Association Québécoise de Hockey Simulé - Marmots 

Marmots

GP: 48 | W: 16 | L: 29 | OTL: 3 | P: 35
GF: 158 | GA: 199 | PP%: 26.09% | PK%: 76.51%
GM : Patrick Gagnon | Morale : 90 | Team Overall : 57
Next Games #746 vs Smirnoff Ice
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
1Cedric PaquetteX100.00994867756850404860475085508875090620
2Tyler JohnsonX100.00784582825065405630535962839181090600
3Tyler PitlickX100.00874591777055475030485268659078090600
4Andy AndreoffX99.00584595767050404730405457509077090550
5Kiefer SherwoodX100.00594595786350404930445455508774090550
6Andrew PoturalskiX100.0050459579535140493048505550887509054X0
7Alex BroadhurstX99.00504595795450404530405055508572090530
8Kole SherwoodX100.00504595747450404530405055508572090530
9Daniel WalcottX100.00504595795550404530405055508774090560
Scratches
1Mathieu PerreaultX100.00784591835656406030566368689482090620
2Paul ByronX100.00994593844063405630496273699383090620
3Timothy Gettinger (R)X100.00634595738850404530405055508471090550
4Nic PetanX100.00524590804751404930485056668774090540
5Brian Pinho (R)X100.00504595776350404530405055508673090530
6Adam JohnsonX100.00504595805250404530405055508572090520
7Matt BenningX100.00754879786568785230545070668777090660
8Dylan McIlrathX100.00504595728750404530405055508776090580
9Taylor FedunX100.00504595826350404530405055509179090580
10Kevin GravelX100.00504595757250404530405055508876090570
11Evan McEnenyX100.00504595756650404530405055508471090560
TEAM AVERAGE99.9062459178635342483244526056887609057
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
1Thomas Greiss100.0072657492717472747170709689090660
Scratches
TEAM AVERAGE100.007265749271747274717070968909066
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Tony Granato65656565927456USA604700,000$


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
1Tyler JohnsonMarmots (LON)RW44222648-142206246157478914.01%2080018.19591424810008364045.28%534933001.2001000425
2Mathieu PerreaultMarmots (LON)LW3819214001205249141428513.48%1867817.8554910381015752049.33%753920011.1812000412
3Paul ByronMarmots (LON)LW39171936010075501264410213.49%2673318.813038310001640140.54%2224135000.9814000415
4Jansen HarkinsLondon SpartiatesC37181735-121404556126244814.29%968318.481051525730000122143.42%7901922001.0200000421
5Tyler PitlickMarmots (LON)RW47131528-171008450110508511.82%2886818.48561113900002350040.00%652531000.6422000141
6Andrew PoturalskiMarmots (LON)C4891423-19100466410229648.82%1282917.281451587000081043.37%6183319000.5500000013
7Kiefer SherwoodMarmots (LON)RW4671421-88041369829567.14%2368714.95101527000052038.46%392814000.6100000001
8Cedric PaquetteMarmots (LON)LW3811920-28435785477294314.29%2567317.710442420110620056.48%1082341000.5905010111
9Matt BenningMarmots (LON)D264812-2334049315014148.00%3167125.83213760000044000.00%0563000.3600000101
10Alex BroadhurstMarmots (LON)C277310-138017312981324.14%741515.381122130001160044.81%270714000.4800000001
11Taylor FedunMarmots (LON)D34088-266015262111140.00%2771921.17022155000156000.00%0432000.2200000000
12Nic PetanMarmots (LON)RW25358-61758231981815.79%229011.600220100001120139.78%9377000.5500010111
13Andrej SustrLondon SpartiatesD18167-136019212812163.57%3046425.79033142000132000.00%0628100.3000000000
14Kevin GravelMarmots (LON)D37156-82062613997.69%3261816.73000025000040000.00%0220000.1900000000
15Evan McEnenyMarmots (LON)D16066255121910480.00%1432120.11011122000128000.00%1217000.3700100000
16Daniel WalcottMarmots (LON)D40055240927169120.00%2765516.39000421000049000.00%1827000.1500000000
17Kole SherwoodMarmots (LON)RW43325-90024193051310.00%1543710.18000216000070039.02%82712000.2300000100
18Andy AndreoffMarmots (LON)LW93032209373442.86%411813.1900006000051034.88%4335000.5100000002
19Timothy GettingerMarmots (LON)LW821300010350140.00%18911.2400025000041050.00%211000.6700000020
20Dylan McIlrathMarmots (LON)D34022-1320830227100.00%2670320.68011255000258000.00%0939000.0600000000
Team Total or Average654140186326-20321515669664118738470411.79%3771146017.523343761248051122365613343.46%2462318480110.57414120211524
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
1Thomas GreissMarmots (LON)38142030.8833.652136401301112559310.52619372231
Team Total or Average38142030.8833.652136401301112559310.52619372231


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 JohnsonMarmots (LON)RW281993-06-22No174 Lbs6 ft0NoNoNo1UFAPro & Farm700,000$0$0$No
Alex BroadhurstMarmots (LON)C281992-10-12No178 Lbs6 ft0NoNoNo2UFAPro & Farm750,000$0$0$No
Andrew PoturalskiMarmots (LON)C271993-10-12No183 Lbs5 ft10NoYesNo2RFAPro & Farm900,000$0$0$No
Andy AndreoffMarmots (LON)LW311990-05-17No200 Lbs6 ft2NoNoNo2UFAPro & Farm900,000$0$0$No
Brian PinhoMarmots (LON)C271994-05-11Yes190 Lbs6 ft1NoNoNo3RFAPro & Farm750,000$0$0$No
Cedric PaquetteMarmots (LON)LW291992-08-13No205 Lbs6 ft0NoNoNo4UFAPro & Farm3,500,000$0$0$No
Daniel WalcottMarmots (LON)D281993-02-19No175 Lbs6 ft1NoNoNo2UFAPro & Farm900,000$0$0$No
Dylan McIlrathMarmots (LON)D301991-04-20No231 Lbs6 ft5NoNoNo5UFAPro & Farm750,000$0$0$No
Evan McEnenyMarmots (LON)D271993-10-12No203 Lbs6 ft2NoNoNo1RFAPro & Farm750,000$0$0$No
Kevin GravelMarmots (LON)D301991-03-06No205 Lbs6 ft4NoNoNo5UFAPro & Farm750,000$0$0$No
Kiefer SherwoodMarmots (LON)RW271994-03-31No194 Lbs6 ft0NoNoNo3RFAPro & Farm800,000$0$0$No
Kole SherwoodMarmots (LON)RW251996-01-22No212 Lbs6 ft1NoNoNo1RFAPro & Farm700,000$0$0$No
Mathieu PerreaultMarmots (LON)LW341987-01-05No189 Lbs5 ft10NoNoNo4UFAPro & Farm4,000,000$0$0$No
Matt BenningMarmots (LON)D281993-05-25No203 Lbs6 ft1NoNoNo4UFAPro & Farm1,000,000$0$0$No
Nic PetanMarmots (LON)RW271994-03-22No175 Lbs5 ft9NoNoNo5RFAPro & Farm700,000$0$0$No
Paul ByronMarmots (LON)LW331988-04-27No158 Lbs5 ft9NoNoNo4UFAPro & Farm4,000,000$0$0$No
Taylor FedunMarmots (LON)D341987-06-04No200 Lbs6 ft1NoNoNo5UFAPro & Farm750,000$0$0$No
Thomas GreissMarmots (LON)G361985-01-29No219 Lbs6 ft2NoNoNo5UFAPro & Farm1,200,000$0$0$No
Timothy GettingerMarmots (LON)LW241997-04-14Yes220 Lbs6 ft6NoNoNo1RFAPro & Farm700,000$0$0$No
Tyler JohnsonMarmots (LON)RW321989-07-29No185 Lbs5 ft8NoNoNo2UFAPro & Farm950,000$0$0$No
Tyler PitlickMarmots (LON)RW301990-11-01No200 Lbs6 ft2NoNoNo2UFAPro & Farm2,200,000$0$0$No
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2129.29195 Lbs6 ft13.001,316,667$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Andrew PoturalskiTyler Pitlick35122
2Alex BroadhurstTyler Johnson30122
3Cedric PaquetteAndy AndreoffKiefer Sherwood25122
4Andy AndreoffKole Sherwood10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
135122
2Daniel WalcottKole Sherwood30122
325122
410122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Andrew PoturalskiTyler Pitlick55122
2Alex BroadhurstTyler Johnson45122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
155122
2Daniel WalcottKole Sherwood45122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
155122
2Cedric PaquetteTyler Pitlick45122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
155122
2Daniel Walcott45122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
15512255122
245122Daniel Walcott45122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
155122
2Cedric PaquetteTyler Pitlick45122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
155122
2Daniel Walcott45122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Andrew PoturalskiTyler Pitlick
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Andrew PoturalskiTyler Pitlick
Extra Forwards
Normal PowerPlayPenalty Kill
Kiefer Sherwood, Tyler Johnson, Andy AndreoffKiefer Sherwood, Tyler JohnsonAndy Andreoff
Extra Defensemen
Normal PowerPlayPenalty Kill
Daniel Walcott, , Daniel Walcott,
Penalty Shots
, , Cedric Paquette, Tyler Pitlick, Tyler Johnson
Goalie
#1 : Thomas Greiss, #2 :


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
1Bandits1010000056-11010000056-10000000000000.0005712002655747193264605612644148133133.33%4175.00%038888343.94%43299243.55%34577144.75%8604461202424845418
2Barracudas2020000058-31010000024-21010000034-100.0005712002655747523264605612644921168337.50%80100.00%038888343.94%43299243.55%34577144.75%8604461202424845418
3Bayou1010000045-1000000000001010000045-100.000461000265574743326460561263221229100.00%110.00%038888343.94%43299243.55%34577144.75%8604461202424845418
4Farmers403000101420-620100010910-120200000510-520.2501424381026557471073264605612613336267913323.08%13376.92%038888343.94%43299243.55%34577144.75%8604461202424845418
5Goons20200000711-41010000046-21010000035-200.000710170026557476632646056126661916339333.33%8362.50%038888343.94%43299243.55%34577144.75%8604461202424845418
6Hunters11000000312110000003120000000000021.000358002655747223264605612624710113133.33%50100.00%038888343.94%43299243.55%34577144.75%8604461202424845418
7Husky20200000611-51010000024-21010000047-300.000612180026557477032646056126812914313133.33%7185.71%038888343.94%43299243.55%34577144.75%8604461202424845418
8Igloos1000000112-11000000112-10000000000010.50011200265574723326460561262194133133.33%20100.00%038888343.94%43299243.55%34577144.75%8604461202424845418
9Marlies412000011215-32010000158-32110000077030.3751221330026557471323264605612615344247211327.27%11281.82%038888343.94%43299243.55%34577144.75%8604461202424845418
10Outlaws10001000321000000000001000100032121.000347002655747273264605612623132175240.00%10100.00%038888343.94%43299243.55%34577144.75%8604461202424845418
11Raptors1010000024-21010000024-20000000000000.0002351026557473732646056126358622200.00%3166.67%038888343.94%43299243.55%34577144.75%8604461202424845418
12Rockets1010000038-51010000038-50000000000000.00035800265574742326460561264620819200.00%4325.00%038888343.94%43299243.55%34577144.75%8604461202424845418
13Saguenéens1010000013-2000000000001010000013-200.00012300265574725326460561262913023200.00%000.00%038888343.94%43299243.55%34577144.75%8604461202424845418
14Scorpions2110000011101110000007431010000046-220.5001119300026557479432646056126631110348337.50%5260.00%138888343.94%43299243.55%34577144.75%8604461202424845418
15Smirnoff Ice3120000013121211000008621010000056-120.33313203300265574781326460561261193724602150.00%12375.00%038888343.94%43299243.55%34577144.75%8604461202424845418
16Snowbirds11000000312110000003120000000000021.00035800265574727326460561263780165240.00%000.00%038888343.94%43299243.55%34577144.75%8604461202424845418
17Spartans10000010431000000000001000001043121.00046100026557472332646056126318717300.00%000.00%038888343.94%43299243.55%34577144.75%8604461202424845418
18Supreme11000000633000000000001100000063321.000612180026557473632646056126301010194125.00%5180.00%138888343.94%43299243.55%34577144.75%8604461202424845418
19Thugs1010000003-3000000000001010000003-300.00000000265574721326460561262010813300.00%4175.00%038888343.94%43299243.55%34577144.75%8604461202424845418
20TigersCats321000001112-11100000042221100000710-340.667111425002655747693264605612610027226110220.00%11463.64%038888343.94%43299243.55%34577144.75%8604461202424845418
Total48132901023158199-4124713000137895-17246160101080104-24350.36515825341120265574713553264605612615514673228341383626.09%1493576.51%238888343.94%43299243.55%34577144.75%8604461202424845418
22Twins21100000981110000005141010000047-320.500913220026557475832646056126481713314125.00%40100.00%038888343.94%43299243.55%34577144.75%8604461202424845418
23Vandals11000000523000000000001100000052321.000591400265574736326460561262477183133.33%10100.00%038888343.94%43299243.55%34577144.75%8604461202424845418
24Vipers2020000036-31010000013-21010000023-100.000369002655747443264605612667156373133.33%30100.00%038888343.94%43299243.55%34577144.75%8604461202424845418
25Warriors412000011125-1420100001616-102110000059-430.375111829002655747963264605612616842488716318.75%24866.67%038888343.94%43299243.55%34577144.75%8604461202424845418
26Wolves321000001091211000006601100000043140.66710152500265574770326460561266419183010220.00%90100.00%038888343.94%43299243.55%34577144.75%8604461202424845418
27Xpress2020000069-31010000023-11010000046-200.0006915002655747353264605612649148332150.00%4175.00%038888343.94%43299243.55%34577144.75%8604461202424845418
_Since Last GM Reset48132901023158199-4124713000137895-17246160101080104-24350.36515825341120265574713553264605612615514673228341383626.09%1493576.51%238888343.94%43299243.55%34577144.75%8604461202424845418
_Vs Conference286180001392132-401639000135272-201239000004060-20170.30492146238102655747762326460561261004298212512772025.97%1052972.38%038888343.94%43299243.55%34577144.75%8604461202424845418
_Vs Division19511000126492-281025000123550-15936000002942-13140.3686410216610265574752732646056126719206152378541222.22%752369.33%038888343.94%43299243.55%34577144.75%8604461202424845418

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
4835W11582534111355155146732283420
All Games
GPWLOTWOTL SOWSOLGFGA
4813291023158199
Home Games
GPWLOTWOTL SOWSOLGFGA
2471300137895
Visitor Games
GPWLOTWOTL SOWSOLGFGA
24616101080104
Last 10 Games
WLOTWOTL SOWSOL
251020
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1383626.09%1493576.51%2
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
326460561262655747
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
38888343.94%43299243.55%34577144.75%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
8604461202424845418


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 - 2023-04-051Marmots3Marlies2WBoxScore
2 - 2023-04-0626Smirnoff Ice4Marmots1LBoxScore
3 - 2023-04-0736Marmots4Bayou5LBoxScore
4 - 2023-04-0850Raptors4Marmots2LBoxScore
6 - 2023-04-1070Marmots3Farmers5LBoxScore
7 - 2023-04-1180TigersCats2Marmots4WBoxScore
9 - 2023-04-1399Marmots3Warriors2WBoxScore
10 - 2023-04-14113Marlies3Marmots2LXXBoxScore
12 - 2023-04-16132Marmots1Saguenéens3LBoxScore
13 - 2023-04-17142Rockets8Marmots3LBoxScore
14 - 2023-04-18161Marmots2Farmers5LBoxScore
15 - 2023-04-19172Goons6Marmots4LBoxScore
16 - 2023-04-20185Marmots5TigersCats3WBoxScore
17 - 2023-04-21201Warriors5Marmots4LXXBoxScore
20 - 2023-04-24224Marmots4Scorpions6LBoxScore
21 - 2023-04-25238Farmers6Marmots4LBoxScore
22 - 2023-04-26257Marmots3Barracudas4LBoxScore
23 - 2023-04-27268Smirnoff Ice2Marmots7WBoxScore
25 - 2023-04-29289Wolves4Marmots3LBoxScore
27 - 2023-05-01309Marmots3Goons5LBoxScore
28 - 2023-05-02325Warriors11Marmots2LBoxScore
29 - 2023-05-03337Marmots4Husky7LBoxScore
30 - 2023-05-04351Husky4Marmots2LBoxScore
31 - 2023-05-05375Wolves2Marmots3WBoxScore
32 - 2023-05-06388Marmots5Smirnoff Ice6LBoxScore
33 - 2023-05-07396Marmots5Vandals2WBoxScore
35 - 2023-05-09418Marmots4Twins7LBoxScore
36 - 2023-05-10425Bandits6Marmots5LBoxScore
37 - 2023-05-11447Marlies5Marmots3LBoxScore
38 - 2023-05-12462Marmots4Wolves3WBoxScore
39 - 2023-05-13477Vipers3Marmots1LBoxScore
40 - 2023-05-14487Marmots2Vipers3LBoxScore
42 - 2023-05-16505Marmots2Warriors7LBoxScore
43 - 2023-05-17518Igloos2Marmots1LXXBoxScore
45 - 2023-05-19539Marmots4Xpress6LBoxScore
46 - 2023-05-20549Snowbirds1Marmots3WBoxScore
47 - 2023-05-21569Scorpions4Marmots7WBoxScore
48 - 2023-05-22581Marmots6Supreme3WBoxScore
50 - 2023-05-24597Xpress3Marmots2LBoxScore
51 - 2023-05-25617Marmots2TigersCats7LBoxScore
52 - 2023-05-26626Marmots3Outlaws2WXBoxScore
53 - 2023-05-27639Barracudas4Marmots2LBoxScore
54 - 2023-05-28659Hunters1Marmots3WBoxScore
56 - 2023-05-30675Marmots4Marlies5LBoxScore
57 - 2023-05-31688Marmots4Spartans3WXXBoxScore
58 - 2023-06-01702Farmers4Marmots5WXXBoxScore
59 - 2023-06-02713Marmots0Thugs3LBoxScore
61 - 2023-06-04734Twins1Marmots5WBoxScore
62 - 2023-06-05746Marmots-Smirnoff Ice-
63 - 2023-06-06761TigersCats-Marmots-
65 - 2023-06-08778Marmots-Grizzlies-
66 - 2023-06-09793Marmots-Marlies-
67 - 2023-06-10802Outlaws-Marmots-
69 - 2023-06-12825Vandals-Marmots-
71 - 2023-06-14845Marmots-Scorpions-
72 - 2023-06-15861Saguenéens-Marmots-
73 - 2023-06-16875Marmots-Saguenéens-
74 - 2023-06-17886Bayou-Marmots-
75 - 2023-06-18908Chiwawa-Marmots-
76 - 2023-06-19922Marmots-Chiwawa-
77 - 2023-06-20936Spartans-Marmots-
79 - 2023-06-22955Marmots-Bandits-
80 - 2023-06-23964Marmots-Hunters-
81 - 2023-06-24977Marmots-Raptors-
82 - 2023-06-25988CoolFm-Marmots-
83 - 2023-06-261011Raptors-Marmots-
85 - 2023-06-281021Marmots-Predateurs-
86 - 2023-06-291039Goons-Marmots-
87 - 2023-06-301052Marmots-Rockets-
88 - 2023-07-011068Marmots-Snowbirds-
89 - 2023-07-021076Supreme-Marmots-
Trade Deadline --- Trades can’t be done after this day is simulated!
90 - 2023-07-031099Marmots-CoolFm-
91 - 2023-07-041110Grizzlies-Marmots-
93 - 2023-07-061126Marmots-Bayou-
95 - 2023-07-081141Thugs-Marmots-
97 - 2023-07-101165Rockets-Marmots-
99 - 2023-07-121185Marmots-Grizzlies-
102 - 2023-07-151201Grizzlies-Marmots-
103 - 2023-07-161209Marmots-Igloos-
104 - 2023-07-171224Marmots-Rockets-
105 - 2023-07-181234Outlaws-Marmots-
110 - 2023-07-231271Predateurs-Marmots-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price7530
Attendance23,96613,211
Attendance PCT49.93%55.05%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
17 1549 - 51.63% 109,689$2,632,536$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
2,063,191$ 2,765,000$ 1,945,000$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 1,675,813$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
1,864,713$ 50 31,216$ 1,560,800$




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
3282313108912277288-1141151704401132143-1141161404511145145062277463740034810711310212149370988740225477770512702105827.62%2536076.28%7732147449.66%730145450.21%604127947.22%1747107818736791340662
3482333903322270282-12411920010101431321141141902312127150-236627044471421331071255200442174882523224074357013732366326.69%2075672.95%5662140547.12%673135449.70%624129148.33%1747110819176621286627
4182362803753282251314118120324213211121411816005111501401098282492774024610112711231849381499741211769148113672577428.79%1965173.98%2753150250.13%691140549.18%681124354.79%2041138116746291255628
42763138011232712683381618011111531401338152000012118128-107227146573640361291033212548180982329216068949614372156630.70%1875172.73%3649139646.49%604132445.62%537119245.05%1728111716536061205595
4548132901023158199-4124713000137895-17246160101080104-243515825341120265574713553264605612615514673228341383626.09%1493576.51%238888343.94%43299243.55%34577144.75%8604461202424845418
Total Regular Season37014416501620121312581288-30185758009777638621171856985071356620667-473331258211733758618949954236992322143540409315910322336725746281105629728.13%99225374.50%193184666047.81%3130652947.94%2791577648.32%812651338321300359332932