Wolf Pack

GP: 82 | W: 25 | L: 52 | OTL: 5 | P: 55
GF: 327 | GA: 421 | PP%: 19.81% | PK%: 75.78%
DG: Jeff Dumais | Morale : 50 | Moyenne d'Équipe : 44
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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
1Hunter ShinkarukXX100.00483586725553334735464762473734050510
2Borna RendulicXX100.00513594666949333340333365473734050470
3Mitch CallahanX100.00533594706244333335333366473734050470
4Sergei PlotnikovX100.00643580647044373549393260463532050470
5Blake SpeersXX100.00423594705746333335333367473532050470
6Jordan CaronXX100.00564382667145323235323257464943050460
7Cole Bardreau (R)XX100.00454545455745454545454545453230050450
8Mike VecchioneXX100.00423594726446333370333351473532050450
9Alexandre Mallet (R)XX100.00414545456739394145414145433230050440
10Cliff Pu (R)X100.00434343436643434343434343433230050440
11Anton Karlsson (R)XX100.00394343436037373943393943413230050420
12Max Zimmer (R)X100.00404040405940404040404040403230050420
13Matt BartkowskiX100.00704383616463434435454361485248050560
14Anton Lindholm (R)X100.00783587636161453635393274483734050560
15Christian Jaros (R)X100.00543595616744353135303262483532050490
16Gleason Fournier (R)X100.00394343436137373943393943413230050420
17Tomas KundratekX100.00308040496629453135313147453734050420
Rayé
1Jakub Culek (R)X100.00394343436037373943393943413230050420
2Pavel Kraskovsky (R)X100.00353737376835353537353537363230050390
3Jason Wilson (R)X100.00333737377133333337333337353230050380
4Adam PayerlXX100.00308535357629403135313135453532050370
5Kevin CzuczmanX100.00308436456829483135313135453532050400
6Simon Bourque (R)X100.00353737376335353537353537363230050390
7Joey Laleggia (R)X100.00333737375533333337333337353230050380
MOYENNE D'ÉQUIPE100.0045446052644238364037365043353305044
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
1Jared Coreau (R)100.0036458385354946355265453734050500
2Samu Perhonen (R)100.0041434168403939393939383230050420
Rayé
1Karel Vejmelka (R)100.0036373676363535353535353230050400
2Nicola Riopel100.0035373567343333333333333230050380
3Henri Kiviaho (R)100.0035373560343333333333333230050370
MOYENNE D'ÉQUIPE100.003740467136383735384137333105041
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Rod Brind'Amour57697165717067CAN471500,000$


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
1Dominik SimonRangersC/LW/RW5632447641160581012126014815.09%10105318.811010204719802251135256.07%10700021.4402000493
2Matt BenningRangersD451642581760011169107296014.95%5499122.036915521331014117200.00%000101.1700000644
3Jean-Sebastien DeaRangersC/RW5431245513515661872596918111.97%3476714.20112519000002162.51%93100011.43010121023
4Alexandre MalletWolf Pack (Ran)C/LW82231639-1782301141081675112313.77%307168.7400000000004045.74%96200001.0933213252
5Evan RodriguesRangersC/LW/RW109514700122734103226.47%317517.503146360000141166.89%14800011.6000000201
6Simon BourqueWolf Pack (Ran)D503912-1655591211781717.65%374288.560000000000000.00%000000.5600100001
7Christian JarosWolf Pack (Ran)D31099818034131814190.00%3360219.43044896000021000.00%000000.3000000011
8Blake SpeersWolf Pack (Ran)C/RW8000040310112100.00%49612.0800000000000030.00%1000000.0000000000
Stats d'équipe Total ou en Moyenne336114149263412705048953682524359013.82%205483014.38202545118483123926614454.87%215800141.0936325242115
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)82234550.8725.4539896036228290230.667278282621
Stats d'équipe Total ou en Moyenne82234550.8725.4539896036228290230.667278282621


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 PayerlWolf Pack (Ran)C/RW261991-03-04No218 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm600,000$60,000$0$NoLien
Alexandre MalletWolf Pack (Ran)C/LW251992-05-22Yes195 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm825,000$82,500$0$NoLien
Anton KarlssonWolf Pack (Ran)LW/RW211996-08-03Yes187 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Anton Lindholm (Sur la Masse Salariale)Wolf Pack (Ran)D221994-11-29Yes191 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm667,000$0$0$YesLien
Blake SpeersWolf Pack (Ran)C/RW201997-01-02No185 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm667,000$66,700$0$NoLien
Borna RendulicWolf Pack (Ran)LW/RW251992-03-25No200 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm610,000$61,000$0$NoLien
Christian JarosWolf Pack (Ran)D211996-04-02Yes201 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm730,000$73,000$0$NoLien
Cliff PuWolf Pack (Ran)C191998-06-03Yes193 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm742,500$74,250$0$NoLien
Cole BardreauWolf Pack (Ran)C/RW241993-07-22Yes185 Lbs5 ft10NoNoNo4Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Gleason FournierWolf Pack (Ran)D261991-09-08Yes191 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Henri KiviahoWolf Pack (Ran)G231994-02-26Yes167 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm615,000$61,500$0$NoLien
Hunter ShinkarukWolf Pack (Ran)LW/RW221994-10-13No181 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Jakub CulekWolf Pack (Ran)LW251992-09-07Yes185 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Jared CoreauWolf Pack (Ran)G251991-11-05Yes220 Lbs6 ft6NoNoNo2Avec RestrictionPro & Farm600,000$60,000$0$NoLien
Jason WilsonWolf Pack (Ran)LW221995-01-14Yes205 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Joey LaleggiaWolf Pack (Ran)D251992-07-24Yes182 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm843,000$84,300$0$NoLien
Jordan CaronWolf Pack (Ran)LW/RW261990-11-02No204 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm500,000$50,000$0$NoLien
Karel VejmelkaWolf Pack (Ran)G211996-05-25Yes202 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Kevin CzuczmanWolf Pack (Ran)D261991-01-09No204 Lbs6 ft3NoNoNo5Avec RestrictionPro & Farm500,000$50,000$0$NoLien
Matt BartkowskiWolf Pack (Ran)D291988-06-04No196 Lbs6 ft1YesNoNo5Sans RestrictionPro & Farm750,000$75,000$0$NoLien
Max ZimmerWolf Pack (Ran)LW191997-10-29Yes187 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Mike VecchioneWolf Pack (Ran)C/RW241993-02-25No194 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Mitch CallahanWolf Pack (Ran)RW261991-08-17No190 Lbs6 ft0NoNoNo5Avec RestrictionPro & Farm555,555$55,556$0$NoLien
Nicola RiopelWolf Pack (Ran)G281989-02-20No185 Lbs6 ft0NoNoNo2Sans RestrictionPro & Farm525,000$52,500$0$NoLien
Pavel KraskovskyWolf Pack (Ran)C211996-09-11Yes194 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Samu PerhonenWolf Pack (Ran)G241993-03-07Yes184 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Sergei PlotnikovWolf Pack (Ran)LW271990-06-03No202 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Simon BourqueWolf Pack (Ran)D201997-01-12Yes195 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Tomas KundratekWolf Pack (Ran)D271989-12-26No201 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm450,000$45,000$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2923.76194 Lbs6 ft12.69660,519$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
230122
3Alexandre Mallet20122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , ,
Gardien
#1 : , #2 : Samu Perhonen


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
1Admirals21100000121021010000035-21100000095420.500122335001291138288810321028109651862617508225.00%5180.00%01095265941.18%1203289641.54%635152741.58%151399924206491021439
2Baby Hawks21100000990110000005231010000047-320.50091625001291138284410321028109651882624456116.67%12283.33%01095265941.18%1203289641.54%635152741.58%151399924206491021439
3Bears404000001128-1720200000614-820200000514-900.00011193000129113828138103210281096511966314651516.67%7357.14%01095265941.18%1203289641.54%635152741.58%151399924206491021439
4Bruins321000001284110000006242110000066040.6671222340012911382813210321028109651791627661218.33%10370.00%01095265941.18%1203289641.54%635152741.58%151399924206491021439
5Cabaret Lady Mary Ann312000001218-621100000911-21010000037-420.333121931001291138281731032102810965113035376210110.00%9277.78%11095265941.18%1203289641.54%635152741.58%151399924206491021439
6Caroline4310000021174211000001011-122000000116560.750214263001291138281991032102810965117555368521419.05%13376.92%01095265941.18%1203289641.54%635152741.58%151399924206491021439
7Chiefs20100001512-71000000134-11010000028-610.2505914001291138285710321028109651110281850700.00%9277.78%01095265941.18%1203289641.54%635152741.58%151399924206491021439
8Chill20200000411-71010000005-51010000046-200.000471110129113828621032102810965168912441100.00%5180.00%01095265941.18%1203289641.54%635152741.58%151399924206491021439
9Comets202000001014-41010000067-11010000047-300.0001018280012911382874103210281096511023831438337.50%13561.54%01095265941.18%1203289641.54%635152741.58%151399924206491021439
10Cougars302000011418-41010000057-220100001911-210.16714274100129113828107103210281096511465620639444.44%10370.00%01095265941.18%1203289641.54%635152741.58%151399924206491021439
11Crunch31200000151411010000045-121100000119220.333152843001291138281521032102810965113034285219526.32%13561.54%01095265941.18%1203289641.54%635152741.58%151399924206491021439
12Heat2110000078-1110000006331010000015-420.50071421001291138287910321028109651892825427228.57%9366.67%01095265941.18%1203289641.54%635152741.58%151399924206491021439
13Jayhawks20200000510-51010000014-31010000046-200.00051015001291138287410321028109651892722397114.29%11372.73%01095265941.18%1203289641.54%635152741.58%151399924206491021439
14Las Vegas2020000069-31010000035-21010000034-100.00061117001291138288610321028109651852520361119.09%10190.00%01095265941.18%1203289641.54%635152741.58%151399924206491021439
15Manchots42200000171702110000069-321100000118340.5001733500012911382814210321028109651138384910312325.00%17664.71%01095265941.18%1203289641.54%635152741.58%151399924206491021439
16Marlies312000001214-21100000064220200000610-420.33312223400129113828981032102810965114748166212325.00%8275.00%01095265941.18%1203289641.54%635152741.58%151399924206491021439
17Minnesota20200000712-51010000024-21010000058-300.00071421001291138287910321028109651962514386233.33%7357.14%01095265941.18%1203289641.54%635152741.58%151399924206491021439
18Monarchs21100000910-1110000006421010000036-320.500916250012911382888103210281096511062439511000.00%9188.89%01095265941.18%1203289641.54%635152741.58%151399924206491021439
19Monsters404000001527-1220200000613-720200000914-500.0001527420012911382814110321028109651200474095900.00%15380.00%01095265941.18%1203289641.54%635152741.58%151399924206491021439
20Monsters20200000815-71010000046-21010000049-500.000816240012911382870103210281096519025143611327.27%7185.71%01095265941.18%1203289641.54%635152741.58%151399924206491021439
21Oceanics20200000612-61010000045-11010000027-500.00069150012911382860103210281096511053322486116.67%11372.73%01095265941.18%1203289641.54%635152741.58%151399924206491021439
22Oil Kings2110000079-2110000006241010000017-620.5007132000129113828791032102810965169201647400.00%8362.50%01095265941.18%1203289641.54%635152741.58%151399924206491021439
23Phantoms421000102118321000010121022110000098160.750213960001291138281291032102810965114747559210330.00%19478.95%11095265941.18%1203289641.54%635152741.58%151399924206491021439
24Rocket31100001810-22010000158-31100000032130.500816240012911382813810321028109651851918681218.33%9277.78%01095265941.18%1203289641.54%635152741.58%151399924206491021439
25Senators312000001416-2211000008801010000068-220.33314284200129113828104103210281096511272433569333.33%12283.33%01095265941.18%1203289641.54%635152741.58%151399924206491021439
26Sharks2100000112120110000005411000000178-130.7501224360012911382888103210281096511334218397342.86%90100.00%01095265941.18%1203289641.54%635152741.58%151399924206491021439
27Sound Tigers413000001518-321100000541202000001014-420.2501528432012911382812410321028109651126415610410220.00%21385.71%01095265941.18%1203289641.54%635152741.58%151399924206491021439
28Spiders403001001424-1020100100913-420200000511-610.125142741001291138281581032102810965119046268116425.00%13376.92%01095265941.18%1203289641.54%635152741.58%151399924206491021439
29Stars21000010972110000003211000001065141.00091625001291138287210321028109651602218549333.33%8187.50%01095265941.18%1203289641.54%635152741.58%151399924206491021439
30Thunder302000101014-4201000109901010000015-420.333101828001291138281421032102810965112233335914428.57%13469.23%01095265941.18%1203289641.54%635152741.58%151399924206491021439
Total82225200134327421-9441142200122163190-274183000012164231-67550.335327611938301291138283177103210281096513514100079817753086119.81%3227875.78%21095265941.18%1203289641.54%635152741.58%151399924206491021439
_Since Last GM Reset82225200134327421-9441142200122163190-274183000012164231-67550.335327611938301291138283177103210281096513514100079817753086119.81%3227875.78%21095265941.18%1203289641.54%635152741.58%151399924206491021439
_Vs Conference46123000121184239-55238120012091109-18234180000193130-37300.32618434252630129113828169410321028109651197053745710151613018.63%1743977.59%11095265941.18%1203289641.54%635152741.58%151399924206491021439
_Vs Division2831100110114149-351424001105474-201417000006075-1590.161114215329201291138281031103210281096511172337276625931718.28%1052576.19%11095265941.18%1203289641.54%635152741.58%151399924206491021439

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8255W1327611938317735141000798177530
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8222520134327421
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4114220122163190
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
418300012164231
Derniers 10 Matchs
WLOTWOTL SOWSOL
360001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3086119.81%3227875.78%2
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
10321028109651129113828
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
1095265941.18%1203289641.54%635152741.58%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
151399924206491021439


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 - 2018-10-046Chill5Wolf Pack0LSommaire du Match
4 - 2018-10-0619Wolf Pack6Crunch7LSommaire du Match
5 - 2018-10-0729Wolf Pack8Caroline4WSommaire du Match
9 - 2018-10-1149Sharks4Wolf Pack5WSommaire du Match
11 - 2018-10-1357Oil Kings2Wolf Pack6WSommaire du Match
14 - 2018-10-1679Monsters6Wolf Pack4LSommaire du Match
15 - 2018-10-1787Wolf Pack3Bears6LSommaire du Match
19 - 2018-10-21116Heat3Wolf Pack6WSommaire du Match
21 - 2018-10-23122Cabaret Lady Mary Ann7Wolf Pack4LSommaire du Match
23 - 2018-10-25139Wolf Pack4Baby Hawks7LSommaire du Match
26 - 2018-10-28159Wolf Pack3Monarchs6LSommaire du Match
28 - 2018-10-30177Wolf Pack7Sharks8LXXSommaire du Match
30 - 2018-11-01189Wolf Pack9Admirals5WSommaire du Match
33 - 2018-11-04208Crunch5Wolf Pack4LSommaire du Match
35 - 2018-11-06216Rocket5Wolf Pack4LXXSommaire du Match
38 - 2018-11-09238Wolf Pack4Cougars5LXXSommaire du Match
39 - 2018-11-10251Wolf Pack2Monsters5LSommaire du Match
41 - 2018-11-12260Comets7Wolf Pack6LSommaire du Match
44 - 2018-11-15277Wolf Pack5Sound Tigers7LSommaire du Match
46 - 2018-11-17297Cabaret Lady Mary Ann4Wolf Pack5WSommaire du Match
48 - 2018-11-19309Stars2Wolf Pack3WSommaire du Match
50 - 2018-11-21320Sound Tigers1Wolf Pack4WSommaire du Match
52 - 2018-11-23332Wolf Pack4Phantoms5LSommaire du Match
53 - 2018-11-24347Bears6Wolf Pack4LSommaire du Match
55 - 2018-11-26365Senators4Wolf Pack5WSommaire du Match
58 - 2018-11-29384Wolf Pack6Senators8LSommaire du Match
60 - 2018-12-01399Wolf Pack3Rocket2WSommaire du Match
61 - 2018-12-02408Oceanics5Wolf Pack4LSommaire du Match
67 - 2018-12-08450Wolf Pack3Cabaret Lady Mary Ann7LSommaire du Match
69 - 2018-12-10463Wolf Pack1Thunder5LSommaire du Match
73 - 2018-12-14488Jayhawks4Wolf Pack1LSommaire du Match
75 - 2018-12-16505Las Vegas5Wolf Pack3LSommaire du Match
77 - 2018-12-18519Admirals5Wolf Pack3LSommaire du Match
81 - 2018-12-22553Wolf Pack3Marlies5LSommaire du Match
82 - 2018-12-23562Phantoms5Wolf Pack6WXXSommaire du Match
86 - 2018-12-27568Monsters5Wolf Pack2LSommaire du Match
88 - 2018-12-29593Wolf Pack4Chill6LSommaire du Match
90 - 2018-12-31604Wolf Pack2Chiefs8LSommaire du Match
92 - 2019-01-02617Manchots2Wolf Pack4WSommaire du Match
94 - 2019-01-04633Wolf Pack4Monsters9LSommaire du Match
96 - 2019-01-06647Wolf Pack4Jayhawks6LSommaire du Match
98 - 2019-01-08666Wolf Pack3Las Vegas4LSommaire du Match
100 - 2019-01-10673Sound Tigers3Wolf Pack1LSommaire du Match
102 - 2019-01-12688Wolf Pack5Sound Tigers7LSommaire du Match
103 - 2019-01-13701Wolf Pack7Monsters9LSommaire du Match
105 - 2019-01-15712Caroline6Wolf Pack8WSommaire du Match
107 - 2019-01-17728Baby Hawks2Wolf Pack5WSommaire du Match
109 - 2019-01-19744Wolf Pack0Bruins2LSommaire du Match
119 - 2019-01-29774Phantoms5Wolf Pack6WSommaire du Match
121 - 2019-01-31779Wolf Pack3Spiders7LSommaire du Match
123 - 2019-02-02796Thunder3Wolf Pack2LSommaire du Match
125 - 2019-02-04806Monarchs4Wolf Pack6WSommaire du Match
127 - 2019-02-06822Bruins2Wolf Pack6WSommaire du Match
129 - 2019-02-08837Caroline5Wolf Pack2LSommaire du Match
131 - 2019-02-10859Marlies4Wolf Pack6WSommaire du Match
133 - 2019-02-12872Wolf Pack2Oceanics7LSommaire du Match
136 - 2019-02-15888Wolf Pack5Crunch2WSommaire du Match
138 - 2019-02-17904Wolf Pack3Manchots4LSommaire du Match
140 - 2019-02-19919Wolf Pack3Caroline2WSommaire du Match
142 - 2019-02-21932Minnesota4Wolf Pack2LSommaire du Match
144 - 2019-02-23946Spiders8Wolf Pack5LSommaire du Match
145 - 2019-02-24956Wolf Pack2Bears8LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
148 - 2019-02-27981Thunder6Wolf Pack7WXXSommaire du Match
150 - 2019-03-01994Rocket3Wolf Pack1LSommaire du Match
152 - 2019-03-031009Bears8Wolf Pack2LSommaire du Match
154 - 2019-03-051025Wolf Pack6Stars5WXXSommaire du Match
156 - 2019-03-071036Wolf Pack5Cougars6LSommaire du Match
158 - 2019-03-091054Spiders5Wolf Pack4LXSommaire du Match
160 - 2019-03-111071Wolf Pack1Oil Kings7LSommaire du Match
162 - 2019-03-131082Wolf Pack4Comets7LSommaire du Match
164 - 2019-03-151097Wolf Pack1Heat5LSommaire du Match
165 - 2019-03-161108Wolf Pack5Minnesota8LSommaire du Match
168 - 2019-03-191124Cougars7Wolf Pack5LSommaire du Match
172 - 2019-03-231155Wolf Pack3Marlies5LSommaire du Match
174 - 2019-03-251171Manchots7Wolf Pack2LSommaire du Match
176 - 2019-03-271186Wolf Pack6Bruins4WSommaire du Match
178 - 2019-03-291197Chiefs4Wolf Pack3LXXSommaire du Match
180 - 2019-03-311215Wolf Pack5Phantoms3WSommaire du Match
181 - 2019-04-011222Wolf Pack2Spiders4LSommaire du Match
183 - 2019-04-031239Senators4Wolf Pack3LSommaire du Match
185 - 2019-04-051254Monsters8Wolf Pack4LSommaire du Match
186 - 2019-04-061264Wolf Pack8Manchots4WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets4020
Assistance61,02230,835
Assistance PCT74.42%75.21%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2240 - 74.68% 74,575$3,057,580$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,963,015$ 1,915,506$ 1,906,006$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
9,887$ 1,932,353$ 28 1

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 10,243$ 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
201882225200134327421-9441142200122163190-274183000012164231-6755327611938301291138283177103210281096513514100079817753086119.81%3227875.78%21095265941.18%1203289641.54%635152741.58%151399924206491021439
Total Saison Régulière82225200134327421-9441142200122163190-274183000012164231-6755327611938301291138283177103210281096513514100079817753086119.81%3227875.78%21095265941.18%1203289641.54%635152741.58%151399924206491021439