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Moose
GP: 80 | W: 32 | L: 41 | OTL: 7 | P: 71
GF: 312 | GA: 335 | PP%: 19.09% | PK%: 77.16%
GM : Pascal Verret | Morale : 21 | Team Overall : 64
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Game Center
Rampage
45-28-7, 97pts
4
FINAL
2 Moose
32-41-7, 71pts
Team Stats
W5StreakL2
22-15-3Home Record14-22-4
23-13-4Away Record18-19-3
9-0-1Last 10 Games0-9-1
4.33Goals Per Game3.90
3.95Goals Against Per Game4.19
19.39%Power Play Percentage19.09%
79.82%Penalty Kill Percentage77.16%
Reign
41-32-7, 89pts
4
FINAL
3 Moose
32-41-7, 71pts
Team Stats
L1StreakL2
21-15-4Home Record14-22-4
20-17-3Away Record18-19-3
5-3-2Last 10 Games0-9-1
4.25Goals Per Game3.90
4.18Goals Against Per Game4.19
22.94%Power Play Percentage19.09%
78.81%Penalty Kill Percentage77.16%
Team Leaders
Goals
Mathieu Joseph
43
Assists
Dylan Strome
75
Points
Dylan Strome
116
Plus/Minus
Mathieu Joseph
14
Wins
Filip Gustavsson
17
Save Percentage
Filip Gustavsson
0.877

Team Stats
Goals For
312
3.90 GFG
Shots For
2696
33.70 Avg
Power Play Percentage
19.1%
63 GF
Offensive Zone Start
37.9%
Goals Against
335
4.19 GAA
Shots Against
2571
32.14 Avg
Penalty Kill Percentage
77.2%%
74 GA
Defensive Zone Start
36.2%
Team Info

General ManagerPascal Verret
CoachAdams Oates
DivisionThayer-Tutt
ConferenceRobert-Lebel
Captain
Assistant #1Ludwig Bystrom
Assistant #2


Arena Info

Capacity3,000
Attendance2,784
Season Tickets300


Roster Info

Pro Team36
Farm Team18
Contract Limit54 / 250
Prospects0


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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.
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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 SPAgeContractSalary
1Nathan Walker (R)X100.006931727772786977717572647351515033700231850,000$
2Kyle Connor (R)X100.006134897572747873596088517751466231690213800,000$
3Nikolay Goldobin (R)X100.006537827568705880647170687947445625690211850,000$
4Mathieu Joseph (R)X100.007337707375627474596774696445435844680203950,000$
5Dylan Strome (R)X100.006128786763797473848169525349436733670204950,000$
6Michael McLeod (R)X100.005237738362635682616470637343426441660191500,000$
7Julien Gauthier (R)X100.006129775574626167586973486144425641620201500,000$
8Nick Merkley (R)X100.005735816157666370806862395942425617610204550,000$
9Mitchell Stephens (R)X100.004827907066796549706658614642425918600202500,000$
10Boris Katchouk (R)X100.006742726364626968625863476342437220600192500,000$
11Kieffer Bellows (R)X100.006024795174666661636171406741426514590191500,000$
12Jake Leschyshyn (R)X100.007436596075577866565853444740407926570182500,000$
13Mirco Mueller (R)X100.007222827174787472557463815655454948720221990,000$
14Ludwig Bystrom (R) (A)X100.007323787874727677497158775861474141710231975,000$
15Erik Cernak (R)X100.007735726979786356417264775049446210700202950,000$
16Matthew Benning (R)X100.006722796866716166457061725549494518660231750,000$
17Juuso Valimaki (R)X100.005030667654615977297947674641417326620192500,000$
18Josh Mahura (R)X100.00513774725457597526665262384141598600191500,000$
Scratches
1Lane MacDermidX100.007744787675677473667472696869662811710281700,000$
2Tomas JurcoX100.007733767282716871717673657364603625710251700,000$
3Chase De Leo (R)X100.006530817066697167697673516145445730660211750,000$
4Vinni Lettieri (R)X100.006539867278777353667656635749484919650222500,000$
5Anders Bjork (R)X100.006029738056626181586863567143434818640211600,000$
6Nathan Bastian (R)X100.004941725760726166796561495942445214600201500,000$
7Max Jones (R)X100.006742666570557360466659544441416116590191500,000$
8William Bitten (R)X100.007140616468516964495664505841425916590191500,000$
9Tim Gettinger (R)X100.005629655164595460505862316541416020540191500,000$
10Roman JosiX100.0073308671747379725370757365645233207102711,000,000$
11Nelson Nogier (R)X100.006641746466676260386657694543434716640211600,000$
12Urho Vaakanainen (R)X100.005623765957575747285936643840407717560182500,000$
13Jonathan Kovacevic (R)X100.006133635655635443356137593542444920550201350,000$
TEAM AVERAGE100.00643375686867666756686359584745562464
Filter Tips
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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.
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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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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 SPAgeContractSalary
1Filip Gustavsson (R)100.00646774635478795648786445427346630191500,000$
2Daniel Vladar (R)100.00536644675767557065555742436820590203500,000$
Scratches
1Brandon Halverson100.00727772707572727167687348445239700211850,000$
2Karel Vejmelka (R)100.00725869787460556271487145475514640212500,000$
3Joey Daccord100.00676665485273735352685344435520600211600,000$
TEAM AVERAGE100.0066676565627067626163644544612863
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Adams Oates53568572375954CAN531950,000$


Filter Tips
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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 NamePOSGP 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
1Dylan StromeMoose (Win)C77417511684001101492437615616.87%35157620.48112031402660000692353.82%24193630001.4703000944
2Nathan WalkerMoose (Win)LW75285785670011197285881659.82%44148719.83517223023900051486149.49%1965833001.1437000141
3Mathieu JosephMoose (Win)RW7743378014555147971966210421.94%30144018.71913223321711261224051.69%1184431011.1104100337
4Kyle ConnorMoose (Win)LW78363470-141751159227010418113.33%42169021.679101944255303151872342.49%1935824100.8369000534
5Tomas JurcoMoose (Win)RW71333164-546094612044810616.18%39120917.037714231551012572054.24%1184226021.0602000541
6Nikolay GoldobinMoose (Win)LW73293160410087712156611713.49%3699813.68751216621012911445.26%1373920101.2036000451
7Michael McLeodMoose (Win)C793120518320661052306911813.48%28111414.1126810851013925143.90%7704925010.9223000322
8Mirco MuellerMoose (Win)D7664046-738012716212545504.80%138202926.705611242230006258110.00%03773000.4500000304
9Chase De LeoMoose (Win)C73142741-13200905915354869.15%2296013.15369101230001320048.31%5613414000.8501000113
10Ludwig BystromMoose (Win)D8053439154013915313860673.62%146211926.49257222930002255000.00%04669000.3700000121
11Julien GauthierMoose (Win)RW781213251120613670145617.14%1684710.870113280001533044.44%451210000.5900000210
12Erik CernakMoose (Win)D7232124-156951171087427254.05%87151821.0910161590331157000.00%01456000.3201000111
13Roman JosiMoose (Win)D7432124-231808111811953472.52%93158921.47246182220110166000.00%03555000.3012000001
14Anders BjorkMoose (Win)LW3951318-314042178636555.81%1441210.57000070005440053.33%15225000.8722000100
15Vinni LettieriMoose (Win)RW4841317-102044215219337.69%1759612.43112142000000054.55%2266000.5700000000
16Jake LeschyshynMoose (Win)C696915-7400743437122916.22%76599.55011060000731041.29%264111000.4600000010
17Juuso ValimakiMoose (Win)D59114151338020472223154.55%4275612.83011425000034000.00%0322000.4000000010
18Nick MerkleyMoose (Win)RW386915240191146162413.04%32977.8200009000000160.00%1022001.0100000011
19Boris KatchoukMoose (Win)LW636915-10140422346224413.04%134897.78000122000070040.00%15195000.6101000010
20Lane MacDermidMoose (Win)LW185611-910022175618238.93%1129016.132026150001260148.48%3374000.7601000010
21Matthew BenningMoose (Win)D74279624045865323153.77%65105014.19011173000177000.00%0830000.1700000010
22Kieffer BellowsMoose (Win)RW38415-178016162472516.67%22827.4300000000010033.33%394000.3500000000
23Josh MahuraMoose (Win)D30134712072616596.25%1234611.5600022200006000.00%0611000.2300000000
24Mitchell StephensMoose (Win)C14112-50051383312.50%11359.7000002000030157.14%5614000.2900000000
25Nelson NogierMoose (Win)D17022-9808218310.00%1421012.3800000011115000.00%029000.1900000000
26Nathan BastianMoose (Win)RW91121401352220.00%2404.5300001000080066.67%320000.9800000001
27Sam ReinhartJetsRW2011-500846160.00%14422.2401138000060050.00%1441000.4500000000
28William BittenMoose (Win)RW16011-6407510050.00%0915.700000000001000.00%211000.2200000000
29Urho VaakanainenMoose (Win)D8000320153200.00%3769.620000000002000.00%000000.00%00000000
30Max JonesMoose (Win)LW7000-200010000.00%181.230000000000000.00%000000.00%00000000
Team Total or Average1532326531857-8666515170616582800958156711.64%9642437015.916610517129725697613522006271649.98%4994597581240.701742100393632
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
1Filip GustavssonMoose (Win)41171640.8773.932247201471197596310.625163734021
2Brandon HalversonMoose (Win)41151930.8743.952249201481179589310.591223736002
3Karel VejmelkaMoose (Win)70500.8156.52276003016281000.00%0510000
4Daniel VladarMoose (Win)10100.8714.07590043115000.00%010000
Team Total or Average90324170.8724.084834403292569128162388080023


Filter Tips
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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 Type Current Salary Salary RemainingSalary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Link
Anders BjorkMoose (Win)LW211996-01-01Yes190 Lbs6 ft0NoNoNo1Pro & Farm600,000$0$0$NoLink
Boris KatchoukMoose (Win)LW191998-01-01Yes206 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Brandon HalversonMoose (Win)G211996-01-01No203 Lbs6 ft4NoNoNo1Pro & Farm850,000$0$0$NoLink
Chase De LeoMoose (Win)C211996-01-01Yes179 Lbs5 ft9NoNoNo1Pro & Farm750,000$0$0$NoLink
Daniel VladarMoose (Win)G201997-01-01Yes185 Lbs6 ft5NoNoNo3Pro & Farm500,000$0$0$No700,000$750,000$Link
Dylan StromeMoose (Win)C201997-01-01Yes200 Lbs6 ft3NoNoNo4Pro & Farm950,000$0$0$No975,000$1,500,000$2,250,000$Link
Erik CernakMoose (Win)D201997-01-01Yes233 Lbs6 ft3NoNoNo2Pro & Farm950,000$0$0$No975,000$Link
Filip GustavssonMoose (Win)G191998-01-01Yes183 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLink
Jake LeschyshynMoose (Win)C181999-01-01Yes192 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Joey DaccordMoose (Win)G211996-01-01No197 Lbs6 ft2NoNoNo1Pro & Farm600,000$0$0$NoLink
Jonathan KovacevicMoose (Win)D201997-01-01Yes208 Lbs6 ft4NoNoNo1Pro & Farm350,000$0$0$NoLink
Josh MahuraMoose (Win)D191998-01-01Yes185 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$NoLink
Julien GauthierMoose (Win)RW201997-01-01Yes227 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$NoLink
Juuso ValimakiMoose (Win)D191998-01-01Yes212 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Karel VejmelkaMoose (Win)G211996-01-01Yes224 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Kieffer BellowsMoose (Win)RW191998-01-01Yes194 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$NoLink
Kyle ConnorMoose (Win)LW211996-01-01Yes182 Lbs6 ft1NoNoNo3Pro & Farm800,000$0$0$No950,000$1,750,000$Link
Lane MacDermidMoose (Win)LW281989-01-01No215 Lbs6 ft3NoNoNo1Pro & Farm700,000$0$0$No
Ludwig BystromMoose (Win)D231994-01-01Yes169 Lbs6 ft0NoNoNo1Pro & Farm975,000$0$0$NoLink
Mathieu JosephMoose (Win)RW201997-01-01Yes190 Lbs6 ft1NoNoNo3Pro & Farm950,000$0$0$No975,000$1,000,000$Link
Matthew BenningMoose (Win)D231994-01-01Yes180 Lbs6 ft0NoNoNo1Pro & Farm750,000$0$0$NoLink
Max JonesMoose (Win)LW191998-01-01Yes220 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$NoLink
Michael McLeodMoose (Win)C191998-01-01Yes187 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLink
Mirco MuellerMoose (Win)D221995-01-01Yes185 Lbs6 ft4NoNoNo1Pro & Farm990,000$0$0$NoLink
Mitchell StephensMoose (Win)C201997-01-01Yes193 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Nathan BastianMoose (Win)RW201997-01-01Yes205 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$NoLink
Nathan WalkerMoose (Win)LW231994-01-01Yes186 Lbs5 ft9NoNoNo1Pro & Farm850,000$0$0$NoLink
Nelson NogierMoose (Win)D211996-01-01Yes191 Lbs6 ft2NoNoNo1Pro & Farm600,000$0$0$NoLink
Nick MerkleyMoose (Win)RW201997-01-01Yes194 Lbs5 ft10NoNoNo4Pro & Farm550,000$0$0$No550,000$650,000$650,000$Link
Nikolay GoldobinMoose (Win)LW211996-01-01Yes196 Lbs5 ft11NoNoNo1Pro & Farm850,000$0$0$NoLink
Roman JosiMoose (Win)D271990-01-01No198 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$0$0$No
Tim GettingerMoose (Win)LW191998-01-01Yes220 Lbs6 ft6NoNoNo1Pro & Farm500,000$0$0$NoLink
Tomas JurcoMoose (Win)RW251992-01-01No203 Lbs6 ft1NoNoNo1Pro & Farm700,000$0$0$No
Urho VaakanainenMoose (Win)D181999-01-01Yes200 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Vinni LettieriMoose (Win)RW221995-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
William BittenMoose (Win)RW191998-01-01Yes179 Lbs5 ft10NoNoNo1Pro & Farm500,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3620.78197 Lbs6 ft11.56646,250$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Kyle ConnorDylan StromeNick Merkley40122
2Nathan WalkerMichael McLeodMathieu Joseph30122
3Nikolay GoldobinMitchell StephensJulien Gauthier20122
4Boris KatchoukJake LeschyshynKieffer Bellows10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Mirco MuellerJuuso Valimaki40122
2Josh MahuraErik Cernak30122
3Matthew BenningLudwig Bystrom20122
4Mirco MuellerLudwig Bystrom10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Kyle ConnorDylan StromeNick Merkley60122
2Nikolay GoldobinMichael McLeodMathieu Joseph40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Mirco MuellerJuuso Valimaki60122
2Ludwig BystromJosh Mahura40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Dylan StromeNathan Walker60122
2Mitchell StephensKyle Connor40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Mirco MuellerLudwig Bystrom60122
2Matthew BenningErik Cernak40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Mitchell Stephens60122Mirco MuellerLudwig Bystrom60122
2Jake Leschyshyn40122Matthew BenningErik Cernak40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Dylan StromeKyle Connor60122
2Michael McLeodMathieu Joseph40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Mirco MuellerLudwig Bystrom60122
2Juuso ValimakiErik Cernak40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Kyle ConnorDylan StromeMathieu JosephMirco MuellerLudwig Bystrom
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Kyle ConnorDylan StromeMathieu JosephMirco MuellerErik Cernak
Extra Forwards
Normal PowerPlayPenalty Kill
Mathieu Joseph, Dylan Strome, Kyle ConnorMathieu Joseph, Dylan StromeMathieu Joseph
Extra Defensemen
Normal PowerPlayPenalty Kill
Erik Cernak, Matthew Benning, Josh MahuraErik CernakMatthew Benning, Josh Mahura
Penalty Shots
Dylan Strome, Nathan Walker, Kyle Connor, Nikolay Goldobin, Mathieu Joseph
Goalie
#1 : Daniel Vladar, #2 : Filip Gustavsson


Filter Tips
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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
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
1Admirals311000011213-12100000110821010000025-330.50012193100969711416117890884912499139186311218.18%9366.67%0973191850.73%882183048.20%677131251.60%172195916947491430718
2Barracuda613001102428-4302001001014-4311000101414050.4172439630096971141621789088491249202666211331619.35%311067.74%0973191850.73%882183048.20%677131251.60%172195916947491430718
3Bears2100000110641000000145-11100000061530.750101626009697114166789088491249692512356350.00%6183.33%0973191850.73%882183048.20%677131251.60%172195916947491430718
4Comets2020000069-31010000045-11010000024-200.000611170096971141679890884912496219143911218.18%7357.14%0973191850.73%882183048.20%677131251.60%172195916947491430718
5Condors622010102116531200000910-131001010126680.6672132530096971141620089088491249181875411935514.29%28389.29%3973191850.73%882183048.20%677131251.60%172195916947491430718
6Crunch2020000059-41010000035-21010000024-200.0005813109697114166889088491249682512451200.00%6266.67%0973191850.73%882183048.20%677131251.60%172195916947491430718
7Devils211000009811010000045-11100000053220.50091423009697114165789088491249572122444125.00%11281.82%1973191850.73%882183048.20%677131251.60%172195916947491430718
8Eagles201000101213-11010000046-21000001087120.5001217291096971141656890884912497422185010220.00%9188.89%0973191850.73%882183048.20%677131251.60%172195916947491430718
9Griffins623000102021-132100000121203020001089-160.5002031510096971141618289088491249194595214539512.82%26965.38%1973191850.73%882183048.20%677131251.60%172195916947491430718
10Heat30300000815-720200000712-51010000013-200.000813210096971141680890884912499227286413323.08%14285.71%0973191850.73%882183048.20%677131251.60%172195916947491430718
11Icehogs30300000913-41010000024-22020000079-200.00091524009697114169189088491249883015764125.00%60100.00%0973191850.73%882183048.20%677131251.60%172195916947491430718
12Little Stars412001001315-2311001001011-11010000034-130.37513223500969711416133890884912491344634898112.50%17288.24%0973191850.73%882183048.20%677131251.60%172195916947491430718
13Marlies321000001917211000000105521100000912-340.6671933520096971141611489088491249892426639444.44%13653.85%0973191850.73%882183048.20%677131251.60%172195916947491430718
14Monsters30300000514-91010000024-220200000310-700.00059140096971141610089088491249109443263600.00%16568.75%0973191850.73%882183048.20%677131251.60%172195916947491430718
15Penguins30200100814-61010000035-22010010059-410.1678152300969711416108890884912499737264610220.00%13192.31%0973191850.73%882183048.20%677131251.60%172195916947491430718
16Phantoms321000001515021100000911-21100000064240.6671524390096971141699890884912491113827519111.11%11463.64%0973191850.73%882183048.20%677131251.60%172195916947491430718
17Punishers220000001055110000005231100000053241.0001018280096971141671890884912495220164110330.00%8275.00%0973191850.73%882183048.20%677131251.60%172195916947491430718
18Rampage2010000147-31010000024-21000000123-110.250459009697114166689088491249522820367114.29%10190.00%0973191850.73%882183048.20%677131251.60%172195916947491430718
19Reign422000002218420200000810-222000000148640.500223860009697114161508908849124912645388615640.00%19289.47%0973191850.73%882183048.20%677131251.60%172195916947491430718
20Rocket624000002331-83120000013103312000001021-1140.3332337600096971141619289088491249195676514126934.62%32778.13%0973191850.73%882183048.20%677131251.60%172195916947491430718
21Senators3300000016791100000063322000000104661.0001629450096971141698890884912499044106315426.67%50100.00%0973191850.73%882183048.20%677131251.60%172195916947491430718
22Sound Tigers210000011091110000006421000000145-130.750101626009697114167189088491249653110511119.09%5340.00%0973191850.73%882183048.20%677131251.60%172195916947491430718
23Thunderbirds20200000711-41010000036-31010000045-100.0007142100969711416728908849124972251241800.00%6183.33%0973191850.73%882183048.20%677131251.60%172195916947491430718
24Wolfpack21100000880110000004221010000046-220.5008152300969711416638908849124970291435700.00%7185.71%0973191850.73%882183048.20%677131251.60%172195916947491430718
25Wolves43100000161332200000073421100000910-160.75016284400969711416145890884912491314018901317.69%9366.67%0973191850.73%882183048.20%677131251.60%172195916947491430718
Total80274101344312335-2340142200202157166-940131901142155169-14710.44431251883020969711416269689088491249257193865516893306319.09%3247477.16%5973191850.73%882183048.20%677131251.60%172195916947491430718
_Since Last GM Reset80274101344312335-2340142200202157166-940131901142155169-14710.44431251883020969711416269689088491249257193865516893306319.09%3247477.16%5973191850.73%882183048.20%677131251.60%172195916947491430718
_Vs Conference49172601131194208-14248140010198103-5259120103096105-9440.44919431951300969711416164089088491249156857042710472134621.60%2105175.71%4973191850.73%882183048.20%677131251.60%172195916947491430718
_Vs Division24712011308896-81247001004446-21235010304450-6230.4798813922700969711416791890884912497722792335181312519.08%1172975.21%4973191850.73%882183048.20%677131251.60%172195916947491430718

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8071L231251883026962571938655168920
All Games
GPWLOTWOTL SOWSOLGFGA
8027411344312335
Home Games
GPWLOTWOTL SOWSOLGFGA
4014220202157166
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4013191142155169
Last 10 Games
WLOTWOTL SOWSOL
090001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
3306319.09%3247477.16%5
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
89088491249969711416
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
973191850.73%882183048.20%677131251.60%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
172195916947491430718


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 - 2022-10-272Rocket5Moose4BLR1BoxScore
3 - 2022-10-2911Moose3Condors2AWXXR1BoxScore
6 - 2022-11-0131Moose5Barracuda4AWXXBoxScore
9 - 2022-11-0446Little Stars2Moose4BWBoxScore
12 - 2022-11-0763Griffins3Moose4BWR1BoxScore
14 - 2022-11-0973Moose3Griffins2AWXXBoxScore
16 - 2022-11-1181Moose3Rocket8ALR1BoxScore
19 - 2022-11-1496Barracuda4Moose2BLR1BoxScore
21 - 2022-11-16115Wolves2Moose3BWBoxScore
23 - 2022-11-18126Moose5Wolves3AWBoxScore
26 - 2022-11-21139Condors4Moose3BLR1BoxScore
28 - 2022-11-23151Moose6Condors2AWBoxScore
32 - 2022-11-27171Condors4Moose3BLR1BoxScore
35 - 2022-11-30185Moose8Barracuda4AWBoxScore
37 - 2022-12-02193Griffins5Moose7BWR1BoxScore
39 - 2022-12-04209Moose2Comets4ALBoxScore
42 - 2022-12-07221Eagles6Moose4BLBoxScore
45 - 2022-12-10237Monsters4Moose2BLBoxScore
48 - 2022-12-13250Moose6Phantoms4AWBoxScore
52 - 2022-12-17265Rocket3Moose2BLR1BoxScore
55 - 2022-12-20284Moose4Wolfpack6ALBoxScore
57 - 2022-12-22294Little Stars5Moose4BLXBoxScore
61 - 2022-12-26313Moose2Rampage3ALXXBoxScore
62 - 2022-12-27319Condors2Moose3BWR1BoxScore
66 - 2022-12-31335Moose1Heat3ALBoxScore
67 - 2023-01-01345Griffins4Moose1BLR1BoxScore
70 - 2023-01-04360Moose5Punishers3AWBoxScore
72 - 2023-01-06370Moose2Admirals5ALBoxScore
73 - 2023-01-07376Thunderbirds6Moose3BLBoxScore
77 - 2023-01-11396Heat5Moose3BLBoxScore
81 - 2023-01-15417Moose7Reign4AWBoxScore
82 - 2023-01-16424Senators3Moose6BWBoxScore
85 - 2023-01-19437Moose6Bears1AWBoxScore
87 - 2023-01-21449Bears5Moose4BLXXBoxScore
91 - 2023-01-25469Moose7Reign4AWBoxScore
92 - 2023-01-26475Punishers2Moose5BWBoxScore
95 - 2023-01-29497Wolves1Moose4BWBoxScore
97 - 2023-01-31506Moose8Eagles7AWXXBoxScore
101 - 2023-02-04524Little Stars4Moose2BLBoxScore
104 - 2023-02-07540Moose6Marlies4AWBoxScore
106 - 2023-02-09551Phantoms4Moose5BWBoxScore
108 - 2023-02-11562Moose3Marlies8ALBoxScore
110 - 2023-02-13574Moose4Thunderbirds5ALBoxScore
111 - 2023-02-14581Penguins5Moose3BLBoxScore
115 - 2023-02-18597Moose2Crunch4ALBoxScore
117 - 2023-02-20606Sound Tigers4Moose6BWBoxScore
119 - 2023-02-22618Moose1Rocket9ALR1BoxScore
122 - 2023-02-25634Rocket2Moose7BWBoxScore
124 - 2023-02-27644Moose5Devils3AWBoxScore
126 - 2023-03-01653Moose4Icehogs5ALBoxScore
128 - 2023-03-03662Wolfpack2Moose4BWBoxScore
130 - 2023-03-05680Moose4Wolves7ALBoxScore
132 - 2023-03-07687Heat7Moose4BLBoxScore
134 - 2023-03-09701Moose3Condors2AWXR1BoxScore
136 - 2023-03-11713Moose2Penguins5ALBoxScore
137 - 2023-03-12717Devils5Moose4BLBoxScore
141 - 2023-03-16738Crunch5Moose3BLBoxScore
144 - 2023-03-19751Moose6Rocket4AWR1BoxScore
147 - 2023-03-22764Comets5Moose4BLBoxScore
149 - 2023-03-24776Moose3Little Stars4ALBoxScore
152 - 2023-03-27791Moose3Penguins4ALXBoxScore
153 - 2023-03-28797Admirals3Moose6BWBoxScore
156 - 2023-03-31812Moose4Sound Tigers5ALXXBoxScore
158 - 2023-04-02820Icehogs4Moose2BLBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
161 - 2023-04-05834Moose3Icehogs4ALBoxScore
164 - 2023-04-08849Marlies5Moose10BWBoxScore
166 - 2023-04-10856Moose4Senators1AWBoxScore
168 - 2023-04-12871Barracuda4Moose3BLXR1BoxScore
170 - 2023-04-14882Moose6Senators3AWBoxScore
172 - 2023-04-16894Moose3Griffins4ALR1BoxScore
174 - 2023-04-18900Moose2Monsters3ALBoxScore
176 - 2023-04-20908Barracuda6Moose5BLR1BoxScore
178 - 2023-04-22921Moose2Griffins3ALR1BoxScore
179 - 2023-04-23927Moose1Barracuda6ALBoxScore
181 - 2023-04-25936Phantoms7Moose4BLBoxScore
183 - 2023-04-27946Moose1Monsters7ALBoxScore
186 - 2023-04-30961Reign6Moose5BLBoxScore
192 - 2023-05-06986Admirals5Moose4BLXXBoxScore
198 - 2023-05-121010Rampage4Moose2BLBoxScore
203 - 2023-05-171027Reign4Moose3BLBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3515
Attendance73,60137,754
Attendance PCT92.00%94.39%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 2784 - 92.80% 82,487$3,299,461$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
3,208,984$ 2,326,500$ 1,976,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
11,294$ 2,233,988$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 15,905$ 0$




Moose Stat Leaders (Regular Season)

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Moose Goalies Stat Leaders (Regular Season)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Moose Career Team Stats

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

Moose Stat Leaders (Play-Off)

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Moose Goalies Stat Leaders (Play-Off)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA