Wolf Pack

GP: 43 | W: 24 | L: 15 | OTL: 4 | P: 52
GF: 126 | GA: 90 | PP%: 11.92% | PK%: 85.40%
DG: Steve Lechasseur | Morale : 57 | Moyenne d'Équipe : 61
Prochain matchs #659 vs Devils
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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
1Johan Larsson (A)XX100.008145776473778663796258776173675969650
2TJ Tynan (A)XX100.005436906461949263756659656273705668640
3Chris Terry (C)XX100.005437876469939163686162586378705568630
4Sonny MilanoXX100.005637926873707266526369587265638374630
5Corey TroppXX100.005745656272908561645960576178705173620
6Jimmy HayesX100.007636905792949356585555615678705449620
7Tyler GaudetXX100.006938855884898357635853595571665968610
8Jayce HawrylukXXX100.007442905972736958645657635865637768600
9Wade MeganX100.005637885976756759675958595677695168600
10Michael BuntingXX100.005439836072786859585960565867645868590
11Marko DanoXXX100.006145805875766857615856625469657769590
12Kole SherwoodXX100.007338865978796958545657555463625468590
13Keegan LoweX100.006339815679939054305752564871766268620
14Austin StrandX100.007238855787857956305653594663626371620
15Michael PaliottaX100.007239835488807453305351574671666336610
16Julius HonkaX100.005638876468755663306258665767648270610
17Kevin DavisX100.006344645470778053305552585573675264590
18Zachary LeslieX100.006344645272778052305351585573665326590
Rayé
1Colton HargroveX100.006837885680949555575354565573675820600
2Mitch CallahanX100.005936905972928858625756585775685720600
3Tye McGinnXX100.007339825587928854565254585477695620600
4Luke GazdicX100.007744685691777155585453595478705520590
5Joseph CramarossaXX100.005944675573918654585551545373675620580
6Ryan BourqueXX100.005038865566918754565352585475685320580
7Cameron HebigXXX100.005037885758928956615654505563626320570
8Cody BassXXX100.006345655475817553545251535280725320560
9Ty LewisX100.005138865657908455585554525361636420560
10Steve OleksyX100.005844695672837755305351594582735220600
11Vincent LoVerdeX100.006137885373939152305250534578705520600
12Ryan CulkinX100.005634805580767255305652564564655120580
MOYENNE D'ÉQUIPE100.00634081587584805752575558557267594660
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
1Alex Lyon100.00786866787776787776787773774253730
Rayé
MOYENNE D'ÉQUIPE100.0078686678777678777678777377425373
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Yeo75858080686380CAN4558,000,000$


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'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
1Johan LarssonWolf Pack (NYR)C/LW4315254019771511610816050979.38%2189920.9128102415402251692462.84%106300000.8913111233
2TJ TynanWolf Pack (NYR)C/RW43112637192203496123281068.94%1396622.492683416901131822255.65%82300000.7705000422
3Chris TerryWolf Pack (NYR)LW/RW4311152619601638100306811.00%177618.05033221580001190160.61%6600000.6705000120
4Sonny MilanoWolf Pack (NYR)LW/RW2816102615100232986286918.60%254219.38336261120001154058.33%4800010.9602000402
5Julius HonkaWolf Pack (NYR)D43817258215254173193410.96%5096122.376511521460001183100.00%000000.5200100022
6Corey TroppWolf Pack (NYR)LW/RW4312102293515453693215712.90%362114.452241498000001148.39%3100000.7101102212
7Austin StrandWolf Pack (NYR)D43115161841580313013213.33%4298422.89044161580001186000.00%000000.3300100001
8Wade MeganWolf Pack (NYR)C436915310012507114478.45%243610.16000532000080060.13%44900000.6900000200
9Tyler GaudetWolf Pack (NYR)C/LW43410141230038214913338.16%447311.01011517000051147.78%9000000.5900000011
10Marko DanoWolf Pack (NYR)C/LW/RW43851310195253663123412.70%552012.102135471014482160.00%7500000.5000001100
11Michael BuntingWolf Pack (NYR)LW/RW436612840132357193910.53%350211.68112896000002063.33%3000000.4800000111
12Jayce HawrylukWolf Pack (NYR)C/LW/RW434610524033265518247.27%251812.060003511281801047.77%15700000.3900000020
13Keegan LoweWolf Pack (NYR)D4328101638038182610127.69%2777217.961121784101165100.00%000000.2600000012
14Kevin DavisWolf Pack (NYR)D37191013621064202610193.85%1862716.961011272000020100.00%000000.3200110000
15Kole SherwoodWolf Pack (NYR)C/RW4364109140211639111715.38%22986.9300000000002141.67%6000000.6700000012
16Michael PaliottaWolf Pack (NYR)D210771730033135360.00%1335016.6800001000178000.00%000000.4000000001
17Jimmy HayesWolf Pack (NYR)RW29235380311118101811.11%22629.06000090000910061.54%2600000.3800000000
18Zachary LeslieWolf Pack (NYR)D172351121520682225.00%1327616.2800001000059000.00%000000.3600001000
19Mitch CallahanWolf Pack (NYR)RW9011200147140.00%19810.92000000000190055.17%2900000.2000000000
20Ryan CulkinWolf Pack (NYR)D6000-260121030.00%18514.230000000001000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne70611518930421447860669625109031271010.55%2251097515.552035552431368347261337201158.30%294700010.55116525171619
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
1Alex LyonWolf Pack (NYR)34201030.9041.90196006626450110.875163310221
Stats d'équipe Total ou en Moyenne34201030.9041.90196006626450110.875163310221


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 Cap 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
Alex LyonWolf Pack (NYR)G261992-12-09No201 Lbs6 ft1NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Austin StrandWolf Pack (NYR)D221997-02-17No216 Lbs6 ft3NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Cameron HebigWolf Pack (NYR)C/LW/RW221997-01-21No184 Lbs5 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Chris TerryWolf Pack (NYR)LW/RW301989-04-07No191 Lbs5 ft10NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Cody BassWolf Pack (NYR)C/LW/RW321987-01-07No205 Lbs6 ft0NoNoNo1Pro & Farm300,000$0$0$NoLien
Colton HargroveWolf Pack (NYR)LW271992-06-25No215 Lbs6 ft1NoNoNo1Pro & Farm300,000$0$0$NoLien
Corey TroppWolf Pack (NYR)LW/RW291989-07-25No186 Lbs6 ft0NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Jayce HawrylukWolf Pack (NYR)C/LW/RW231996-01-01No196 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Jimmy HayesWolf Pack (NYR)RW291989-11-21No215 Lbs6 ft5NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Johan LarssonWolf Pack (NYR)C/LW261992-07-25No202 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Joseph CramarossaWolf Pack (NYR)C/LW261992-10-26No192 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Julius HonkaWolf Pack (NYR)D231995-12-03No180 Lbs5 ft11NoNoNo1Pro & Farm900,000$0$0$NoLien
Keegan LoweWolf Pack (NYR)D261993-03-29No191 Lbs6 ft2NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Kevin DavisWolf Pack (NYR)D221997-03-14No172 Lbs5 ft11NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Kole SherwoodWolf Pack (NYR)C/RW221997-01-22No202 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Luke GazdicWolf Pack (NYR)LW291989-07-25No225 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$NoLien
Marko DanoWolf Pack (NYR)C/LW/RW241994-11-30No212 Lbs5 ft11NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Michael BuntingWolf Pack (NYR)LW/RW231995-09-17No197 Lbs5 ft11NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Michael PaliottaWolf Pack (NYR)D261993-04-06No207 Lbs6 ft4NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Mitch CallahanWolf Pack (NYR)RW271991-08-17No198 Lbs5 ft11NoNoNo1Pro & Farm300,000$0$0$NoLien
Ryan BourqueWolf Pack (NYR)C/LW281991-01-03No185 Lbs5 ft9NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Ryan CulkinWolf Pack (NYR)D251993-12-15No200 Lbs6 ft2NoNoNo1Pro & Farm300,000$0$0$NoLien
Sonny MilanoWolf Pack (NYR)LW/RW231996-05-12No195 Lbs6 ft0NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Steve OleksyWolf Pack (NYR)D331986-02-04No188 Lbs6 ft0NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
TJ TynanWolf Pack (NYR)C/RW271992-02-25No165 Lbs5 ft8NoNoNo1Pro & Farm500,000$0$0$NoLien
Ty LewisWolf Pack (NYR)RW211998-03-05No180 Lbs5 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Tye McGinnWolf Pack (NYR)LW/RW281990-07-29No218 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Tyler GaudetWolf Pack (NYR)C/LW261993-04-04No205 Lbs6 ft3NoNoNo1Pro & Farm300,000$0$0$NoLien
Vincent LoVerdeWolf Pack (NYR)D301989-04-14No205 Lbs5 ft11NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Wade MeganWolf Pack (NYR)C281990-07-22No191 Lbs6 ft1NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Zachary LeslieWolf Pack (NYR)D251994-01-31No195 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3126.06197 Lbs6 ft02.35383,871$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Sonny MilanoJohan LarssonTJ Tynan40023
2Corey TroppWade MeganChris Terry35122
3Tyler GaudetJayce HawrylukMarko Dano15122
4Michael BuntingKole SherwoodJimmy Hayes10032
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julius HonkaKevin Davis40122
2Keegan LoweAustin Strand35131
3Zachary LeslieMichael Paliotta24131
4Julius HonkaAustin Strand1113
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris TerryTJ TynanSonny Milano60005
2Johan LarssonWade MeganCorey Tropp40104
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julius HonkaAustin Strand60014
2Kevin DavisKeegan Lowe40014
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Johan LarssonJayce Hawryluk55041
2TJ TynanJimmy Hayes45041
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julius HonkaMichael Paliotta55140
2Austin StrandZachary Leslie45140
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Johan Larsson60050Julius HonkaMichael Paliotta60140
2TJ Tynan40050Zachary LeslieAustin Strand40140
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1TJ TynanSonny Milano55023
2Johan LarssonChris Terry45023
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julius HonkaKevin Davis60122
2Keegan LoweAustin Strand40131
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Sonny MilanoJohan LarssonTJ TynanJulius HonkaChris Terry
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
TJ TynanJohan LarssonJayce HawrylukJulius HonkaAustin Strand
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Chris Terry, Sonny Milano, Marko DanoChris Terry, Sonny MilanoSonny Milano
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Julius Honka, Austin Strand, Keegan LoweKeegan LoweJulius Honka, Austin Strand
Tirs de Pénalité
TJ Tynan, Chris Terry, Sonny Milano, Johan Larsson, Corey Tropp
Gardien
#1 : Alex Lyon, #2 :


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
1Americans3010001169-3100000103212010000137-430.500610160047334249038836843835691333451715.88%13376.92%0826141358.46%686119357.50%36660460.60%1163830923304525274
2Bears22000000642000000000002200000064241.000611170047334245338836843835471827378225.00%90100.00%0826141358.46%686119357.50%36660460.60%1163830923304525274
3Bruins834000012125-441300000715-8421000011410470.43821385901473342418338836843835183591091603139.68%501080.00%1826141358.46%686119357.50%36660460.60%1163830923304525274
4Checkers44000000323292200000016214220000001611581.000325486024733424202388368438357319438018316.67%170100.00%1826141358.46%686119357.50%36660460.60%1163830923304525274
5Comets2010100045-1100010002111010000024-220.50047111047334245238836843835471022341500.00%11372.73%0826141358.46%686119357.50%36660460.60%1163830923304525274
6Devils1000000112-1000000000001000000112-110.5001230047334242238836843835191813700.00%4175.00%0826141358.46%686119357.50%36660460.60%1163830923304525274
7Marlies11000000826000000000001100000082621.00081422004733424553883684383592622400.00%20100.00%0826141358.46%686119357.50%36660460.60%1163830923304525274
8Penguins32100000633110000002022110000043140.6676111702473342471388368438354818385320315.00%140100.00%0826141358.46%686119357.50%36660460.60%1163830923304525274
9Phantoms3110010067-13110010067-10000000000030.5006121801473342481388368438355923494916318.75%15473.33%0826141358.46%686119357.50%36660460.60%1163830923304525274
10Rocket21100000651110000004221010000023-120.500610160047334243638836843835431433358112.50%14564.29%0826141358.46%686119357.50%36660460.60%1163830923304525274
11Senators11000000413000000000001100000041321.0004610004733424253883684383519112124250.00%60100.00%0826141358.46%686119357.50%36660460.60%1163830923304525274
12Sound Tigers834010001314-1412010006604220000078-180.50013243711473342419938836843835152509514625312.00%38392.11%1826141358.46%686119357.50%36660460.60%1163830923304525274
13Thunderbirds52200010131034210001012841010000012-160.6001321340047334241403883684383510536689120210.00%33487.88%0826141358.46%686119357.50%36660460.60%1163830923304525274
Total4320150212312690362197021205843152211800003684721520.6051262203462747334241209388368438358732645437771932311.92%2263385.40%3826141358.46%686119357.50%36660460.60%1163830923304525274
_Since Last GM Reset4320150212312690362197021205843152211800003684721520.6051262203462747334241209388368438358732645437771932311.92%2263385.40%3826141358.46%686119357.50%36660460.60%1163830923304525274
_Vs Conference26121001102575611246011002128-714840000236288290.55857104161154733424634388368438355271703384701111614.41%1361886.76%2826141358.46%686119357.50%36660460.60%1163830923304525274
_Vs Division204501101585261023011002627-110220000132257120.30058991570147334245293883684383542812526136584910.71%1182281.36%1826141358.46%686119357.50%36660460.60%1163830923304525274

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4352W2126220346120987326454377727
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
432015212312690
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
219721205843
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2211800036847
Derniers 10 Matchs
WLOTWOTL SOWSOL
430111
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1932311.92%2263385.40%3
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
388368438354733424
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
826141358.46%686119357.50%36660460.60%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1163830923304525274


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
3 - 2019-09-044Bruins4Wolf Pack1LSommaire du Match
5 - 2019-09-0624Rocket2Wolf Pack4WSommaire du Match
8 - 2019-09-0929Wolf Pack1Devils2LXXSommaire du Match
10 - 2019-09-1136Bruins1Wolf Pack2WSommaire du Match
11 - 2019-09-1251Wolf Pack3Bruins4LSommaire du Match
15 - 2019-09-1667Wolf Pack2Rocket3LSommaire du Match
17 - 2019-09-1871Wolf Pack4Senators1WSommaire du Match
18 - 2019-09-1983Wolf Pack8Marlies2WSommaire du Match
22 - 2019-09-23103Phantoms0Wolf Pack1WSommaire du Match
25 - 2019-09-26126Sound Tigers2Wolf Pack0LSommaire du Match
26 - 2019-09-27132Wolf Pack1Thunderbirds2LSommaire du Match
31 - 2019-10-02143Wolf Pack1Penguins3LSommaire du Match
32 - 2019-10-03161Wolf Pack3Penguins0WSommaire du Match
33 - 2019-10-04168Wolf Pack3Bears2WSommaire du Match
38 - 2019-10-09181Wolf Pack2Comets4LSommaire du Match
39 - 2019-10-10193Penguins0Wolf Pack2WSommaire du Match
43 - 2019-10-14215Sound Tigers1Wolf Pack2WXSommaire du Match
46 - 2019-10-17237Comets1Wolf Pack2WXSommaire du Match
47 - 2019-10-18249Americans2Wolf Pack3WXXSommaire du Match
50 - 2019-10-21257Bruins4Wolf Pack2LSommaire du Match
52 - 2019-10-23264Wolf Pack1Sound Tigers3LSommaire du Match
53 - 2019-10-24285Sound Tigers1Wolf Pack3WSommaire du Match
60 - 2019-10-31321Checkers2Wolf Pack7WSommaire du Match
64 - 2019-11-04340Wolf Pack2Sound Tigers0WSommaire du Match
66 - 2019-11-06355Checkers0Wolf Pack9WSommaire du Match
67 - 2019-11-07364Wolf Pack3Bears2WSommaire du Match
72 - 2019-11-12390Wolf Pack8Checkers0WSommaire du Match
74 - 2019-11-14402Wolf Pack8Checkers1WSommaire du Match
78 - 2019-11-18424Bruins6Wolf Pack2LSommaire du Match
80 - 2019-11-20437Wolf Pack2Americans3LXXSommaire du Match
81 - 2019-11-21453Wolf Pack1Americans4LSommaire du Match
86 - 2019-11-26471Wolf Pack3Sound Tigers2WSommaire du Match
88 - 2019-11-28487Sound Tigers2Wolf Pack1LSommaire du Match
89 - 2019-11-29499Thunderbirds2Wolf Pack3WSommaire du Match
94 - 2019-12-04523Thunderbirds3Wolf Pack4WXXSommaire du Match
95 - 2019-12-05533Phantoms4Wolf Pack3LSommaire du Match
96 - 2019-12-06546Wolf Pack3Bruins1WSommaire du Match
101 - 2019-12-11565Wolf Pack4Bruins5LXXSommaire du Match
102 - 2019-12-12576Wolf Pack1Sound Tigers3LSommaire du Match
108 - 2019-12-18609Phantoms3Wolf Pack2LXSommaire du Match
109 - 2019-12-19619Thunderbirds2Wolf Pack1LSommaire du Match
110 - 2019-12-20634Wolf Pack4Bruins0WSommaire du Match
113 - 2019-12-23646Thunderbirds1Wolf Pack4WSommaire du Match
115 - 2019-12-25659Wolf Pack-Devils-
116 - 2019-12-26670Checkers-Wolf Pack-
122 - 2020-01-01687Wolf Pack-Thunderbirds-
123 - 2020-01-02701Americans-Wolf Pack-
126 - 2020-01-05712Sound Tigers-Wolf Pack-
129 - 2020-01-08726Crunch-Wolf Pack-
130 - 2020-01-09745Wolf Pack-Phantoms-
131 - 2020-01-10751Wolf Pack-Phantoms-
134 - 2020-01-13763Marlies-Wolf Pack-
137 - 2020-01-16780Wolf Pack-Sound Tigers-
138 - 2020-01-17793Penguins-Wolf Pack-
143 - 2020-01-22824Thunderbirds-Wolf Pack-
144 - 2020-01-23830Bruins-Wolf Pack-
145 - 2020-01-24842Wolf Pack-Bruins-
148 - 2020-01-27851Bears-Wolf Pack-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29862Wolf Pack-Thunderbirds-
151 - 2020-01-30876Penguins-Wolf Pack-
157 - 2020-02-05903Wolf Pack-Penguins-
158 - 2020-02-06914Wolf Pack-Thunderbirds-
159 - 2020-02-07923Bears-Wolf Pack-
162 - 2020-02-10936Devils-Wolf Pack-
164 - 2020-02-12943Wolf Pack-Crunch-
165 - 2020-02-13957Wolf Pack-Comets-
172 - 2020-02-20995Wolf Pack-Checkers-
173 - 2020-02-211008Wolf Pack-Checkers-
178 - 2020-02-261033Checkers-Wolf Pack-
179 - 2020-02-271042Senators-Wolf Pack-
183 - 2020-03-021065Wolf Pack-Thunderbirds-
186 - 2020-03-051088Comets-Wolf Pack-
187 - 2020-03-061098Devils-Wolf Pack-
192 - 2020-03-111122Bears-Wolf Pack-
193 - 2020-03-121133Wolf Pack-Phantoms-
194 - 2020-03-131146Wolf Pack-Bears-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
17 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
4,778,385$ 119,000$ 37,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 77,342$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 80 41,851$ 3,348,080$




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
144320150212312690362197021205843152211800003684721521262203462747334241209388368438358732645437771932311.92%2263385.40%3826141358.46%686119357.50%36660460.60%1163830923304525274
Total Saison Régulière4320150212312690362197021205843152211800003684721521262203462747334241209388368438358732645437771932311.92%2263385.40%3826141358.46%686119357.50%36660460.60%1163830923304525274