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Connexion

San Jose
GP: 70 | W: 35 | L: 27 | OTL: 8 | P: 78
GF: 239 | GA: 235 | PP%: 19.57% | PK%: 79.55%
DG: Vincent Fournier | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #904 vs Eagles

Centre de jeu
San Jose
35-27-8, 78pts
7
2 Utica
11-56-6, 28pts
Team Stats
W2SéquenceL29
18-14-4Fiche domicile6-27-3
17-13-4Fiche domicile5-29-3
7-2-1Derniers 10 matchs0-10-0
3.41Buts par match 2.19
3.36Buts contre par match 5.16
19.57%Pourcentage en avantage numérique16.60%
79.55%Pourcentage en désavantage numérique70.85%
Grand Rapids
34-33-5, 73pts
3
4 San Jose
35-27-8, 78pts
Team Stats
W1SéquenceW2
19-14-3Fiche domicile18-14-4
15-19-2Fiche domicile17-13-4
3-5-2Derniers 10 matchs7-2-1
3.22Buts par match 3.41
3.43Buts contre par match 3.36
22.11%Pourcentage en avantage numérique19.57%
83.93%Pourcentage en désavantage numérique79.55%
Eagles
44-20-6, 94pts
Jour 167
San Jose
35-27-8, 78pts
Statistiques d’équipe
W5SéquenceW2
23-11-2Fiche domicile18-14-4
21-9-4Fiche visiteur17-13-4
6-3-110 derniers matchs7-2-1
3.51Buts par match 3.41
2.67Buts contre par match 3.41
19.40%Pourcentage en avantage numérique19.57%
81.47%Pourcentage en désavantage numérique79.55%
San Jose
35-27-8, 78pts
Jour 170
Ontario
48-20-3, 99pts
Statistiques d’équipe
W2SéquenceW1
18-14-4Fiche domicile23-13-0
17-13-4Fiche visiteur25-7-3
7-2-110 derniers matchs7-3-0
3.41Buts par match 3.93
3.36Buts contre par match 3.93
19.57%Pourcentage en avantage numérique25.26%
79.55%Pourcentage en désavantage numérique82.94%
San Jose
35-27-8, 78pts
Jour 173
Eagles
44-20-6, 94pts
Statistiques d’équipe
W2SéquenceW5
18-14-4Fiche domicile23-11-2
17-13-4Fiche visiteur21-9-4
7-2-110 derniers matchs6-3-1
3.41Buts par match 3.51
3.36Buts contre par match 3.51
19.57%Pourcentage en avantage numérique19.40%
79.55%Pourcentage en désavantage numérique81.47%
Meneurs d'équipe
Buts
Saku Maenalanen
24
Passes
Dominik Simon
47
Points
Dominik Simon
71
Plus/Moins
Dominik Simon
13
Connor IngramVictoires
Connor Ingram
18
Connor IngramPourcentage d’arrêts
Connor Ingram
0.919

Statistiques d’équipe
Buts pour
239
3.41 GFG
Tirs pour
2595
37.07 Avg
Pourcentage en avantage numérique
19.6%
54 GF
Début de zone offensive
40.6%
Buts contre
235
3.36 GAA
Tirs contre
2568
36.69 Avg
Pourcentage en désavantage numérique
79.5%%
54 GA
Début de la zone défensive
41.7%
Informations de l'équipe

Directeur généralVincent Fournier
EntraîneurJack Capuano
DivisionPacifique
ConférenceConference ouest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,192
Billets de saison300


Informations de la formation

Équipe Pro21
Équipe Mineure19
Limite contact 40 / 50
Espoirs40


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
1Saku MaenalanenX100.00743094749072876970697076756461395000303950,000$
2Nikita FilatovXX100.00622898637460787130666658768267255000341500,000$
3Dominik SimonXXX100.00622799757782867468737362806052495000291875,000$
4Drew LarmanXXX100.0066328237706084685364676668998475000391500,000$
5Sam CarrickXX100.00793873738570806883686965746869275000321500,000$
6Brian FlynnXXX100.00681788597564886479656666756871175000351700,000$
7Sergei KalininXXX100.00713472658470876972686958786652315000332750,000$
8Michael GrabnerXX100.00673498637469927057687166728576225000362750,000$
9Zach Aston-ReeseXX100.008239927685789168716771677662604550002911,500,000$
10Michael PezzettaXX100.00855862828570857171707160755244495000262925,000$
11Michael EyssimontXXX100.00814582768076996668696969765653505000272925,000$
12Cole Koepke (R)XX98.00903593828274977070677269705252615000261500,000$
13Justin SchultzX100.00623486728180976050575482636754355000342500,000$
14Jack JohnsonX100.00622987507582905425515091709688245000372800,000$
15David RundbladX100.00573394679275845650545289697060305000332500,000$
16Ryan SuterX100.006234814366799958315253896499982250003921,150,000$
17Keith YandleX100.006832815575769466335757856992852450003711,750,000$
18Dennis GilbertX100.00753290728675994270424285755456525000271725,000$
19Calle RosenX100.007324847382769951705254907465674550003011,050,000$
Rayé
MOYENNE D’ÉQUIPE99.8971338666807390645962637373716634500
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
1Jakob Markstrom100.00638781827887878687778382814150003421,000,000$
2Connor Ingram100.0067959080789085868779855555745000273950,000$
Rayé
MOYENNE D’ÉQUIPE100.006591868178898686877884696858500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jack Capuano95787887949972USA5711,500,000$


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
1Dominik SimonSan Jose (S J)C/LW/RW70244771132031242286915510.53%7131418.788152359238000004248.58%180100101.0801000442
2Saku MaenalanenSan Jose (S J)RW67243660810041572305916310.43%17108516.2031215401630000121251.38%10900301.1106000432
3Michael PezzettaSan Jose (S J)LW/RW702336596551519768239811759.62%4127618.247111857221000042259.55%8900000.9200102625
4Zach Aston-ReeseSan Jose (S J)LW/RW70223052-536010997292651847.53%14140020.0166126922100061944248.54%51300100.7416000233
5Michael EyssimontSan Jose (S J)C/LW/RW70222850-270201221502094715710.53%17137919.70511163822010151894047.18%203700000.7216013254
6David RundbladSan Jose (S J)D68123042130045551195410410.08%135146221.5041014582190000208110%000000.5700000002
7Calle RosenSan Jose (S J)D70142539-654011570149571089.40%127160322.907815702240003189310%000100.4900000221
8Keith YandleSan Jose (S J)D7053338-540085659436885.32%129161923.1351116582250003194100%000000.4700000013
9Sam CarrickSan Jose (S J)C/RW701421354601010285145381239.66%683611.95101112000051154.57%109400000.8400002202
10Michael GrabnerSan Jose (S J)LW/RW70161632-5201244196431538.16%9131018.724373211600062044133.61%11900010.4902000401
11Jack JohnsonSan Jose (S J)D709223112560564572174312.50%93108515.5100049000021100%000000.5700000110
12Nikita FilatovSan Jose (S J)LW/RW7011182904072811236719.82%185312.1900001000002037.70%6100000.6800000022
13Ryan SuterSan Jose (S J)D709192827201084410940828.26%112149221.32347522310110193300%000000.3800000013
14Cole KoepkeSan Jose (S J)LW/RW391116271122104649109288510.09%472618.6412317790003510040.91%6600000.7400002005
15Justin SchultzSan Jose (S J)D70519241141561716424467.81%94113416.2100026000275110%000000.4200010012
16Sergei KalininSan Jose (S J)C/LW/RW7041216018040299930614.04%46178.82022170003551155.38%13000000.5201000001
17Brian FlynnSan Jose (S J)C/LW/RW7078152140212265216610.77%36168.81000000111941063.38%7100000.4900000000
18Drew LarmanSan Jose (S J)C/LW/RW704812-18034315317367.55%54856.9300000000000040.20%58700000.4900000002
19Dennis GilbertSan Jose (S J)D25202-58065112718.18%01496.0000010000000037.50%800000.2700000001
Statistiques d’équipe totales ou en moyenne1249238424662416026012101139259576419079.17%7812045016.3754951495592199123321694341448.42%668500610.65222129272541
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
1Connor IngramSan Jose (S J)37181260.9193.0221664010913390410.714143429332
2Jakob MarkstromSan Jose (S J)36171520.9043.4120776011812260420.71473637321
Statistiques d’équipe totales ou en moyenne73352780.9123.2142431002272565083217066653


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
Brian FlynnSan Jose (S J)C/LW/RW351988-07-26USANo191 Lbs6 ft1NoNoFree AgentNoNo12025-09-26FalseFalsePro & Farm700,000$104,103$0$0$No---------------------------Lien
Calle RosenSan Jose (S J)D301994-02-02SWENo188 Lbs6 ft1NoNoN/ANoNo12025-09-11FalseFalsePro & Farm1,050,000$156,154$0$0$No---------------------------
Cole KoepkeSan Jose (S J)LW/RW261998-05-17USAYes196 Lbs6 ft1NoNoProspectNoNo12025-10-16FalseFalsePro & Farm500,000$74,359$0$0$No---------------------------
Connor IngramSan Jose (S J)G271997-03-31CANNo196 Lbs6 ft2NoNoProspectNoNo32025-09-11FalseFalsePro & Farm950,000$141,282$0$0$No950,000$950,000$-------950,000$950,000$-------NoNo-------Lien NHL
David RundbladSan Jose (S J)D331990-10-08SWENo194 Lbs6 ft2NoNoFree AgentNoNo22025-10-08FalseFalsePro & Farm500,000$74,359$0$0$No500,000$--------500,000$--------No--------Lien
Dennis GilbertSan Jose (S J)D271996-10-30USANo216 Lbs6 ft2NoNoProspectNoNo12025-09-11FalseFalsePro & Farm725,000$107,821$0$0$No---------------------------Lien NHL
Dominik SimonSan Jose (S J)C/LW/RW291994-08-08CZENo193 Lbs5 ft11NoNoN/ANoNo12024-09-15FalseFalsePro & Farm875,000$130,128$0$0$No---------------------------Lien
Drew LarmanSan Jose (S J)C/LW/RW391985-05-15USANo186 Lbs6 ft3NoNoFree AgentNoNo12025-10-08FalseFalsePro & Farm500,000$74,359$0$0$No---------------------------
Jack JohnsonSan Jose (S J)D371987-01-13USANo238 Lbs6 ft1NoNoFree AgentNoNo22025-09-30FalseFalsePro & Farm800,000$118,974$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Jakob MarkstromSan Jose (S J)G341990-01-31SWENo212 Lbs6 ft6NoNoFree AgentNoNo22024-09-28FalseFalsePro & Farm1,000,000$148,718$0$0$No1,000,000$--------1,000,000$--------No--------Lien
Justin SchultzSan Jose (S J)D341990-06-07CANNo199 Lbs6 ft2NoNoFree AgentNoNo22025-10-08FalseFalsePro & Farm500,000$74,359$0$0$No500,000$--------500,000$--------No--------Lien / Lien NHL
Keith YandleSan Jose (S J)D371986-09-09USANo215 Lbs6 ft2NoNoFree AgentNoNo12024-10-02FalseFalsePro & Farm1,750,000$260,256$0$0$No---------------------------Lien
Michael EyssimontSan Jose (S J)C/LW/RW271996-09-09USANo180 Lbs6 ft0NoNoN/ANoNo22024-09-15FalseFalsePro & Farm925,000$137,564$0$0$No925,000$--------925,000$--------No--------Lien NHL
Michael GrabnerSan Jose (S J)LW/RW361987-10-05AUSNo198 Lbs6 ft0NoNoFree AgentNoNo22025-09-26FalseFalsePro & Farm750,000$111,538$0$0$No750,000$--------750,000$--------No--------Lien
Michael PezzettaSan Jose (S J)LW/RW261998-03-13CANNo210 Lbs6 ft1NoNoN/ANoNo22024-09-15FalseFalsePro & Farm925,000$137,564$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Nikita FilatovSan Jose (S J)LW/RW341990-01-11RUSNo196 Lbs6 ft6NoNoFree AgentNoNo12025-10-08FalseFalsePro & Farm500,000$74,359$0$0$No---------------------------
Ryan SuterSan Jose (S J)D391985-01-21USANo203 Lbs6 ft1NoNoFree AgentNoNo22025-10-06FalseFalsePro & Farm1,150,000$171,026$0$0$No1,150,000$--------1,150,000$--------No--------Lien / Lien NHL
Saku MaenalanenSan Jose (S J)RW301994-05-29FINNo214 Lbs6 ft4NoNoN/ANoNo32025-09-11FalseFalsePro & Farm950,000$141,282$0$0$No950,000$950,000$-------950,000$950,000$-------NoNo-------
Sam CarrickSan Jose (S J)C/RW321992-02-04CANNo205 Lbs6 ft0NoNoFree AgentNoNo12025-10-08FalseFalsePro & Farm500,000$74,359$0$0$No---------------------------Lien / Lien NHL
Sergei KalininSan Jose (S J)C/LW/RW331991-03-17RUSNo205 Lbs6 ft3NoNoFree AgentNoNo22025-09-24FalseFalsePro & Farm750,000$111,538$0$0$No750,000$--------750,000$--------No--------Lien
Zach Aston-ReeseSan Jose (S J)LW/RW291994-08-10USANo204 Lbs6 ft0NoNoFree AgentNoNo12025-09-22FalseFalsePro & Farm1,500,000$223,077$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2132.10202 Lbs6 ft21.62847,619$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael PezzettaDominik SimonCole Koepke32005
2Zach Aston-ReeseMichael EyssimontMichael Grabner30005
3Nikita FilatovSam CarrickSaku Maenalanen26005
4Sergei KalininDrew LarmanBrian Flynn12005
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Keith YandleCalle Rosen36014
2Ryan SuterDavid Rundblad33014
3Jack JohnsonJustin Schultz31023
4Calle RosenKeith Yandle0005
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael PezzettaDominik SimonCole Koepke50005
2Zach Aston-ReeseMichael EyssimontSaku Maenalanen50005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Keith YandleCalle Rosen50005
2Ryan SuterDavid Rundblad50005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Michael EyssimontCole Koepke50050
2Zach Aston-ReeseMichael Grabner50050
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Keith YandleCalle Rosen50050
2Ryan SuterDavid Rundblad50050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Saku Maenalanen50050Keith YandleCalle Rosen50050
2Michael Eyssimont50050Ryan SuterDavid Rundblad50050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Brian FlynnMichael Pezzetta50023
2Zach Aston-ReeseMichael Grabner50023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Keith YandleCalle Rosen50041
2Ryan SuterDavid Rundblad50041
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael GrabnerDominik SimonCole KoepkeKeith YandleCalle Rosen
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael EyssimontDominik SimonSaku MaenalanenKeith YandleCalle Rosen
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Sam Carrick, Michael Pezzetta, Sergei KalininMichael Grabner, Michael PezzettaSergei Kalinin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jack Johnson, Justin Schultz, Ryan SuterJack JohnsonJustin Schultz, Jack Johnson
Tirs de pénalité
Saku Maenalanen, Michael Eyssimont, Zach Aston-Reese, Michael Grabner, Dominik Simon
Gardien
#1 : Connor Ingram, #2 : Jakob Markstrom
Lignes d’attaque personnalisées en prolongation
Saku Maenalanen, Michael Grabner, Zach Aston-Reese, Michael Eyssimont, Dominik Simon, Michael Pezzetta, Sam Carrick, Nikita Filatov, Sergei Kalinin, Brian Flynn
Lignes de défense personnalisées en prolongation
Keith Yandle, Calle Rosen, Ryan Suter, David Rundblad, Jack Johnson


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
TotalDomicileVisiteur
# 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
1Abbotsford43000010191182200000010552100001096381.000193251008175786163842850872531814554771119.09%22386.36%01334269349.54%1344276848.55%559117947.41%164611101675539925458
2Bakersfield421010001091210010007432110000035-260.750101929008175786139842850872531534349711218.33%17382.35%01334269349.54%1344276848.55%559117947.41%164611101675539925458
3Bridgeport2110000011651010000035-21100000081720.50011203100817578687842850872536520123413538.46%6266.67%01334269349.54%1344276848.55%559117947.41%164611101675539925458
4Charlotte20200000611-51010000035-21010000036-300.000610161081757866984285087253922722288112.50%11190.91%01334269349.54%1344276848.55%559117947.41%164611101675539925458
5Cleveland1000010045-1000000000001000010045-110.5004711008175786378428508725338112318500.00%30100.00%01334269349.54%1344276848.55%559117947.41%164611101675539925458
6Coachella Valley422000001214-2211000008802110000046-240.5001223350081757861248428508725316344308419736.84%15473.33%01334269349.54%1344276848.55%559117947.41%164611101675539925458
7Eagles30300000413-91010000014-32020000039-600.000471100817578683842850872531043133461119.09%14471.43%01334269349.54%1344276848.55%559117947.41%164611101675539925458
8Grand Rapids10001000431100010004310000000000021.0004812008175786428428508725333913189111.11%4175.00%01334269349.54%1344276848.55%559117947.41%164611101675539925458
9Hartford31200000141222110000010731010000045-120.33314233710817578610184285087253873516541417.14%7357.14%01334269349.54%1344276848.55%559117947.41%164611101675539925458
10Hershey200010017701000000145-11000100032130.75071320008175786688428508725363181822300.00%9277.78%01334269349.54%1344276848.55%559117947.41%164611101675539925458
11Iowa522000012122-1312000001314-12100000188050.50021385900817578621884285087253179534285221150.00%19478.95%01334269349.54%1344276848.55%559117947.41%164611101675539925458
12Laval430000011394210000019722200000042270.8751322350081757861298428508725314540316612216.67%130100.00%01334269349.54%1344276848.55%559117947.41%164611101675539925458
13Lehigh Valley211000005501010000023-11100000032120.5005712008175786788428508725369161735800.00%6266.67%01334269349.54%1344276848.55%559117947.41%164611101675539925458
14Manitoba33000000963220000006421100000032161.000914230081757861378428508725310338244517211.76%12191.67%01334269349.54%1344276848.55%559117947.41%164611101675539925458
15Ontario30200100914-51010000034-120100100610-410.1679172600817578610584285087253107372564700.00%10280.00%01334269349.54%1344276848.55%559117947.41%164611101675539925458
16Providence21100000550110000003121010000024-220.50058130081757866384285087253832516343133.33%8275.00%01334269349.54%1344276848.55%559117947.41%164611101675539925458
17Rochester2110000047-31010000015-41100000032120.5004812008175786908428508725360151734900.00%6183.33%01334269349.54%1344276848.55%559117947.41%164611101675539925458
18Rockford321000001394211000009721100000042240.6671321341081757861038428508725312743264018422.22%13376.92%01334269349.54%1344276848.55%559117947.41%164611101675539925458
19San Diego403010001115-4201010008802020000037-420.2501121320081757861268428508725316861427116318.75%19573.68%11334269349.54%1344276848.55%559117947.41%164611101675539925458
20Springfield40300001916-72010000158-32020000048-410.125916250081757861378428508725313941267817211.76%12375.00%01334269349.54%1344276848.55%559117947.41%164611101675539925458
21Syracuse210001006511000010023-11100000042230.75061117008175786708428508725359198376116.67%4175.00%01334269349.54%1344276848.55%559117947.41%164611101675539925458
22Texas43000001171252200000074321000001108270.8751728450081757861628428508725313039287617635.29%14285.71%01334269349.54%1344276848.55%559117947.41%164611101675539925458
23Utica 330000001861211000000532220000001331061.00018355300817578616684285087253953026436233.33%13376.92%01334269349.54%1344276848.55%559117947.41%164611101675539925458
24Wilkes-Barre/Scranton31200000813-52110000067-11010000026-420.33381624008175786988428508725312541145013215.38%7271.43%01334269349.54%1344276848.55%559117947.41%164611101675539925458
Total70302704315239235436151403103129124534151301212110111-1780.557239424663308175786259584285087253256878161212102765419.57%2645479.55%11334269349.54%1344276848.55%559117947.41%164611101675539925458
_Since Last GM Reset70302704315239235436151403103129124534151301212110111-1780.557239424663308175786259584285087253256878161212102765419.57%2645479.55%11334269349.54%1344276848.55%559117947.41%164611101675539925458
_Vs Conference41171702113134141-72110802001777072079001125771-14440.53713423637010817578614978428508725315544753797371673822.75%1673479.64%11334269349.54%1344276848.55%559117947.41%164611101675539925458
_Vs Division1978021106163-294302000362971035001102534-9210.5536111217300817578665784285087253772230200367651218.46%831779.52%11334269349.54%1344276848.55%559117947.41%164611101675539925458

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7078W223942466325952568781612121030
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7030274315239235
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3615143103129124
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3415131212110111
Derniers 10 matchs
WLOTWOTL SOWSOL
720001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2765419.57%2645479.55%1
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
842850872538175786
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
1334269349.54%1344276848.55%559117947.41%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
164611101675539925458


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
15Bakersfield2San Jose4WSommaire du match
524San Jose5Ontario6LXSommaire du match
834Eagles4San Jose1LSommaire du match
1145San Jose1Ontario4LSommaire du match
1461San Jose4Coachella Valley3WSommaire du match
1568Hartford4San Jose2LSommaire du match
1985Iowa5San Jose3LSommaire du match
2197San Jose2Eagles6LSommaire du match
24108San Jose3Abbotsford1WSommaire du match
26117Bakersfield2San Jose3WXSommaire du match
28132San Jose4Iowa3WSommaire du match
30141San Jose2Springfield5LSommaire du match
32148Springfield4San Jose3LXXSommaire du match
33159San Jose2Laval1WSommaire du match
35170San Jose2Bakersfield1WSommaire du match
37177Abbotsford3San Jose5WSommaire du match
40194Manitoba3San Jose4WSommaire du match
42209San Jose3Lehigh Valley2WSommaire du match
44219San Jose2Springfield3LSommaire du match
45224Texas2San Jose4WSommaire du match
48237San Jose4Cleveland5LXSommaire du match
50248Syracuse3San Jose2LXSommaire du match
55270Abbotsford2San Jose5WSommaire du match
58288Rochester5San Jose1LSommaire du match
60294San Jose0Coachella Valley3LSommaire du match
62309San Jose6Abbotsford5WXXSommaire du match
64319Providence1San Jose3WSommaire du match
69342Texas2San Jose3WSommaire du match
72361San Diego7San Jose6LSommaire du match
74370San Jose4Hartford5LSommaire du match
76385Iowa5San Jose7WSommaire du match
78397San Jose8Bridgeport1WSommaire du match
80409San Jose4Syracuse2WSommaire du match
81415Rockford6San Jose4LSommaire du match
83433Springfield4San Jose2LSommaire du match
86446San Jose2San Diego4LSommaire du match
87459Iowa4San Jose3LSommaire du match
90472San Jose1Bakersfield4LSommaire du match
93486Hartford3San Jose8WSommaire du match
96499San Jose1San Diego3LSommaire du match
98511Lehigh Valley3San Jose2LSommaire du match
101523San Jose4Texas5LXXSommaire du match
103537Hershey5San Jose4LXXSommaire du match
105547San Jose4Iowa5LXXSommaire du match
107562Coachella Valley2San Jose4WSommaire du match
109573San Jose3Charlotte6LSommaire du match
110584Bridgeport5San Jose3LSommaire du match
112595San Jose6Texas3WSommaire du match
115610Manitoba1San Jose2WSommaire du match
119630San Jose6Utica 1WSommaire du match
120639Charlotte5San Jose3LSommaire du match
123656San Jose2Providence4LSommaire du match
124664Coachella Valley6San Jose4LSommaire du match
127676San Jose3Hershey2WXSommaire du match
129687Utica 3San Jose5WSommaire du match
132705San Jose1Eagles3LSommaire du match
134713Wilkes-Barre/Scranton3San Jose4WSommaire du match
136728Ontario4San Jose3LSommaire du match
138741San Jose4Rockford2WSommaire du match
139749San Jose3Rochester2WSommaire du match
141762Wilkes-Barre/Scranton4San Jose2LSommaire du match
146784San Diego1San Jose2WXSommaire du match
149798San Jose2Wilkes-Barre/Scranton6LSommaire du match
151808Rockford1San Jose5WSommaire du match
154828Laval2San Jose5WSommaire du match
155837San Jose2Laval1WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
157848San Jose3Manitoba2WSommaire du match
159857Laval5San Jose4LXXSommaire du match
161867San Jose7Utica 2WSommaire du match
163881Grand Rapids3San Jose4WXSommaire du match
167904Eagles-San Jose-
170914San Jose-Ontario-
173928San Jose-Eagles-
174933Bakersfield-San Jose-
176945San Jose-Rockford-
179958Ontario-San Jose-
181968San Jose-Manitoba-
184980San Jose-Coachella Valley-
185984San Jose-Ontario-
187992Eagles-San Jose-
1921012Cleveland-San Jose-
1931021San Jose-Grand Rapids-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance52,92125,974
Assistance PCT73.50%72.15%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
5 2192 - 73.05% 128,447$4,624,108$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,770,966$ 1,780,000$ 1,780,000$ 1,500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,128$ 1,493,994$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
642,237$ 29 16,821$ 487,809$




San Jose 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

San Jose 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

San Jose 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

San Jose 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

San Jose 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