Thème
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Connexion

Texas
GP: 16 | W: 9 | L: 6 | OTL: 1 | P: 19
GF: 53 | GA: 47 | PP%: 23.88% | PK%: 76.39%
DG: Ben Dicaire | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #219 vs Iowa

Centre de jeu
Wilkes-Barre/Scranton
11-3-2, 24pts
3
4 Texas
9-6-1, 19pts
Team Stats
W1SéquenceL1
7-1-0Fiche domicile4-3-1
4-2-2Fiche domicile5-3-0
8-1-1Derniers 10 matchs6-3-1
3.38Buts par match 3.31
2.81Buts contre par match 2.94
26.79%Pourcentage en avantage numérique23.88%
89.39%Pourcentage en désavantage numérique76.39%
Texas
9-6-1, 19pts
3
4 Bridgeport
11-4-1, 23pts
Team Stats
L1SéquenceW2
4-3-1Fiche domicile6-2-0
5-3-0Fiche domicile5-2-1
6-3-1Derniers 10 matchs7-2-1
3.31Buts par match 4.19
2.94Buts contre par match 3.00
23.88%Pourcentage en avantage numérique21.21%
76.39%Pourcentage en désavantage numérique76.27%
Iowa
5-7-4, 14pts
Jour 34
Texas
9-6-1, 19pts
Statistiques d’équipe
L1SéquenceL1
4-3-1Fiche domicile4-3-1
1-4-3Fiche visiteur5-3-0
4-4-210 derniers matchs6-3-1
2.06Buts par match 3.31
2.88Buts contre par match 3.31
20.69%Pourcentage en avantage numérique23.88%
76.81%Pourcentage en désavantage numérique76.39%
Texas
9-6-1, 19pts
Jour 35
Wilkes-Barre/Scranton
11-3-2, 24pts
Statistiques d’équipe
L1SéquenceW1
4-3-1Fiche domicile7-1-0
5-3-0Fiche visiteur4-2-2
6-3-110 derniers matchs8-1-1
3.31Buts par match 3.38
2.94Buts contre par match 3.38
23.88%Pourcentage en avantage numérique26.79%
76.39%Pourcentage en désavantage numérique89.39%
Texas
9-6-1, 19pts
Jour 37
Rochester
7-9-0, 14pts
Statistiques d’équipe
L1SéquenceL1
4-3-1Fiche domicile6-2-0
5-3-0Fiche visiteur1-7-0
6-3-110 derniers matchs3-7-0
3.31Buts par match 2.44
2.94Buts contre par match 2.44
23.88%Pourcentage en avantage numérique20.29%
76.39%Pourcentage en désavantage numérique83.08%
Meneurs d'équipe
Buts
Benoit-Olivier Groulx
7
Passes
Kyle Rau
8
Points
Benoit-Olivier Groulx
14
Plus/Moins
Alex Goligoski
10
Joel HoferVictoires
Joel Hofer
7
Joel HoferPourcentage d’arrêts
Joel Hofer
0.931

Statistiques d’équipe
Buts pour
53
3.31 GFG
Tirs pour
552
34.50 Avg
Pourcentage en avantage numérique
23.9%
16 GF
Début de zone offensive
39.6%
Buts contre
47
2.94 GAA
Tirs contre
558
34.88 Avg
Pourcentage en désavantage numérique
76.4%%
17 GA
Début de la zone défensive
43.3%
Informations de l'équipe

Directeur généralBen Dicaire
EntraîneurJoel Bouchard
DivisionCentrale
ConférenceConference ouest
CapitaineBrian Gibbons
Assistant #1Marc-Andre Cliche
Assistant #2Riley Nash


Informations de l’aréna

Capacité3,000
Assistance2,145
Billets de saison300


Informations de la formation

Équipe Pro21
Équipe Mineure20
Limite Contrat41 / 50
Espoirs29


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
1Riley Nash (A)XXX100.006424945081708965916568708577702550003611,210,000$
2Brian Gibbons (C)XXX100.006626935568687866796668748684771550003711,210,000$
3Rick NashXX100.007846663571569364776163777899981250004111,250,000$
4Scott WilsonXX100.00733679668269876670656556766254375000332500,000$
5Marc-Andre Cliche (A)XX100.006629974666507966596466717982771750003811,100,000$
6Ryan WhiteXX100.00763457487959886695656559697976245000371500,000$
7Matt MartinXX100.00784681558363936150636360576358175000362550,000$
8Benoit-Olivier Groulx (R)XX100.00822990838881997185707268804845595000252800,000$
9Kyle RauXXX100.00662988766673827564717558746253305000321950,000$
10Conor ShearyXX98.006835947271779969707070747775743250003321,600,000$
11Cole SmithX100.00845185728774866169646472745959465000291850,000$
12Austin WatsonXX100.00787967708868935969606469747271355000333650,000$
13Cole Schwindt (R)XX99.00773695798077947086736873744444625000241600,000$
14Radim SimekX99.007634716881748251504852897570663550003231,050,000$
15Oscar FantenbergX100.006730806482758550505347887370703550003311,281,000$
16Alex GoligoskiX99.005735904175568456504753897799971350003911,200,000$
17Dylan McIlrathX100.00865137598972734450444882706468355000331500,000$
18Dennis CholowskiX98.00743089698476995350535492725454655000271750,000$
Rayé
MOYENNE D’ÉQUIPE99.6173388162796988626761637375706733500
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 SPÂgeContratSalaire
1Darcy Kuemper99.0063858583788686868781767978465000351981,000$
2Joel Hofer (R)100.00679983867684838585798849497750002431,400,000$
Rayé
1Matt Keetley100.0054808283748888878768749290850004011,100,000$
MOYENNE D’ÉQUIPE99.676188838476868686867679737244500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Joel Bouchard79827281999960CAN5221,000,000$


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
1Benoit-Olivier GroulxTexas (DAL)C/LW167714360332357184012.28%230819.311561153000042054.70%11700000.9100000121
2Niklas HjalmarssonDallasD153912834032141882016.67%2132321.59123646000036000%000000.7400000110
3Nic DowdDallasC/RW148412220102648214716.67%227519.6832512470001401058.40%39900010.8700000201
4Kyle RauTexas (DAL)C/LW/RW1438112401411456376.67%027119.39145947000030038.26%23000000.8100000000
5Conor ShearyTexas (DAL)LW/RW1628101607214924404.08%529218.290339370000351040.74%5400000.6801000001
6Riley NashTexas (DAL)C/LW/RW166396206194171514.63%224315.201012150001100154.00%5000000.7401000120
7Ian ColeDallasD1527901401813225169.09%2034022.692021153000043100%000000.5300000001
8Austin WatsonTexas (DAL)LW/RW10459419510420101520.00%212912.90101210000030152.94%1700001.4000010101
9Radim SimekTexas (DAL)D16358023525142161014.29%1729018.18022320000038200%000000.5500000100
10Alex GoligoskiTexas (DAL)D1634710551201891716.67%3534621.68336748000050100%000000.4000100011
11Cole SchwindtTexas (DAL)C/RW1025719513143112206.45%320620.682247270001200050.84%17900000.6800010000
12Brian GibbonsTexas (DAL)C/LW/RW161565409223713312.70%428417.8000010410000350050.68%14800000.4200000001
13Cole SmithTexas (DAL)LW15156-16023143114263.23%225116.7902210330000180037.50%3200000.4800000010
14Rick NashTexas (DAL)LW/RW16235-11351371851311.11%316110.10000020003490044.44%1800000.6201001001
15Ryan WhiteTexas (DAL)C/RW1623541001417296106.90%11569.8100000000000058.29%18700000.6400000000
16Dennis CholowskiTexas (DAL)D12235060720231078.70%3227723.121121036000039010%000000.3600000000
17Marc-Andre ClicheTexas (DAL)C/RW16033-22011213550%01096.8600000000000050.45%11100000.5500000000
18Scott WilsonTexas (DAL)LW/RW12112-1005513367.69%0685.7200000000110050.00%200000.5800000000
19Oscar FantenbergTexas (DAL)D16112-4140812142127.14%2326416.5200013000014100%000000.1500000000
20Matt MartinTexas (DAL)LW/RW4000-100104120%0235.75000000000000100.00%10000000000000
21Dylan McIlrathTexas (DAL)D7000-2402050120%38612.290000100002000%00000000000000
Statistiques d’équipe totales ou en moyenne288538914234183252702935521863919.60%177471316.3716264211052600074499351.52%154500010.6003121778
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
1Joel HoferTexas (DAL)117310.9312.3367101263790000.6673114310
2Matt KeetleyTexas (DAL)42200.8874.0024020161410200048000
3Darcy KuemperTexas (DAL)10100.8954.0759004380000014000
Statistiques d’équipe totales ou en moyenne169610.9182.84971214655802031616310


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Alex GoligoskiTexas (DAL)D391985-07-30USANo187 Lbs5 ft11NoNoFree AgentNoNo12026-09-14FalseFalsePro & Farm1,200,000$968,675$0$0$No---------------------------
Austin WatsonTexas (DAL)LW/RW331992-01-13USANo204 Lbs6 ft4NoNoFree AgentNoNo32026-09-21FalseFalsePro & Farm650,000$524,699$0$0$No650,000$650,000$-------650,000$650,000$-------NoNo-------Lien NHL
Benoit-Olivier GroulxTexas (DAL)C/LW252000-02-06FRAYes198 Lbs6 ft2NoNoProspectNoNo22026-09-02FalseFalsePro & Farm800,000$645,783$0$0$No800,000$--------800,000$--------No--------
Brian GibbonsTexas (DAL)C/LW/RW371988-02-26USANo176 Lbs5 ft8NoNoFree AgentNoNo12025-09-23FalseFalsePro & Farm1,210,000$976,747$0$0$No---------------------------Lien
Cole SchwindtTexas (DAL)C/RW242001-04-25CANYes182 Lbs6 ft2NoNoProspectNoNo12025-10-16FalseFalsePro & Farm600,000$484,337$0$0$No---------------------------
Cole SmithTexas (DAL)LW291995-10-28USANo195 Lbs6 ft3NoNoN/ANoNo12024-09-16FalseFalsePro & Farm850,000$686,145$0$0$No---------------------------Lien NHL
Conor ShearyTexas (DAL)LW/RW331992-06-08USANo179 Lbs5 ft9NoNoFree AgentNoNo22026-09-15FalseFalsePro & Farm1,600,000$1,291,566$0$0$No1,600,000$--------1,600,000$--------No--------Lien / Lien NHL
Darcy KuemperTexas (DAL)G351990-05-05CANNo220 Lbs6 ft5NoNoFree AgentNoNo12024-09-23FalseFalsePro & Farm981,000$791,892$0$0$No---------------------------Lien / Lien NHL
Dennis CholowskiTexas (DAL)D271998-02-15CANNo210 Lbs6 ft2NoNoProspectNoNo12026-09-02FalseFalsePro & Farm750,000$605,422$0$0$No---------------------------
Dylan McIlrathTexas (DAL)D331992-04-20CANNo238 Lbs6 ft5NoNoFree AgentNoNo12026-10-01FalseFalsePro & Farm500,000$403,614$0$0$No---------------------------Lien
Joel HoferTexas (DAL)G242000-07-30CANYes179 Lbs6 ft5NoNoN/ANoNo32026-09-02FalseFalsePro & Farm1,400,000$1,130,120$0$0$No1,400,000$1,400,000$-------1,400,000$1,400,000$-------NoNo-------Lien NHL
Kyle RauTexas (DAL)C/LW/RW321992-10-24USANo179 Lbs5 ft8NoNoN/ANoNo1FalseFalsePro & Farm950,000$766,867$0$0$No---------------------------Lien
Marc-Andre ClicheTexas (DAL)C/RW381987-03-23CANNo205 Lbs6 ft1NoNoFree AgentNoNo12025-09-27FalseFalsePro & Farm1,100,000$887,952$0$0$No---------------------------
Matt KeetleyTexas (DAL)G401985-01-10CANNo230 Lbs6 ft2NoNoFree AgentNoNo12024-09-23FalseFalsePro & Farm1,100,000$887,952$0$0$No---------------------------
Matt MartinTexas (DAL)LW/RW361989-01-01CANNo224 Lbs6 ft3NoNoFree AgentNoNo22026-09-21FalseFalsePro & Farm550,000$443,976$0$0$No550,000$--------550,000$--------No--------Lien / Lien NHL
Oscar FantenbergTexas (DAL)D331991-10-07SWENo210 Lbs6 ft0NoNoFree AgentNoNo12024-10-02FalseFalsePro & Farm1,281,000$1,034,060$0$0$No---------------------------Lien
Radim SimekTexas (DAL)D321992-09-20CZENo200 Lbs5 ft11NoNoFree AgentNoNo32026-09-19FalseFalsePro & Farm1,050,000$847,590$0$0$No1,050,000$1,050,000$-------1,050,000$1,050,000$-------NoNo-------Lien
Rick NashTexas (DAL)LW/RW411984-06-16CANNo228 Lbs6 ft4NoNoFree AgentNoNo12026-09-21FalseFalsePro & Farm1,250,000$1,009,036$0$0$No---------------------------
Riley NashTexas (DAL)C/LW/RW361989-05-09CANNo208 Lbs6 ft1NoNoFree Agent2024-10-02NoNo12025-09-24FalseFalsePro & Farm1,210,000$976,747$0$0$No---------------------------Lien
Ryan WhiteTexas (DAL)C/RW371988-03-17CANNo203 Lbs6 ft0NoNoFree AgentNoNo12026-10-01FalseFalsePro & Farm500,000$403,614$0$0$No---------------------------Lien
Scott WilsonTexas (DAL)LW/RW331992-04-24CANNo189 Lbs5 ft11NoNoFree AgentNoNo22025-10-30FalseFalsePro & Farm500,000$403,614$0$0$No500,000$--------500,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2133.19202 Lbs6 ft11.48953,905$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Conor ShearyBenoit-Olivier GroulxCole Schwindt35122
2Brian GibbonsKyle RauRick Nash30122
3Cole SmithRiley NashMarc-Andre Cliche25122
4Austin WatsonRyan WhiteScott Wilson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dennis CholowskiRadim Simek35122
2Oscar FantenbergAlex Goligoski30122
3Dylan McIlrathAustin Watson25122
4Dennis CholowskiRadim Simek10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Conor ShearyBenoit-Olivier GroulxCole Schwindt50122
2Brian GibbonsKyle RauRick Nash50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dennis CholowskiRadim Simek50122
2Oscar FantenbergAlex Goligoski50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Conor ShearyBenoit-Olivier Groulx50122
2Cole SchwindtKyle Rau50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dennis CholowskiRadim Simek50122
2Oscar FantenbergAlex Goligoski50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Conor Sheary50122Dennis CholowskiRadim Simek50122
2Benoit-Olivier Groulx50122Oscar FantenbergAlex Goligoski50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Conor ShearyBenoit-Olivier Groulx50122
2Cole SchwindtKyle Rau50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dennis CholowskiRadim Simek50122
2Oscar FantenbergAlex Goligoski50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Conor ShearyBenoit-Olivier GroulxCole SchwindtDennis CholowskiRadim Simek
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Conor ShearyBenoit-Olivier GroulxCole SchwindtDennis CholowskiRadim Simek
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Matt Martin, Cole Smith, Riley NashMatt Martin, Cole SmithRiley Nash
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dylan McIlrath, Oscar Fantenberg, Alex GoligoskiDylan McIlrathOscar Fantenberg, Alex Goligoski
Tirs de pénalité
Conor Sheary, Benoit-Olivier Groulx, Cole Schwindt, Kyle Rau, Brian Gibbons
Gardien
#1 : Darcy Kuemper, #2 : Joel Hofer
Lignes d’attaque personnalisées en prolongation
Conor Sheary, Benoit-Olivier Groulx, Cole Schwindt, Kyle Rau, Brian Gibbons, Cole Smith, Rick Nash, Riley Nash, Marc-Andre Cliche, Austin Watson
Lignes de défense personnalisées en prolongation
Dennis Cholowski, Radim Simek, Oscar Fantenberg, Alex Goligoski, Dylan McIlrath


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
TotalDomicile Visiteur
# 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 RI
1Abbotsford201010007701010000023-11000100054120.500711180020171336516916120421591725329222.22%10280.00%031560452.15%34966052.88%13226050.77%384253371128218109
2Bridgeport2020000058-3000000000002020000058-300.00059140020171335716916120421753224419222.22%11372.73%031560452.15%34966052.88%13226050.77%384253371128218109
3Coachella Valley10001000431000000000001000100043121.00046100020171334116916120421291618164125.00%2150.00%031560452.15%34966052.88%13226050.77%384253371128218109
4Hartford11000000321110000003210000000000021.00035800201713324169161204214613831200.00%4250.00%031560452.15%34966052.88%13226050.77%384253371128218109
5Iowa320000011349210000019451100000040450.833132235012017133109169161204218722285915533.33%14378.57%031560452.15%34966052.88%13226050.77%384253371128218109
6Providence2010100049-5000000000002010100049-520.50047110020171335916916120421941938206116.67%10190.00%031560452.15%34966052.88%13226050.77%384253371128218109
7San Diego211000007611010000034-11100000042220.500712190020171337816916120421622114279111.11%7271.43%031560452.15%34966052.88%13226050.77%384253371128218109
8San Jose21100000651211000006510000000000020.500610160020171337316916120421793020278337.50%10280.00%031560452.15%34966052.88%13226050.77%384253371128218109
9Wilkes-Barre/Scranton11000000431110000004310000000000021.0004711002017133461691612042127710175120.00%4175.00%031560452.15%34966052.88%13226050.77%384253371128218109
Total1666030015347684300001272168230300026260190.594538914201201713355216916120421558177185270671623.88%721776.39%031560452.15%34966052.88%13226050.77%384253371128218109
_Since Last GM Reset1666030015347684300001272168230300026260190.594538914201201713355216916120421558177185270671623.88%721776.39%031560452.15%34966052.88%13226050.77%384253371128218109
_Vs Conference1043020013725126230000120164420020001798130.65037619801201713336616916120421316106105161451226.67%431076.74%031560452.15%34966052.88%13226050.77%384253371128218109
_Vs Division320000011349210000019451100000040450.833132235012017133109169161204218722285915533.33%14378.57%031560452.15%34966052.88%13226050.77%384253371128218109

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1619L1538914255255817718527001
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
166630015347
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
84300012721
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
82330002626
Derniers 10 matchs
WLOTWOTL SOWSOL
630001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
671623.88%721776.39%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
169161204212017133
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
31560452.15%34966052.88%13226050.77%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
384253371128218109


Derniers matchs 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
29Texas3Providence2WXSommaire du match
320Texas2Bridgeport4LSommaire du match
529Iowa1Texas7WSommaire du match
745San Jose4Texas3LSommaire du match
959Texas5Abbotsford4WXSommaire du match
1171Texas1Providence7LSommaire du match
1383Abbotsford3Texas2LSommaire du match
1596Hartford2Texas3WSommaire du match
17110San Diego4Texas3LSommaire du match
19126San Jose1Texas3WSommaire du match
21141Texas4Iowa0WSommaire du match
23151Texas4Coachella Valley3WXSommaire du match
25162Iowa3Texas2LXXSommaire du match
27180Texas4San Diego2WSommaire du match
29190Wilkes-Barre/Scranton3Texas4WSommaire du match
31202Texas3Bridgeport4LSommaire du match
34219Iowa-Texas-
35231Texas-Wilkes-Barre/Scranton-
37241Texas-Rochester-
39254Abbotsford-Texas-
41269Rochester-Texas-
43283Texas-Coachella Valley-
44292Texas-Providence-
46306San Jose-Texas-
48318Texas-Tucson-
50333Tucson-Texas-
51340Texas-Charlotte-
54359Rochester-Texas-
56373Bakersfield-Texas-
57385San Diego-Texas-
59396Texas-Ontario-
60407Texas-Lehigh Valley-
62421Texas-Abbotsford-
64433Texas-Lehigh Valley-
66444Bakersfield-Texas-
68458Manitoba-Texas-
70474Wilkes-Barre/Scranton-Texas-
72491Texas-Syracuse-
74501Texas-Cleveland-
75513Ontario-Texas-
77528Cleveland-Texas-
78536Texas-Bakersfield-
80547Texas-Manitoba-
82564Laval-Texas-
84578Ontario-Texas-
85588Texas-Laval-
87597Texas-Hershey-
89614Rockford-Texas-
91627Texas-Grand Rapids-
92636Texas-Tucson-
94648Utica -Texas-
96665Coachella Valley-Texas-
99681Texas-Syracuse-
101694Utica -Texas-
103710Syracuse-Texas-
104719Texas-Bridgeport-
107737Providence-Texas-
109750Texas-Hershey-
111762Providence-Texas-
113770Texas-Springfield-
115785Texas-Syracuse-
117797Texas-Laval-
118805Grand Rapids-Texas-
120823Bridgeport-Texas-
122835Texas-Eagles-
124842Texas-Utica -
125852Grand Rapids-Texas-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
127863Texas-San Jose-
129879Hershey-Texas-
131890Texas-Charlotte-
133906Hartford-Texas-
135918Texas-Rockford-
137928Texas-Eagles-
138936Lehigh Valley-Texas-
140947Texas-Hartford-
141960Springfield-Texas-
143968Texas-Rockford-
145985Lehigh Valley-Texas-
146992Texas-Springfield-
1491012Charlotte-Texas-
1541035Manitoba-Texas-
1571056Eagles-Texas-
1611073Cleveland-Texas-
1621080Texas-Lehigh Valley-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance11,5005,663
Assistance PCT71.88%70.79%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
34 2145 - 71.51% 125,700$1,005,599$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
633,146$ 2,003,200$ 2,003,200$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
12,067$ 440,370$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
4,273,796$ 134 18,092$ 2,424,328$




Texas Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Texas Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Texas Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Texas Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Texas Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA