Wilkes-Barre

GP: 8 | W: 7 | L: 1 | OTL: 0 | P: 14
GF: 35 | GA: 23 | PP%: 15.00% | PK%: 87.80%
DG: Ghyslain Rousseau | Morale : 58 | Moyenne d'Équipe : 66
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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
1Brendan GallagherXX100.007152738266667477376572644579830607003216,500,000$
2Teddy BluegerXX100.007954867569688365907659822567690607003022,200,000$
3Sam LaffertyXXX100.00894687807661926557627066256566060690291750,000$
4Radek FaksaXX100.007845918182639565846359843773750606903032,500,001$
5Drew O'ConnorX100.006943917677709065416772782558590606902632,100,009$
6Nico SturmXX100.007744938177688664986158822565670616802932,000,000$
7Barclay GoodrowXX100.008678737781639865866057852575800626803113,641,667$
8Andrew CoglianoX100.006541928662579465436358807294950606803713,299,001$
9Denis Guryanov (R)XX100.00807690657665647150666874656668051680273987,087$
10Vinnie HinostrozaXX100.007142908161546375386258737566660606703011,050,000$
11Matt NietoX100.006742937967596965256257832577810606603221,900,009$
12Boris KatchoukX100.007943937266597964406062757561610606602631,200,009$
13Vladislav GavrikovX100.006943888079819263255649862567680627002832,800,000$
14Jan RuttaX100.007544847776788063255449922567700627003422,100,009$
15Chad RuhwedelX100.00824497826960676225454786366768062680342800,000$
16Marc StaalX100.007344877778637662254948772588900566703722,000,000$
17Marco ScandellaX100.007654927979596162254848762577800606603413,275,000$
18John LudvigX100.008799627377586362254550802547470516502432,100,001$
Rayé
1Andrew AgozzinoXX100.00716682636681856680636367605959058650332650,000$
2Eric RobinsonX100.00855787757459816544625768256666045650293667,007$
3Riley NashXX100.00717073797068706379596362604446042650351775,000$
4Shane BowersX100.00716293666266695468455960564444042580252750,000$
5Sebastian AhoDX100.00694292736369826625504872256263058650272725,000$
6Jack St. IvanyX100.008644956863628163254647852545450486502532,100,001$
7Ryan JohnsonX100.00594090766263706125524767254747042620233925,000$
8Mark FriedmanX100.00797475736959586125434768255556042620281999,000$
9Lucas JohansenX100.00746691696655565425514262404545042590261750,000$
MOYENNE D'ÉQUIPE100.0075548776716477644657567538646505566
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
1Filip Gustavsson100.0064727073656271656564815758060660
2Scott Wedgewood100.0063575871675869626562596162053620
Rayé
MOYENNE D'ÉQUIPE100.006465647266607064656370596005764
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jacques Martin67717063999539CAN7021,000,000$


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
1Teddy BluegerWilkes-Barre (Pit)C/LW8481296061022101418.18%213216.56022834000001063.92%19400001.8100000201
2Sam LaffertyWilkes-Barre (Pit)C/LW/RW845981601792521716.00%013016.33022734000001052.17%6900001.3800000111
3Brendan GallagherWilkes-Barre (Pit)LW/RW85381208103192616.13%013016.27202933000001041.67%1200001.2300000020
4Jan RuttaWilkes-Barre (Pit)D72687201371851011.11%1016123.031121331000028000.00%000000.9900000101
5Barclay GoodrowWilkes-Barre (Pit)C/LW725710602116234128.70%212718.160118250001151072.88%5900001.1000000020
6Drew O'ConnorWilkes-Barre (Pit)LW8347400442691811.54%112916.22033828000000054.55%1100001.0800000110
7Vladislav GavrikovWilkes-Barre (Pit)D7156600109224104.55%416423.441121633000029100.00%000000.7300000010
8Radek FaksaWilkes-Barre (Pit)C/LW82354209271941110.53%312816.11000000002390063.47%16700000.7800000001
9Matt NietoWilkes-Barre (Pit)RW8224000212114518.18%110613.27000020000410037.50%800100.7500000000
10Andrew CoglianoWilkes-Barre (Pit)LW8044-22061283120.00%310212.85000010001180046.15%1300000.7800000000
11Boris KatchoukWilkes-Barre (Pit)LW81341208714387.14%0698.7400000000030157.14%700001.1400000000
12Sebastian AhoDWilkes-Barre (Pit)D7033-1801174440.00%912618.07000210000011000.00%000000.4700000000
13Chad RuhwedelWilkes-Barre (Pit)D712346017411459.09%714721.11000625000022000.00%000000.4100000001
14Vinnie HinostrozaWilkes-Barre (Pit)LW/RW8213-220781531313.33%010513.20011626000001025.00%800000.5700000100
15Nico SturmWilkes-Barre (Pit)C/LW8123-175101268516.67%410813.57000050000250070.59%10200000.5500001000
16Marc StaalWilkes-Barre (Pit)D8123517516812478.33%614418.12101523000019010.00%000000.4100000001
17Andrew AgozzinoWilkes-Barre (Pit)C/LW7112-1207683312.50%0588.3200001000001056.52%6900000.6900000000
18Marco ScandellaWilkes-Barre (Pit)D8112412013772314.29%1113917.4300024000114000.00%000000.2900000100
19John LudvigWilkes-Barre (Pit)D2101-1406220050.00%23618.1910110000010000.00%000000.5500000000
20Jack St. IvanyWilkes-Barre (Pit)D1101-12011101100.00%12121.130000000006000.00%000000.9500000000
21Denis GuryanovWilkes-Barre (Pit)LW/RW2011120212100.00%03015.23000030000000100.00%100000.6600000000
22Ryan JohnsonWilkes-Barre (Pit)D1000-100200000.00%11616.980000200002000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne14435619654100101961792878618412.20%67231916.11611179132700052927262.08%72000100.8300001776
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
1Filip GustavssonWilkes-Barre (Pit)44000.9032.5024000101030000.000044000
2Scott WedgewoodWilkes-Barre (Pit)43100.8853.2524020131130000.000044000
Stats d'équipe Total ou en Moyenne87100.8942.8848020232160000.000088000


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
Andrew AgozzinoWilkes-Barre (Pit)C/LW331991-01-02No187 Lbs5 ft10NoNoNo2Pro & Farm650,000$650,000$0$0$No650,000$Lien / Lien NHL
Andrew CoglianoWilkes-Barre (Pit)LW371987-06-13No174 Lbs5 ft10NoNoNo1Pro & Farm3,299,001$3,299,001$0$0$NoLien / Lien NHL
Barclay GoodrowWilkes-Barre (Pit)C/LW311993-02-25No216 Lbs6 ft2NoNoNo1Pro & Farm3,641,667$3,641,667$0$0$NoLien / Lien NHL
Boris KatchoukWilkes-Barre (Pit)LW261998-06-17No178 Lbs6 ft1NoNoNo3Pro & Farm1,200,009$1,200,009$0$0$No1,200,009$1,200,009$Lien / Lien NHL
Brendan GallagherWilkes-Barre (Pit)LW/RW321992-05-06No185 Lbs5 ft9NoNoNo1Pro & Farm6,500,000$6,500,000$0$0$NoLien / Lien NHL
Chad RuhwedelWilkes-Barre (Pit)D341990-05-06No191 Lbs5 ft11NoNoNo2Pro & Farm800,000$800,000$0$0$No800,000$Lien / Lien NHL
Denis GuryanovWilkes-Barre (Pit)LW/RW271997-06-07Yes200 Lbs6 ft3NoNoNo3Pro & Farm987,087$987,087$0$0$No987,087$987,087$Lien
Drew O'ConnorWilkes-Barre (Pit)LW261998-06-09No205 Lbs6 ft3NoNoNo3Pro & Farm2,100,009$2,100,009$0$0$No2,100,009$2,100,009$Lien
Eric RobinsonWilkes-Barre (Pit)LW291995-06-14No196 Lbs6 ft2NoNoNo3Pro & Farm667,007$667,007$0$0$No667,007$667,007$Lien / Lien NHL
Filip GustavssonWilkes-Barre (Pit)G261998-06-07No185 Lbs6 ft2NoNoNo1Pro & Farm3,750,000$3,750,000$0$0$NoLien / Lien NHL
Jack St. IvanyWilkes-Barre (Pit)D251999-07-22No169 Lbs6 ft1NoNoNo3Pro & Farm2,100,001$2,100,001$0$0$No2,100,001$2,100,001$Lien
Jan RuttaWilkes-Barre (Pit)D341990-07-29No205 Lbs6 ft2NoNoNo2Pro & Farm2,100,009$2,100,009$0$0$No2,100,009$Lien / Lien NHL
John LudvigWilkes-Barre (Pit)D242000-02-08No200 Lbs6 ft1NoNoNo3Pro & Farm2,100,001$2,100,001$0$0$No2,100,001$2,100,001$Lien
Lucas JohansenWilkes-Barre (Pit)D261997-11-16No176 Lbs6 ft1NoNoNo1Pro & Farm750,000$750,000$0$0$NoLien
Marc StaalWilkes-Barre (Pit)D371987-01-12No209 Lbs6 ft4NoNoNo2Pro & Farm2,000,000$2,000,000$0$0$No2,000,000$Lien / Lien NHL
Marco ScandellaWilkes-Barre (Pit)D341990-02-22No211 Lbs6 ft3NoNoNo1Pro & Farm3,275,000$3,275,000$0$0$NoLien / Lien NHL
Mark FriedmanWilkes-Barre (Pit)D281995-12-25No185 Lbs5 ft11NoNoNo1Pro & Farm999,000$999,000$0$0$NoLien / Lien NHL
Matt NietoWilkes-Barre (Pit)RW321992-05-11No185 Lbs5 ft11NoNoNo2Pro & Farm1,900,009$1,900,009$0$0$No1,900,009$Lien
Nico SturmWilkes-Barre (Pit)C/LW291995-05-02No207 Lbs6 ft3NoNoNo3Pro & Farm2,000,000$2,000,000$0$0$No2,000,000$2,000,000$Lien / Lien NHL
Radek FaksaWilkes-Barre (Pit)C/LW301994-01-09No220 Lbs6 ft3NoNoNo3Pro & Farm2,500,001$2,500,001$0$0$No2,500,001$2,500,001$Lien / Lien NHL
Riley NashWilkes-Barre (Pit)C/RW351989-05-09No185 Lbs6 ft2NoNoNo1Pro & Farm775,000$775,000$0$0$NoLien
Ryan JohnsonWilkes-Barre (Pit)D232001-07-24No169 Lbs6 ft0NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$Lien
Sam LaffertyWilkes-Barre (Pit)C/LW/RW291995-03-06No205 Lbs6 ft2NoNoNo1Pro & Farm750,000$750,000$0$0$NoLien / Lien NHL
Scott WedgewoodWilkes-Barre (Pit)G321992-08-13No194 Lbs6 ft0NoNoNo1Pro & Farm825,000$825,000$0$0$NoLien / Lien NHL
Sebastian AhoDWilkes-Barre (Pit)D271997-02-17No176 Lbs6 ft0NoNoNo2Pro & Farm725,000$725,000$0$0$No725,000$Lien
Shane BowersWilkes-Barre (Pit)C251999-07-30No169 Lbs6 ft0NoNoNo2Pro & Farm750,000$750,000$0$0$No750,000$Lien
Teddy BluegerWilkes-Barre (Pit)C/LW301994-08-14No185 Lbs6 ft0NoNoNo2Pro & Farm2,200,000$2,200,000$0$0$No2,200,000$Lien / Lien NHL
Vinnie HinostrozaWilkes-Barre (Pit)LW/RW301994-04-03No172 Lbs5 ft9NoNoNo1Pro & Farm1,050,000$1,050,000$0$0$NoLien / Lien NHL
Vladislav GavrikovWilkes-Barre (Pit)D281995-11-21No213 Lbs6 ft3NoNoNo3Pro & Farm2,800,000$2,800,000$0$0$No2,800,000$2,800,000$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2929.62191 Lbs6 ft11.971,866,166$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Barclay GoodrowTeddy BluegerDrew O'Connor30122
2Denis GuryanovSam LaffertyBrendan Gallagher30122
3Andrew CoglianoNico SturmVinnie Hinostroza24122
4Boris KatchoukRadek FaksaMatt Nieto16122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Vladislav GavrikovChad Ruhwedel34122
2Marc StaalJan Rutta32122
3Marco ScandellaJohn Ludvig32122
4Marc StaalJan Rutta2122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Sam LaffertyTeddy BluegerBrendan Gallagher60122
2Drew O'ConnorBarclay GoodrowDenis Guryanov40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Vladislav GavrikovJan Rutta60122
2Chad RuhwedelMarc Staal40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Radek FaksaMatt Nieto60122
2Barclay GoodrowNico Sturm40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Vladislav GavrikovChad Ruhwedel60122
2Jan RuttaJohn Ludvig40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Radek Faksa60122Vladislav GavrikovChad Ruhwedel60122
2Barclay Goodrow40122Jan RuttaJohn Ludvig40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Radek FaksaDrew O'Connor60122
2Sam LaffertyBarclay Goodrow40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Vladislav GavrikovJan Rutta60122
2Chad RuhwedelMarc Staal40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Sam LaffertyTeddy BluegerBrendan GallagherVladislav GavrikovJan Rutta
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Radek FaksaNico SturmMatt NietoVladislav GavrikovJan Rutta
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Andrew Cogliano, Nico Sturm, Boris KatchoukVinnie Hinostroza, Matt NietoAndrew Cogliano
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Marco Scandella, John Ludvig, Chad RuhwedelMarco ScandellaMarco Scandella, Jan Rutta
Tirs de Pénalité
Boris Katchouk, Andrew Cogliano, Vinnie Hinostroza, Denis Guryanov, Brendan Gallagher
Gardien
#1 : Filip Gustavsson, #2 : Scott Wedgewood


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
1 Drag 2110000068-2110000004311010000025-320.500681400141011066751139906416265910220.00%12283.33%020931666.14%15826759.18%8013758.39%2061401716110253
2Checkers22000000945110000004131100000053241.00091625001410110477511399056182253700.00%100100.00%020931666.14%15826759.18%8013758.39%2061401716110253
3Hurricanes 220000001073110000004311100000064241.00010172700141011083751139904918324210110.00%8275.00%020931666.14%15826759.18%8013758.39%2061401716110253
4IceHogs220000001046110000005231100000052341.00010203000141011091751139904715224213323.08%11190.91%020931666.14%15826759.18%8013758.39%2061401716110253
Total871000003523124400000017984310000018144140.875356196001410110287751139902166710219640615.00%41587.80%020931666.14%15826759.18%8013758.39%2061401716110253
_Since Last GM Reset871000003523124400000017984310000018144140.875356196001410110287751139902166710219640615.00%41587.80%020931666.14%15826759.18%8013758.39%2061401716110253
_Vs Conference871000003523124400000017984310000018144140.875356196001410110287751139902166710219640615.00%41587.80%020931666.14%15826759.18%8013758.39%2061401716110253
_Vs Division871000003523124400000017984310000018144140.875356196001410110287751139902166710219640615.00%41587.80%020931666.14%15826759.18%8013758.39%2061401716110253

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
814L13561962872166710219600
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
87100003523
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4400000179
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
43100001814
Derniers 10 Matchs
WLOTWOTL SOWSOL
710000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
40615.00%41587.80%0
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
751139901410110
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
20931666.14%15826759.18%8013758.39%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2061401716110253


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 - 2024-09-185Hurricanes 3Wilkes-Barre4WSommaire du Match
3 - 2024-09-1910Wilkes-Barre5IceHogs2WSommaire du Match
5 - 2024-09-2128Checkers1Wilkes-Barre4WSommaire du Match
8 - 2024-09-2443 Drag 3Wilkes-Barre4WSommaire du Match
9 - 2024-09-2552Wilkes-Barre6Hurricanes 4WSommaire du Match
11 - 2024-09-2763IceHogs2Wilkes-Barre5WSommaire du Match
12 - 2024-09-2867Wilkes-Barre5Checkers3WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
13 - 2024-09-2969Wilkes-Barre2 Drag 5LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets2613
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
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 5,411,881$ 3,933,963$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 1 0$ 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
Séries
20212515100000093771613850000049409127500000443773093171264013828252955344284306217622252295731422719.01%951881.05%1560106752.48%45585153.47%23042254.50%685469544192339179
Total Séries2515100000093771613850000049409127500000443773093171264013828252955344284306217622252295731422719.01%951881.05%1560106752.48%45585153.47%23042254.50%685469544192339179