Minnesota

GP: 82 | W: 42 | L: 33 | OTL: 7 | P: 91
GF: 326 | GA: 338 | PP%: 23.70% | PK%: 71.33%
DG: Fred Villiard | Morale : 50 | Moyenne d'Équipe : 44
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Astuces sur les Filtres (Anglais seulement)
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
# Nom du Joueur 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
1Chris TerryXX100.00493587746552385057435760594340050540
2J.T. BrownXXX100.00636179704957564841465059484946050540
3Evgeny Svechnikov (R)XX100.00553582627455365335485863563734050540
4Jonny Brodzinski (R)XX100.00543589637555404950435464453734050530
5Blake PietilaXX100.00483588646860404455444460483936050510
6Craig CunninghamXX100.00493589715647334152404268464136050500
7Jason AkesonX100.00413578716043303249353160424037050460
8Logan Brown (R)X100.00463595607849353743383550483532050460
9Chase De LeoX100.00423593775643313245323257463532050450
10Joseph Anderson (R)X100.00434343436343434343434343433230050440
11Alexander Guptill (R)X100.00394343435437373943393943413230050410
12Oliver KylingtonX100.00433593685747312935283064463532050490
13Bobby Nardella (R)X100.00454545455345454545454545453230050450
14Adam Fox (R)X100.00434343435743434343434343433230050440
15Miles Gendron (R)X100.00394343435637373943393943413230050420
Rayé
1Chris ThorburnXX100.00736667608450514558444658486657050540
2Travis Ewanyk (R)X100.00394343435437373943393943413230050410
3James WrightXX100.00416552427029453135313142454438050400
4David Pope (R)X100.00364040406135353640363640383230050400
5Martin Reway (R)XX100.00364040404235353640363640383230050390
6Mathias From (R)XX100.00373737374637373737373737373230050390
7Julius Vahatalo (R)X100.00333737376733333337333337353230050380
8Saku Maenalanen (R)XX100.00333737375533333337333337353230050370
9Anthony Louis (R)X100.00333737373533333337333337353230050360
10Kristopher FoucaultX100.00309030337029353135313133453532050360
11Filip Berglund (R)X100.00404040406940404040404040403230050420
MOYENNE D'ÉQUIPE100.0043436052614238394338404944373405045
Astuces sur les Filtres (Anglais seulement)
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
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Kevin Poulin100.0042458674424041423956554441050480
2Timo Pielmeier100.0034383662343333343333333532050380
Rayé
MOYENNE D'ÉQUIPE100.003842616838373738364544403705043
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les Filtres (Anglais seulement)
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
# Nom du Joueur Nom de l'ÉquipePOS 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
1Chris TerryMinnesota (Min)LW/RW823970109252157512632010626312.19%13147518.00132134772671123735056.84%9500011.4837001848
2J.T. BrownMinnesota (Min)C/LW/RW8243571000822018320631410221313.69%31175121.361319328331321392034143.31%222800001.143120131065
3Jonny BrodzinskiMinnesota (Min)C/RW8236641002234101081632636819213.69%27145817.79121830762700002462653.98%163400011.3725002775
4Evgeny SvechnikovMinnesota (Min)LW/RW8245509511609714135611324712.64%29159519.46151732893111123773341.44%18100101.19311000356
5Blake PietilaMinnesota (Min)LW/RW824038782216071982206114818.18%15138516.907121960272000027160.78%10200011.1322000654
6Will ButcherMinnesotaD63135366-171603381105387412.38%74138622.0162733622090110148200.00%000000.9500000033
7Travis DermottMinnesotaD63204161-1550011479115266117.39%90137121.77141529762070000136100.00%000000.8911000410
8Oliver KylingtonMinnesota (Min)D82939480100256683225410.84%113154618.8631316362060111141100.00%000000.6200000121
9Craig CunninghamMinnesota (Min)LW/RW68182139-62004097128309614.06%206739.9134714570000354151.72%8700001.1601000225
10Chase De LeoMinnesota (Min)C8282230-19260269361113613.11%81125615.32000030000140144.56%28500000.4800000010
11Jason AkesonMinnesota (Min)RW8291221-36603414414235976.34%21113313.821129470000231050.43%23400000.3700000112
12Joseph AndersonMinnesota (Min)RW8281321-193115732549123816.33%56167.52000010000002058.06%3100000.6800012021
13Logan BrownMinnesota (Min)C8271219-301002513010320936.80%26120414.69112145400011370050.05%110300000.3203000021
14Chris ThorburnMinnesota (Min)LW/RW18510155515631328112617.86%435919.952469680001402064.71%1700000.8413100110
15Adam FoxMinnesota (Min)D8221214-4820181171781011.76%51151318.45134719400021171025.00%400000.1900000000
16Miles GendronMinnesota (Min)D822911-1787514812173711.76%26119614.59022568000167100.00%100000.1800001000
17Alexander GuptillMinnesota (Min)LW816410-305410942256213510.71%887010.7400001000010044.00%5000000.2300011000
18Travis EwanykMinnesota (Min)LW14022-12801386360.00%31188.4500001000000050.00%600000.3400000000
19Bobby NardellaMinnesota (Min)D1000-100000000.00%01919.780000300002000.00%000000.0000000000
20James WrightMinnesota (Min)C/LW13000-600441010.00%01108.510001100000230038.78%4900000.0000000000
21Filip BerglundMinnesota (Min)D1000000200000.00%11515.730000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1306310529839-13762070140915252384690169713.00%6382106116.13911572486182582459231293361348.37%610700130.8015451310434241
Astuces sur les Filtres (Anglais seulement)
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
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Kevin PoulinMinnesota (Min)81422630.8644.0642568228821190500.66739810200
2Scott DarlingMinnesota10100.9002.0359002200000.000010000
3Timo PielmeierMinnesota (Min)200640.8893.8166220423790100.69213081000
Stats d'équipe Total ou en Moyenne102423370.8684.00497810233225180600.673528281200


Astuces sur les Filtres (Anglais seulement)
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
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Adam FoxMinnesota (Min)D191998-02-17Yes185 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Alexander GuptillMinnesota (Min)LW251992-05-05Yes175 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm840,000$84,000$0$NoLien
Anthony LouisMinnesota (Min)C221995-02-10Yes145 Lbs5 ft6NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Blake PietilaMinnesota (Min)LW/RW241993-02-20No200 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Bobby NardellaMinnesota (Min)D211996-04-22Yes178 Lbs5 ft9NoNoNo4Contrat d'EntréePro & Farm825,000$82,500$0$NoLien
Chase De LeoMinnesota (Min)C211995-10-25No185 Lbs5 ft9NoNoNo2Contrat d'EntréePro & Farm685,000$68,500$0$NoLien
Chris TerryMinnesota (Min)LW/RW281989-04-07No195 Lbs5 ft10NoNoNo6Sans RestrictionPro & Farm850,000$85,000$0$NoLien
Chris ThorburnMinnesota (Min)LW/RW341983-06-03No235 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm800,000$80,000$0$NoLien
Craig CunninghamMinnesota (Min)LW/RW271990-09-13No184 Lbs5 ft10YesNoNo6Avec RestrictionPro & Farm1,000,000$100,000$0$NoLien
David PopeMinnesota (Min)LW231994-09-27Yes187 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Evgeny SvechnikovMinnesota (Min)LW/RW201996-10-31Yes212 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm925,000$92,500$0$NoLien
Filip BerglundMinnesota (Min)D201997-05-10Yes209 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
J.T. BrownMinnesota (Min)C/LW/RW271990-07-02No169 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm900,000$90,000$0$NoLien
James WrightMinnesota (Min)C/LW271990-03-24No200 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm600,000$60,000$0$NoLien
Jason AkesonMinnesota (Min)RW271990-06-03No190 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm800,000$80,000$0$NoLien
Jonny BrodzinskiMinnesota (Min)C/RW241993-06-19Yes217 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm693,000$69,300$0$NoLien
Joseph AndersonMinnesota (Min)RW191998-06-19Yes192 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Julius VahataloMinnesota (Min)LW221995-05-23Yes191 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Kevin PoulinMinnesota (Min)G271990-04-12No199 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Kristopher FoucaultMinnesota (Min)LW261990-12-12No202 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm750,000$75,000$0$NoLien
Logan BrownMinnesota (Min)C191998-03-05Yes220 Lbs6 ft6NoNoNo4Contrat d'EntréePro & Farm925,000$92,500$0$NoLien
Martin RewayMinnesota (Min)C/LW221995-01-24Yes158 Lbs5 ft8NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Mathias FromMinnesota (Min)LW/RW191997-12-16Yes161 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Miles GendronMinnesota (Min)D211996-06-28Yes181 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Oliver KylingtonMinnesota (Min)D201997-05-19No183 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm743,000$74,300$0$NoLien
Saku MaenalanenMinnesota (Min)LW/RW231994-05-29Yes176 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Timo PielmeierMinnesota (Min)G281989-07-07No175 Lbs5 ft11YesNoNo6Sans RestrictionPro & Farm650,000$65,000$0$NoLien
Travis EwanykMinnesota (Min)LW241993-03-29Yes176 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm750,000$75,000$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2823.54189 Lbs6 ft02.96722,714$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1J.T. BrownEvgeny Svechnikov40122
2Chris TerryJonny BrodzinskiBlake Pietila30122
3Alexander GuptillLogan BrownJason Akeson20122
4Craig CunninghamChase De LeoJoseph Anderson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
2Oliver KylingtonAdam Fox30122
3Miles GendronChase De Leo20122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1J.T. BrownEvgeny Svechnikov60122
2Chris TerryJonny BrodzinskiBlake Pietila40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Oliver KylingtonAdam Fox40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1J.T. Brown60122
2Evgeny SvechnikovChris Terry40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Oliver KylingtonAdam Fox40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1J.T. Brown6012260122
240122Oliver KylingtonAdam Fox40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1J.T. Brown60122
2Evgeny SvechnikovChris Terry40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Oliver KylingtonAdam Fox40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
J.T. BrownEvgeny Svechnikov
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
J.T. BrownEvgeny Svechnikov
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Craig Cunningham, Jason Akeson, Logan BrownCraig Cunningham, Jason AkesonLogan Brown
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Miles Gendron, Oliver Kylington, Adam FoxMiles GendronOliver Kylington, Adam Fox
Tirs de Pénalité
J.T. Brown, , Evgeny Svechnikov, Chris Terry, Jonny Brodzinski
Gardien
#1 : Kevin Poulin, #2 : Timo Pielmeier


Astuces sur les Filtres (Anglais seulement)
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
LigueDomicileVisiteur
# VS Équipe 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
1Admirals321000001165211000007521100000041340.6671119300013786942090833771822756835316111327.27%13284.62%11190241249.34%1089234346.48%723148548.69%1955132819306261098551
2Baby Hawks412000101314-1210000109542020000049-540.500132336001378694201138337718227511634357027622.22%15473.33%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
3Bears2020000069-31010000024-21010000045-100.0006915001378694205083377182275651939407342.86%12558.33%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
4Bruins2110000046-21010000015-41100000031220.500481200137869420538337718227533910379333.33%5180.00%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
5Cabaret Lady Mary Ann220000001073110000006421100000043141.0001017270013786942093833771822756417143713323.08%7271.43%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
6Caroline20101000910-11010000057-21000100043120.500917260013786942074833771822757724123615213.33%6266.67%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
7Chiefs402000201418-42010001078-120100010710-340.50014213500137869420868337718227514530287220315.00%13653.85%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
8Chill411000021217-52100000177020100001510-540.500122234001378694201548337718227512338289218211.11%13284.62%11190241249.34%1089234346.48%723148548.69%1955132819306261098551
9Comets32100000151501100000063321100000912-340.66715243900137869420788337718227510827326016637.50%16662.50%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
10Cougars220000001156110000006331100000052341.0001120310013786942051833771822756115132010440.00%4175.00%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
11Crunch21000001981110000005321000000145-130.750916250013786942072833771822754215103810110.00%5260.00%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
12Heat3300000017981100000053222000000126661.00017284500137869420107833771822757918275621523.81%10370.00%11190241249.34%1089234346.48%723148548.69%1955132819306261098551
13Jayhawks30300000917-820200000612-61010000035-200.000918270013786942072833771822759937286610220.00%14378.57%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
14Las Vegas32100000121111100000031221100000910-140.667122032001378694209983377182275732528449111.11%9277.78%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
15Manchots22000000862110000004311100000043141.000814220013786942046833771822754296298225.00%3166.67%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
16Marlies20100001811-31000000145-11010000046-210.250813210013786942040833771822757914264111436.36%12466.67%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
17Monarchs311010001514121100000101001000100054140.66715243900137869420103833771822759727185817423.53%9277.78%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
18Monsters201001001013-31010000057-21000010056-110.250101727001378694206183377182275611019449222.22%7185.71%11190241249.34%1089234346.48%723148548.69%1955132819306261098551
19Monsters403000101822-4201000101314-12020000058-320.250182644001378694201108337718227513042378524937.50%16662.50%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
20Oceanics514000001829-11303000001116-521100000713-620.200183250001378694201188337718227520377429017317.65%21576.19%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
21Oil Kings31100001121021000000156-12110000074330.5001221330013786942085833771822756616195017529.41%7357.14%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
22Phantoms211000008711010000045-11100000042220.50081624001378694203583377182275461412315240.00%6266.67%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
23Rocket21001000523100010003211100000020241.00051015011378694206183377182275331112376116.67%60100.00%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
24Senators2110000059-41010000016-51100000043120.5005914001378694204183377182275609203010330.00%10460.00%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
25Sharks31100001161422100000114951010000025-330.50016284400137869420137833771822751404732691200.00%11463.64%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
26Sound Tigers210000101192100000106511100000054141.0001115260013786942054833771822755616123413323.08%6266.67%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
27Spiders20200000511-61010000023-11010000038-500.000581300137869420708337718227565146317114.29%3166.67%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
28Stars522000101618-22110000048-4311000101210260.600162743011378694201488337718227514447419018316.67%12375.00%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
29Thunder22000000743110000003211100000042241.00071219001378694205083377182275641525297228.57%9188.89%11190241249.34%1089234346.48%723148548.69%1955132819306261098551
Total82333303166326338-1241151701044172176-441181602122154162-8910.55532655788302137869420244783377182275251873167415303849123.70%2868271.33%51190241249.34%1089234346.48%723148548.69%1955132819306261098551
31Wolf Pack220000001275110000008531100000042241.000122335001378694209683377182275792012537342.86%6266.67%01190241249.34%1089234346.48%723148548.69%1955132819306261098551
_Since Last GM Reset82333303166326338-1241151701044172176-441181602122154162-8910.55532655788302137869420244783377182275251873167415303849123.70%2868271.33%51190241249.34%1089234346.48%723148548.69%1955132819306261098551
_Vs Conference42171602052170166419860103183794239100102187870500.5951702884580213786942012498337718227512373583367612165123.61%1404369.29%11190241249.34%1089234346.48%723148548.69%1955132819306261098551
_Vs Division24550003010796111231000205649712240001051474160.33310718228900137869420771833771822757302322154641132623.01%892571.91%21190241249.34%1089234346.48%723148548.69%1955132819306261098551

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8291W132655788324472518731674153002
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8233333166326338
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4115171044172176
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4118162122154162
Derniers 10 Matchs
WLOTWOTL SOWSOL
550000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3849123.70%2868271.33%5
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
83377182275137869420
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
1190241249.34%1089234346.48%723148548.69%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1955132819306261098551


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
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
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
2 - 2018-10-0413Minnesota1Monsters2LSommaire du Match
4 - 2018-10-0625Las Vegas1Minnesota3WSommaire du Match
9 - 2018-10-1156Baby Hawks2Minnesota3WXXSommaire du Match
11 - 2018-10-1360Caroline7Minnesota5LSommaire du Match
13 - 2018-10-1577Minnesota1Chill5LSommaire du Match
14 - 2018-10-1683Jayhawks6Minnesota3LSommaire du Match
17 - 2018-10-19100Minnesota3Stars5LSommaire du Match
18 - 2018-10-20110Thunder2Minnesota3WSommaire du Match
23 - 2018-10-25138Monarchs4Minnesota6WSommaire du Match
25 - 2018-10-27156Monsters7Minnesota8WXXSommaire du Match
27 - 2018-10-29166Minnesota4Comets8LSommaire du Match
28 - 2018-10-30174Minnesota2Oil Kings3LSommaire du Match
32 - 2018-11-03201Minnesota3Chiefs7LSommaire du Match
35 - 2018-11-06223Minnesota2Sharks5LSommaire du Match
37 - 2018-11-08235Minnesota5Monarchs4WXSommaire du Match
38 - 2018-11-09241Minnesota4Admirals1WSommaire du Match
40 - 2018-11-11253Minnesota4Chiefs3WXXSommaire du Match
42 - 2018-11-13269Bears4Minnesota2LSommaire du Match
44 - 2018-11-15282Comets3Minnesota6WSommaire du Match
46 - 2018-11-17294Crunch3Minnesota5WSommaire du Match
47 - 2018-11-18305Minnesota3Baby Hawks4LSommaire du Match
50 - 2018-11-21327Senators6Minnesota1LSommaire du Match
52 - 2018-11-23334Oceanics7Minnesota4LSommaire du Match
56 - 2018-11-27372Jayhawks6Minnesota3LSommaire du Match
58 - 2018-11-29383Minnesota5Monsters6LXSommaire du Match
60 - 2018-12-01397Marlies5Minnesota4LXXSommaire du Match
63 - 2018-12-04423Minnesota5Comets4WSommaire du Match
65 - 2018-12-06435Minnesota5Heat2WSommaire du Match
66 - 2018-12-07442Minnesota5Oil Kings1WSommaire du Match
70 - 2018-12-11472Rocket2Minnesota3WXSommaire du Match
72 - 2018-12-13484Cabaret Lady Mary Ann4Minnesota6WSommaire du Match
74 - 2018-12-15495Heat3Minnesota5WSommaire du Match
77 - 2018-12-18521Sharks6Minnesota5LXXSommaire du Match
79 - 2018-12-20533Minnesota4Manchots3WSommaire du Match
81 - 2018-12-22556Stars0Minnesota3WSommaire du Match
86 - 2018-12-27575Minnesota1Baby Hawks5LSommaire du Match
88 - 2018-12-29584Minnesota4Oceanics3WSommaire du Match
90 - 2018-12-31601Manchots3Minnesota4WSommaire du Match
93 - 2019-01-03621Minnesota4Marlies6LSommaire du Match
95 - 2019-01-05637Minnesota4Senators3WSommaire du Match
97 - 2019-01-07654Minnesota2Rocket0WSommaire du Match
98 - 2019-01-08657Minnesota3Bruins1WSommaire du Match
100 - 2019-01-10678Oceanics3Minnesota2LSommaire du Match
102 - 2019-01-12693Cougars3Minnesota6WSommaire du Match
104 - 2019-01-14708Minnesota4Phantoms2WSommaire du Match
105 - 2019-01-15717Monarchs6Minnesota4LSommaire du Match
107 - 2019-01-17731Admirals2Minnesota1LSommaire du Match
109 - 2019-01-19748Monsters7Minnesota5LSommaire du Match
111 - 2019-01-21758Minnesota3Las Vegas8LSommaire du Match
113 - 2019-01-23767Minnesota4Monsters6LSommaire du Match
122 - 2019-02-01788Minnesota5Stars4WXXSommaire du Match
123 - 2019-02-02799Baby Hawks3Minnesota6WSommaire du Match
126 - 2019-02-05810Minnesota4Crunch5LXXSommaire du Match
128 - 2019-02-07833Oil Kings6Minnesota5LXXSommaire du Match
130 - 2019-02-09840Minnesota3Spiders8LSommaire du Match
131 - 2019-02-10857Minnesota5Sound Tigers4WSommaire du Match
133 - 2019-02-12871Phantoms5Minnesota4LSommaire du Match
136 - 2019-02-15890Spiders3Minnesota2LSommaire du Match
138 - 2019-02-17905Chiefs4Minnesota5WXXSommaire du Match
140 - 2019-02-19922Admirals3Minnesota6WSommaire du Match
142 - 2019-02-21932Minnesota4Wolf Pack2WSommaire du Match
143 - 2019-02-22942Minnesota5Cougars2WSommaire du Match
145 - 2019-02-24959Chiefs4Minnesota2LSommaire du Match
147 - 2019-02-26976Minnesota3Oceanics10LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
151 - 2019-03-021008Minnesota7Heat4WSommaire du Match
152 - 2019-03-031015Chill3Minnesota2LXXSommaire du Match
154 - 2019-03-051024Minnesota4Chill5LXXSommaire du Match
156 - 2019-03-071037Minnesota4Thunder2WSommaire du Match
157 - 2019-03-081044Minnesota4Cabaret Lady Mary Ann3WSommaire du Match
160 - 2019-03-111068Sharks3Minnesota9WSommaire du Match
163 - 2019-03-141088Stars8Minnesota1LSommaire du Match
165 - 2019-03-161108Wolf Pack5Minnesota8WSommaire du Match
166 - 2019-03-171113Sound Tigers5Minnesota6WXXSommaire du Match
168 - 2019-03-191129Monsters7Minnesota5LSommaire du Match
171 - 2019-03-221148Minnesota4Bears5LSommaire du Match
172 - 2019-03-231158Minnesota4Caroline3WXSommaire du Match
174 - 2019-03-251174Chill4Minnesota5WSommaire du Match
178 - 2019-03-291202Minnesota6Las Vegas2WSommaire du Match
180 - 2019-03-311216Minnesota3Jayhawks5LSommaire du Match
182 - 2019-04-021234Oceanics6Minnesota5LSommaire du Match
184 - 2019-04-041250Bruins5Minnesota1LSommaire du Match
186 - 2019-04-061267Minnesota4Stars1WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance60,88031,139
Assistance PCT74.24%75.95%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2244 - 74.81% 63,363$2,597,885$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,108,450$ 2,023,600$ 2,023,600$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
10,821$ 2,108,450$ 28 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 10,821$ 0$




LigueDomicileVisiteur
Année 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
201882333303166326338-1241151701044172176-441181602122154162-89132655788302137869420244783377182275251873167415303849123.70%2868271.33%51190241249.34%1089234346.48%723148548.69%1955132819306261098551
Total Saison Régulière82333303166326338-1241151701044172176-441181602122154162-89132655788302137869420244783377182275251873167415303849123.70%2868271.33%51190241249.34%1089234346.48%723148548.69%1955132819306261098551