,790$ 2,086,000$ 2,086,000$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 1,917,106$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 6 27,942$ 167,652$




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
287864802301449793703933401100225361893931401201224431811284498271276034235125872386112801256131513126534647014031282721.09%2151891.63%111621244166.41%903164454.93%810121066.94%265321001184391855504
308250180418138313424941318020001996013941191002181184741101003836771060120200918017359511681136126066158146961015061403021.43%2502390.80%51709267263.96%1071192255.72%775121863.63%255819601462474955528
3182531707401383166217413090200019374119412380540119092981063836911074214177115847341811691070115725197760080716672375623.63%3725186.29%71800282563.72%1368237457.62%827130163.57%223916431713540995519
327938360320033120712439181802100155975840201801100176110668433159292328161100673319010161067109215236465256715311743922.41%2523685.71%31480257157.57%1197251047.69%646124751.80%208215751795476876446
Total Regular Season321205790161083154658696016011239072007722675051619340098837743194554181546278743335767734313182914064463345294824119718720672454610767915222.39%108912888.25%2666101050962.90%4539845053.72%3058497661.45%953372796155188336812000
Playoff
2821165000006044161192000003621151073000002423132601061660415232026111992011971450613017335962914.52%75790.67%134168449.85%30864447.83%14028948.44%531368485159280139
3019109000003636010730000025169936000001120-9203669105011510925241551781801152715717637447714.89%85890.59%028359647.48%29563846.24%12025447.24%432287486148249121
Total Playoff40261400000968016211650000061372419109000003543-8529617527105303329411353543793772510332873497331091614.68%1601590.63%1624128048.75%603128247.04%26054347.88%964656972307529260