Wolf Pack

GP: 82 | W: 7 | L: 66 | OTL: 9 | P: 23
GF: 224 | GA: 426 | PP%: 20.28% | PK%: 73.53%
DG: Jonathan Laroche | Morale : 50 | Moyenne d'Équipe : 48
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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 SPÂgeContratSalaire Moyen
1Matt LuffX100.00734396647156765926675758254949050580223700,000$
2Hunter ShinkarukX100.00706691636561585650465464555252050550243900,000$
3Blake SpeersXX100.00747083686760615266464663455555050550221667,000$
4Cliff PuXX100.00777287557254564961494462424444050520212742,500$
5Tyler Moy (R)XXX100.00514690657065904558463545376464050520244650,000$
6Emerson EtemXX100.00524385617348334535424962504943050500272550,000$
7Tomas Hyka (R)XX100.00433591704554354849494754473734050490262710,000$
8Maxim MaminXXX100.00524382597248344335384750473734050460242732,500$
9Borna RendulicXX100.004635926469432931403131654537340504402756,500,000$
10Matt TennysonX100.00784886707663645425494563255858050600291850,000$
11Christian JarosX100.00784786637657725325544662255454050590232730,000$
12Matt BartkowskiX100.00746975657259615125444067386465050590313655,000$
13Joey LaLeggiaXX100.00726288686475785446464862464646050590275900,000$
14Kevin CzuczmanX100.00787384667668684925404065394646050580283700,000$
15Mark AltX100.00797483657768764825384264404444050580271700,000$
16Anton Karlsson (R)X100.00736982626963684625374059384444050550234700,000$
Rayé
1Tyler Kelleher (R)X100.00433486745474916255555745606464050580244525,000$
2Henrik HaapalaXX100.00403593654647313335343253463532050420252925,000$
3Jonne Tammela (R)XX100.00364040405735353640363640383230050380222716,112$
4Martins Dzierkals (R)X100.00374343435135353743373743403230050380221700,000$
5Max Zimmer (R)X100.00364040405935353640363640383230050380212650,000$
6Jordy Stallard (R)X100.00333737375833333337333337353230050350222525,000$
7Daniel SedinX100.001920202020191919201919202020200502103926,000,000$
8Simon Bourque (R)X100.00323737376331313237323237343230050360221525,000$
MOYENNE D'ÉQUIPE100.0056497458635253453842415340444305049
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
1Samu Perhonen (R)100.0038434068373535353535343230050390
2Karel Vejmelka (R)100.0033373576333232323232313230050380
Rayé
MOYENNE D'ÉQUIPE100.003640387235343434343433323005039
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'ÉquipePOSGP 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
1Hunter ShinkarukWolf Pack (Ran)LW81542983-7231519116845211328811.95%45167820.7312820691730000232254.24%11800040.9902001453
2Matt LuffWolf Pack (Ran)RW81313970-47200145165324812339.57%25170921.113253815101151651026.81%27600000.8215000342
3Matt BartkowskiWolf Pack (Ran)D79165268-5082026212417562959.14%181174822.146915641640000109110.00%000000.7800000232
4Blake SpeersWolf Pack (Ran)C/RW82133548-384210163222218741555.96%28140617.16178351550000431055.35%175800000.6803011011
5Christian JarosWolf Pack (Ran)D8183846-5247518185139411015.76%164162620.0821113511460112125010.00%000000.5700010101
6Tobias BjornfotRangersD62112940-395210867914234997.75%94118019.04461063118101590000.00%000000.6800101020
7Cliff PuWolf Pack (Ran)C/RW81192039-47480227160198591469.60%32133516.494482676000010051.26%83500000.5800000201
8Tomas HykaWolf Pack (Ran)LW/RW81191433-54206145242691637.85%11133116.4422418520000180133.33%9000010.5000000300
9Marko DanoRangersLW/RW52141832-15010125108157481178.92%880615.510005260000171237.93%5800000.7900002122
10Kevin CzuczmanWolf Pack (Ran)D8171926-75912519010610937696.42%144135316.71325203800002100100.00%100000.3800302001
11Matt TennysonWolf Pack (Ran)D4341822-2120073435917446.78%6181018.841342256000035010.00%000000.5400000001
12Anton KarlssonWolf Pack (Ran)D8131619-72200109636215514.84%124135116.6901148000080000.00%000000.2800000001
13Tyler MoyWolf Pack (Ran)C/LW/RW8110919-4220238910123329.90%6134416.6021391460001240254.53%77200000.2800000010
14Maxim MaminWolf Pack (Ran)C/LW/RW8131013-368067809126643.30%2082110.140114170004610038.58%74400000.3200000010
15Mark AltWolf Pack (Ran)D4721012152409619447244.55%5570114.9300037000010000.00%000000.3400000003
16Cole BardreauRangersC/RW115510-108027303972412.82%120618.761457260000141153.10%22600000.9701000020
17Borna RendulicWolf Pack (Ran)LW/RW296410-2120113747174012.77%1649116.9301129000020036.67%3000000.4100000000
18Tyler KelleherWolf Pack (Ran)RW10279-1100327327306.25%223523.521125270001310147.44%7800000.7712000000
19Trevor LewisRangersC/RW14088-41001842399310.00%327019.340006360003250049.23%32300000.5900000000
20Joey LaLeggiaWolf Pack (Ran)LW/D10156-240917224144.55%1023523.510118290000240020.00%500000.5102000002
21MacKenzie EntwistleRangersRW11044-126019272315340.00%218616.97000000000170057.14%3500000.4311000000
22Ilya LyubushkinRangersD1011020103120.00%01919.620000000001000.00%000001.0200000000
23Juuso RiikolaRangersD1011000253000.00%52020.170001000002000.00%000000.9900000000
24Anton LindholmRangersD31012207723450.00%66622.080000600009000.00%000000.3000000000
25Mike VecchioneRangersC/RW1101-1002361316.67%11616.6800011000000048.00%2500001.2000000000
26Emerson EtemWolf Pack (Ran)LW/RW1000000012100.00%01515.75000000000000100.00%100000.0000000000
27Henrik HaapalaWolf Pack (Ran)LW/RW7000-2003112140.00%011716.8300002000050030.00%1000000.0000000000
Stats d'équipe Total ou en Moyenne1193230391621-6925736520461863273377218678.42%10442108917.68426410646114831232196471249.47%538500050.59316427162120
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
1Samu PerhonenWolf Pack (Ran)3452430.8835.1616980014612530000.61513340101
2Karel VejmelkaWolf Pack (Ran)5723950.8785.5126052023919630210.400154781000
Stats d'équipe Total ou en Moyenne9176380.8805.3743032038532160210.500288181101


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 Type Salaire Actuel Salaire RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Anton KarlssonWolf Pack (Ran)D231996-08-03Yes187 Lbs6 ft1NoNoNo4Pro & Farm700,000$70,000$0$No700,000$700,000$700,000$Lien
Blake SpeersWolf Pack (Ran)C/RW221997-01-02No185 Lbs5 ft11NoNoNo1Pro & Farm667,000$66,700$0$NoLien
Borna RendulicWolf Pack (Ran)LW/RW271992-03-25No200 Lbs6 ft2NoNoNo5Pro & Farm6,500,000$650,000$0$No6,500,000$6,500,000$6,500,000$6,500,000$Lien
Christian JarosWolf Pack (Ran)D231996-04-02No201 Lbs6 ft3NoNoNo2Pro & Farm730,000$73,000$0$No730,000$Lien
Cliff PuWolf Pack (Ran)C/RW211998-06-03No192 Lbs6 ft2NoNoNo2Pro & Farm742,500$74,250$0$No742,500$Lien
Daniel Sedin (Contrat à 1 Volet)Wolf Pack (Ran)LW391980-09-26No190 Lbs6 ft1NoNoNo2Pro & Farm6,000,000$6,000,000$0$No6,000,000$Lien
Emerson EtemWolf Pack (Ran)LW/RW271992-06-16No212 Lbs6 ft1NoNoNo2Pro & Farm550,000$55,000$0$No550,000$Lien
Henrik HaapalaWolf Pack (Ran)LW/RW251994-02-28No165 Lbs5 ft9NoNoNo2Pro & Farm925,000$92,500$0$No925,000$Lien
Hunter ShinkarukWolf Pack (Ran)LW241994-10-13No181 Lbs5 ft10NoNoNo3Pro & Farm900,000$90,000$0$No900,000$900,000$Lien
Joey LaLeggiaWolf Pack (Ran)LW/D271992-06-24No182 Lbs5 ft9NoNoNo5Pro & Farm900,000$90,000$0$No900,000$900,000$900,000$900,000$Lien
Jonne TammelaWolf Pack (Ran)LW/RW221997-08-05Yes186 Lbs5 ft10NoNoNo2Pro & Farm716,112$71,611$0$No716,112$Lien
Jordy StallardWolf Pack (Ran)C221997-09-18Yes185 Lbs6 ft1NoNoNo2Pro & Farm525,000$52,500$0$No525,000$Lien
Karel VejmelkaWolf Pack (Ran)G231996-05-25Yes202 Lbs6 ft3NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Kevin CzuczmanWolf Pack (Ran)D281991-01-09No206 Lbs6 ft2NoNoNo3Pro & Farm700,000$70,000$0$No700,000$700,000$Lien
Mark AltWolf Pack (Ran)D271991-10-17No201 Lbs6 ft4NoNoNo1Pro & Farm700,000$70,000$0$NoLien
Martins DzierkalsWolf Pack (Ran)RW221997-04-04Yes173 Lbs5 ft11NoNoNo1Pro & Farm700,000$70,000$0$NoLien
Matt BartkowskiWolf Pack (Ran)D311988-06-04No196 Lbs6 ft1NoNoNo3Pro & Farm650,000$65,500$0$No600,000$575,000$Lien
Matt LuffWolf Pack (Ran)RW221997-05-04No188 Lbs6 ft3NoNoNo3Pro & Farm700,000$70,000$0$No700,000$700,000$Lien
Matt TennysonWolf Pack (Ran)D291990-04-23No205 Lbs6 ft2NoNoNo1Pro & Farm850,000$85,000$0$NoLien
Max ZimmerWolf Pack (Ran)LW211997-10-29Yes187 Lbs6 ft0NoNoNo2Pro & Farm650,000$65,000$0$No650,000$Lien
Maxim MaminWolf Pack (Ran)C/LW/RW241995-01-13No206 Lbs6 ft2NoNoNo2Pro & Farm732,500$73,250$0$No732,500$Lien
Samu PerhonenWolf Pack (Ran)G261993-03-07Yes184 Lbs6 ft5NoNoNo4Pro & Farm700,000$70,000$0$No700,000$700,000$700,000$Lien
Simon BourqueWolf Pack (Ran)D221997-01-12Yes195 Lbs6 ft1NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Tomas HykaWolf Pack (Ran)LW/RW261993-03-23Yes160 Lbs5 ft11NoNoNo2Pro & Farm710,000$71,000$0$No710,000$Lien
Tyler KelleherWolf Pack (Ran)RW241995-01-02Yes161 Lbs5 ft6NoNoNo4Pro & Farm525,000$52,500$0$No525,000$525,000$525,000$Lien
Tyler MoyWolf Pack (Ran)C/LW/RW241995-07-18Yes194 Lbs6 ft1NoNoNo4Pro & Farm650,000$65,000$0$No650,000$650,000$650,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2625.04189 Lbs6 ft12.461,122,043$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Hunter ShinkarukBlake SpeersMatt Luff40122
2Tomas HykaTyler MoyCliff Pu30122
3Borna RendulicMaxim Mamin20122
4Blake SpeersMatt LuffHunter Shinkaruk10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt TennysonMatt Bartkowski40122
2Christian Jaros30122
3Kevin CzuczmanAnton Karlsson20122
4Matt TennysonMatt Bartkowski10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Hunter ShinkarukBlake SpeersMatt Luff60122
2Tomas HykaTyler MoyCliff Pu40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt TennysonMatt Bartkowski60122
2Christian Jaros40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Matt LuffBlake Speers60122
2Hunter ShinkarukTyler Moy40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt TennysonMatt Bartkowski60122
2Christian Jaros40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Matt Luff60122Matt TennysonMatt Bartkowski60122
2Blake Speers40122Christian Jaros40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Matt LuffBlake Speers60122
2Hunter ShinkarukTyler Moy40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt TennysonMatt Bartkowski60122
2Christian Jaros40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Hunter ShinkarukBlake SpeersMatt LuffMatt TennysonMatt Bartkowski
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Hunter ShinkarukBlake SpeersMatt LuffMatt TennysonMatt Bartkowski
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Maxim Mamin, Borna Rendulic, Maxim Mamin, Borna Rendulic
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Kevin Czuczman, Anton Karlsson, Christian JarosKevin CzuczmanAnton Karlsson, Christian Jaros
Tirs de Pénalité
Matt Luff, Blake Speers, Hunter Shinkaruk, Tyler Moy, Cliff Pu
Gardien
#1 : Samu Perhonen, #2 : Karel Vejmelka


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
1Admirals2020000038-51010000013-21010000025-300.00035810858156459906842836527815443600.00%2150.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
2Baby Hawks20200000812-41010000047-31010000045-100.00081523008581564549068428365299282418225.00%110.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
3Bears404000001224-1220200000612-620200000612-600.00012213300858156412890684283652208592710418738.89%11190.91%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
4Bruins30300000713-62020000059-41010000024-200.00071320008581564929068428365213336296811327.27%11372.73%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
5Cabaret Lady Mary Ann311000011416-21010000046-2210000011010030.500142438008581564185906842836521353420834125.00%9366.67%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
6Caroline404000001222-1020200000713-62020000059-400.000122032008581564107906842836521935338925120.00%15660.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
7Chiefs2010001068-2100000104311010000025-320.50061016008581564479068428365290301340500.00%2150.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
8Chill20200000412-81010000036-31010000016-500.00048120085815647490684283652823312478112.50%6266.67%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
9Comets20200000410-61010000024-21010000026-400.000471100858156458906842836528231639600.00%30100.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
10Cougars30300000613-72020000059-41010000014-300.000691500858156487906842836521252810535120.00%5180.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
11Crunch30300000817-920200000612-61010000025-300.00081321008581564939068428365215635663500.00%3166.67%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
12Heat2020000039-61010000024-21010000015-400.0003580085815646490684283652912812492150.00%6183.33%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
13Jayhawks20200000510-51010000046-21010000014-300.0005813008581564659068428365289172155200.00%30100.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
14Las Vegas20100001510-51000000134-11010000026-410.2505712008581564549068428365291264547114.29%20100.00%11177250546.99%1117259743.01%682148645.90%1812122720856041074524
15Manchots413000001425-1120200000614-821100000811-320.2501427410085815641079068428365221357207710110.00%10460.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
16Marlies30300000419-1520200000314-111010000015-400.00047110085815649090684283652143342080700.00%10550.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
17Minnesota2110000012111110000007521010000056-120.500121628008581564889068428365295241268200.00%6183.33%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
18Monarchs20200000615-91010000045-110100000210-800.0006111700858156469906842836521134212496116.67%5260.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
19Monsters403010001017-72010100078-12020000039-620.2501018280085815641209068428365215731221051119.09%10190.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
20Monsters20200000512-71010000025-31010000037-400.00059140085815646390684283652101291151300.00%3166.67%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
21Oceanics2110000047-3110000002111010000026-420.500481200858156437906842836521052120618225.00%90100.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
22Oil Kings20200000512-71010000045-11010000017-600.0005914008581564579068428365298351243400.00%6183.33%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
23Phantoms403000011525-1020100001812-420200000713-610.1251528430085815641079068428365219855228612216.67%11554.55%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
24Rocket3010000269-31000000123-12010000146-220.333610160085815641019068428365210127136111218.18%4250.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
25Senators30300000918-91010000036-320200000612-600.00091524008581564929068428365217942266310440.00%12191.67%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
26Sharks20200000111-101010000006-61010000015-400.000123008581564419068428365291251938200.00%20100.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
27Sound Tigers40300001922-1320200000212-1020100001710-310.125916250085815641349068428365214848258511218.18%10370.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
28Spiders412000011317-42110000086220100001511-630.3751321340085815641429068428365216363267519631.58%13469.23%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
29Stars2020000059-41010000035-21010000024-200.00058130085815648790684283652813515466350.00%5260.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
30Thunder30100002913-41000000134-12010000169-320.3339152400858156410790684283652953518593266.67%9188.89%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
Total8256601019224426-2024133201014120209-894123400005104217-113230.1402243856091085815642609906842836523733105649718782174420.28%2045473.53%11177250546.99%1117259743.01%682148645.90%1812122720856041074524
_Since Last GM Reset8256601019224426-2024133201014120209-894123400005104217-113230.1402243856091085815642609906842836523733105649718782174420.28%2045473.53%11177250546.99%1117259743.01%682148645.90%1812122720856041074524
_Vs Conference4633701005120246-126232180100261118-57231190000359128-69130.141120215335108581564139990684283652210659630210401423222.54%1313374.81%01177250546.99%1117259743.01%682148645.90%1812122720856041074524
_Vs Division281110100385152-671415010014477-331406000024175-3470.12585151236008581564845906842836521280366180624862023.26%802470.00%01177250546.99%1117259743.01%682148645.90%1812122720856041074524

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8223L2224385609260937331056497187810
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
825661019224426
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
413321014120209
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
412340005104217
Derniers 10 Matchs
WLOTWOTL SOWSOL
350002
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2174420.28%2045473.53%1
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
906842836528581564
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
1177250546.99%1117259743.01%682148645.90%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1812122720856041074524


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 - 2020-10-236Oceanics1Wolf Pack2WSommaire du Match
4 - 2020-10-2520Wolf Pack3Senators6LSommaire du Match
11 - 2020-11-0161Oil Kings5Wolf Pack4LSommaire du Match
16 - 2020-11-06100Wolf Pack5Spiders6LXXSommaire du Match
17 - 2020-11-07109Wolf Pack2Bears6LSommaire du Match
19 - 2020-11-09124Comets4Wolf Pack2LSommaire du Match
21 - 2020-11-11136Jayhawks6Wolf Pack4LSommaire du Match
23 - 2020-11-13147Crunch6Wolf Pack2LSommaire du Match
26 - 2020-11-16175Bruins5Wolf Pack2LSommaire du Match
28 - 2020-11-18181Thunder4Wolf Pack3LXXSommaire du Match
32 - 2020-11-22205Wolf Pack1Chill6LSommaire du Match
34 - 2020-11-24221Senators6Wolf Pack3LSommaire du Match
36 - 2020-11-26235Cougars5Wolf Pack4LSommaire du Match
37 - 2020-11-27241Wolf Pack1Caroline4LSommaire du Match
40 - 2020-11-30263Cabaret Lady Mary Ann6Wolf Pack4LSommaire du Match
42 - 2020-12-02274Manchots7Wolf Pack5LSommaire du Match
44 - 2020-12-04287Wolf Pack3Thunder5LSommaire du Match
46 - 2020-12-06306Wolf Pack5Cabaret Lady Mary Ann6LXXSommaire du Match
50 - 2020-12-10332Bears6Wolf Pack4LSommaire du Match
52 - 2020-12-12347Wolf Pack3Senators6LSommaire du Match
53 - 2020-12-13354Wolf Pack3Rocket4LXXSommaire du Match
55 - 2020-12-15366Minnesota5Wolf Pack7WSommaire du Match
57 - 2020-12-17381Caroline5Wolf Pack2LSommaire du Match
59 - 2020-12-19391Wolf Pack2Bruins4LSommaire du Match
60 - 2020-12-20403Wolf Pack0Spiders5LSommaire du Match
62 - 2020-12-22420Las Vegas4Wolf Pack3LXXSommaire du Match
65 - 2020-12-25444Wolf Pack1Monsters5LSommaire du Match
66 - 2020-12-26448Rocket3Wolf Pack2LXXSommaire du Match
68 - 2020-12-28465Wolf Pack2Las Vegas6LSommaire du Match
70 - 2020-12-30483Wolf Pack2Monarchs10LSommaire du Match
72 - 2021-01-01498Wolf Pack1Sharks5LSommaire du Match
74 - 2021-01-03503Wolf Pack2Admirals5LSommaire du Match
76 - 2021-01-05520Chill6Wolf Pack3LSommaire du Match
80 - 2021-01-09550Marlies8Wolf Pack1LSommaire du Match
82 - 2021-01-11565Admirals3Wolf Pack1LSommaire du Match
83 - 2021-01-12574Wolf Pack5Phantoms6LSommaire du Match
87 - 2021-01-16584Caroline8Wolf Pack5LSommaire du Match
88 - 2021-01-17594Wolf Pack1Marlies5LSommaire du Match
91 - 2021-01-20624Wolf Pack1Oil Kings7LSommaire du Match
93 - 2021-01-22635Wolf Pack1Heat5LSommaire du Match
95 - 2021-01-24651Wolf Pack2Comets6LSommaire du Match
98 - 2021-01-27666Monsters5Wolf Pack2LSommaire du Match
100 - 2021-01-29682Spiders4Wolf Pack3LSommaire du Match
102 - 2021-01-31698Wolf Pack2Chiefs5LSommaire du Match
104 - 2021-02-02710Sound Tigers6Wolf Pack1LSommaire du Match
107 - 2021-02-05730Wolf Pack5Sound Tigers6LXXSommaire du Match
110 - 2021-02-08758Monsters5Wolf Pack3LSommaire du Match
112 - 2021-02-10762Sound Tigers6Wolf Pack1LSommaire du Match
122 - 2021-02-20785Cougars4Wolf Pack1LSommaire du Match
123 - 2021-02-21797Wolf Pack1Cougars4LSommaire du Match
125 - 2021-02-23810Stars5Wolf Pack3LSommaire du Match
127 - 2021-02-25825Marlies6Wolf Pack2LSommaire du Match
129 - 2021-02-27840Crunch6Wolf Pack4LSommaire du Match
131 - 2021-03-01857Monarchs5Wolf Pack4LSommaire du Match
133 - 2021-03-03872Wolf Pack2Oceanics6LSommaire du Match
135 - 2021-03-05887Wolf Pack5Minnesota6LSommaire du Match
136 - 2021-03-06893Wolf Pack2Monsters4LSommaire du Match
138 - 2021-03-08907Bruins4Wolf Pack3LSommaire du Match
141 - 2021-03-11927Wolf Pack4Baby Hawks5LSommaire du Match
143 - 2021-03-13942Wolf Pack4Caroline5LSommaire du Match
144 - 2021-03-14953Sharks6Wolf Pack0LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
147 - 2021-03-17971Wolf Pack2Sound Tigers4LSommaire du Match
149 - 2021-03-19985Wolf Pack1Rocket2LSommaire du Match
150 - 2021-03-20994Wolf Pack2Phantoms7LSommaire du Match
152 - 2021-03-221011Phantoms6Wolf Pack3LSommaire du Match
154 - 2021-03-241021Chiefs3Wolf Pack4WXXSommaire du Match
156 - 2021-03-261036Bears6Wolf Pack2LSommaire du Match
158 - 2021-03-281056Spiders2Wolf Pack5WSommaire du Match
161 - 2021-03-311076Wolf Pack2Stars4LSommaire du Match
162 - 2021-04-011081Wolf Pack3Monsters7LSommaire du Match
165 - 2021-04-041107Wolf Pack1Jayhawks4LSommaire du Match
167 - 2021-04-061119Heat4Wolf Pack2LSommaire du Match
169 - 2021-04-081133Manchots7Wolf Pack1LSommaire du Match
171 - 2021-04-101146Wolf Pack6Manchots5WSommaire du Match
173 - 2021-04-121165Wolf Pack2Crunch5LSommaire du Match
175 - 2021-04-141178Monsters3Wolf Pack4WXSommaire du Match
177 - 2021-04-161194Wolf Pack4Bears6LSommaire du Match
179 - 2021-04-181211Wolf Pack3Thunder4LXXSommaire du Match
181 - 2021-04-201225Wolf Pack5Cabaret Lady Mary Ann4WSommaire du Match
183 - 2021-04-221239Phantoms6Wolf Pack5LXXSommaire du Match
184 - 2021-04-231247Wolf Pack2Manchots6LSommaire du Match
186 - 2021-04-251257Baby Hawks7Wolf Pack4LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets4020
Assistance62,61326,769
Assistance PCT76.36%65.29%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2180 - 72.67% 74,144$3,039,900$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,185,151$ 2,317,311$ 2,317,811$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
12,461$ 2,185,863$ 26 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 12,459$ 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