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Connexion

San Jose
GP: 69 | W: 34 | L: 27 | OTL: 8 | P: 76
GF: 235 | GA: 232 | PP%: 19.85% | PK%: 79.62%
DG: Vincent Fournier | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #881 vs Grand Rapids

Centre de jeu
Laval
32-31-7, 71pts
5
4 San Jose
34-27-8, 76pts
Team Stats
L1SéquenceW1
15-15-5Fiche domicile17-14-4
17-16-2Fiche domicile17-13-4
6-4-0Derniers 10 matchs7-2-1
3.26Buts par match 3.41
3.00Buts contre par match 3.36
18.53%Pourcentage en avantage numérique19.85%
84.29%Pourcentage en désavantage numérique79.62%
San Jose
34-27-8, 76pts
7
2 Utica
11-54-6, 28pts
Team Stats
W1SéquenceL27
17-14-4Fiche domicile6-26-3
17-13-4Fiche domicile5-28-3
7-2-1Derniers 10 matchs0-10-0
3.41Buts par match 2.21
3.36Buts contre par match 5.17
19.85%Pourcentage en avantage numérique16.73%
79.62%Pourcentage en désavantage numérique70.54%
Grand Rapids
33-33-4, 70pts
Jour 163
San Jose
34-27-8, 76pts
Statistiques d’équipe
L1SéquenceW1
18-14-3Fiche domicile17-14-4
15-19-1Fiche visiteur17-13-4
3-6-110 derniers matchs7-2-1
3.16Buts par match 3.41
3.43Buts contre par match 3.41
21.33%Pourcentage en avantage numérique19.85%
83.71%Pourcentage en désavantage numérique79.62%
Eagles
43-20-6, 92pts
Jour 167
San Jose
34-27-8, 76pts
Statistiques d’équipe
W4SéquenceW1
22-11-2Fiche domicile17-14-4
21-9-4Fiche visiteur17-13-4
6-3-110 derniers matchs7-2-1
3.52Buts par match 3.41
2.68Buts contre par match 3.41
19.48%Pourcentage en avantage numérique19.85%
81.43%Pourcentage en désavantage numérique79.62%
San Jose
34-27-8, 76pts
Jour 170
Ontario
47-19-3, 97pts
Statistiques d’équipe
W1SéquenceW1
17-14-4Fiche domicile23-12-0
17-13-4Fiche visiteur24-7-3
7-2-110 derniers matchs7-3-0
3.41Buts par match 3.86
3.36Buts contre par match 3.86
19.85%Pourcentage en avantage numérique24.82%
79.62%Pourcentage en désavantage numérique82.76%
Meneurs d'équipe
Buts
Saku Maenalanen
24
Passes
Dominik Simon
46
Points
Dominik Simon
68
Jack JohnsonPlus/Moins
Jack Johnson
12
Victoires
Jakob Markstrom
16
Pourcentage d’arrêts
Jakob Markstrom
0.904

Statistiques d’équipe
Buts pour
235
3.41 GFG
Tirs pour
2553
37.00 Avg
Pourcentage en avantage numérique
19.9%
53 GF
Début de zone offensive
40.4%
Buts contre
232
3.36 GAA
Tirs contre
2535
36.74 Avg
Pourcentage en désavantage numérique
79.6%%
53 GA
Début de la zone défensive
41.8%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,189
Billets de saison300


Informations de la formation

Équipe Pro19
Équipe Mineure20
Limite contact 39 / 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 FilatovXX100.00622898637460787130666658768266255000341500,000$
3Dominik SimonXXX100.00622799757782867468737362806052495000291875,000$
4Drew LarmanXXX100.0066328237706084685364676668998375000391500,000$
5Sam CarrickXX100.00793873738570806883686965746868275000321500,000$
6Brian FlynnXXX100.00681788597564886479656666756870175000351700,000$
7Sergei KalininXXX100.00713472658470876972686958786652315000332750,000$
8Michael GrabnerXX100.00673498637469927057687166728575225000362750,000$
9Zach Aston-ReeseXX100.008239927685789168716771677662604550002911,500,000$
10Michael PezzettaXX100.00855862828570857171697160755244495000262925,000$
11Michael EyssimontXXX100.00814582768076996668696969765653505000272925,000$
12Cole Koepke (R)XX97.00903593828274977070677269705252615000261500,000$
13Justin SchultzX100.00623486728180976050575482636754355000342500,000$
14Jack JohnsonX100.00622987507582905425515091709687245000372800,000$
15Ryan SuterX100.006234814366799958315253896499972250003921,150,000$
16Keith YandleX100.006832815575769466335757856992842450003711,750,000$
17Dennis GilbertX100.00753290728675994270424285755456525000271725,000$
18Calle RosenX100.007324847382769951705254907465664550003011,050,000$
Rayé
MOYENNE D’ÉQUIPE99.8372338666797391646062647273726635500
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$
Rayé
MOYENNE D’ÉQUIPE100.006387818278878786877783828141500
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/RW69224668112031192206615210.00%7129318.757152255229000003248.65%177400101.0501000342
2Saku MaenalanenSan Jose (S J)RW66243559710040562245815910.71%16106616.1731215381540000121250.94%10600301.1106000432
3Michael PezzettaSan Jose (S J)LW/RW692333564551519567235801699.79%4125518.207101756212000042260.92%8700000.8900102615
4Zach Aston-ReeseSan Jose (S J)LW/RW69223052-336010593290641797.59%13137719.9666126821200061914248.51%50300100.7616000233
5Michael EyssimontSan Jose (S J)C/LW/RW69222850070201201502074615610.63%16135519.64511163821110151854047.21%200400000.7416013254
6David RundbladSan JoseD68123042130045551195410410.08%135146221.5041014582190000208110%000000.5700000002
7Calle RosenSan Jose (S J)D69142539-654010969147561089.52%126157822.887815682160003186310%000100.4900000221
8Keith YandleSan Jose (S J)D6953338-538084649236875.43%126159423.1151116562170003192100%000000.4800000013
9Sam CarrickSan Jose (S J)C/RW69142034355510284142381219.86%682611.98101112000051154.55%107600000.8200001202
10Michael GrabnerSan Jose (S J)LW/RW69161632-3201244193431498.29%9129418.774373211600062024133.61%11900010.4902000401
11Jack JohnsonSan Jose (S J)D699223112540564572174312.50%93107215.5400049000021100%000000.5800000110
12Nikita FilatovSan Jose (S J)LW/RW69101828-14072811136709.01%184412.2400001000002037.70%6100000.6600000022
13Ryan SuterSan Jose (S J)D699182717201084410637798.49%111146821.28347492220110189300%000000.3700000013
14Cole KoepkeSan Jose (S J)LW/RW38101525102010454810627809.43%370418.5311217700002480040.91%6600000.7100002004
15Justin SchultzSan Jose (S J)D69519241141561706424467.81%94112116.2600026000275110%000000.4300010012
16Sergei KalininSan Jose (S J)C/LW/RW6941216018039299730604.12%46108.85022160003551155.04%12900000.5201000001
17Brian FlynnSan Jose (S J)C/LW/RW6978152140212264216510.94%36118.86000000111941063.38%7100000.4900000000
18Drew LarmanSan Jose (S J)C/LW/RW694812-16034305316347.55%54706.8100000000000040.10%58100000.5100000002
19Dennis GilbertSan Jose (S J)D25202-58065112718.18%01496.0000010000000037.50%800000.2700000001
Statistiques d’équipe totales ou en moyenne1232234416650385895511921122255375118689.17%7722015916.3653931465442120123311672331448.43%658500610.64222128262440
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 Jose37181260.9193.0221664010913390410.714143429332
2Jakob MarkstromSan Jose (S J)35161520.9043.4320146011511930420.71473536321
Statistiques d’équipe totales ou en moyenne72342780.9123.2241801002242532083216965653


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$118,462$0$0$No---------------------------Lien
Calle RosenSan Jose (S J)D301994-02-02SWENo188 Lbs6 ft1NoNoN/ANoNo12025-09-11FalseFalsePro & Farm1,050,000$177,692$0$0$No---------------------------
Cole KoepkeSan Jose (S J)LW/RW261998-05-17USAYes196 Lbs6 ft1NoNoProspectNoNo12025-10-16FalseFalsePro & Farm500,000$84,615$0$0$No---------------------------
Dennis GilbertSan Jose (S J)D271996-10-30USANo216 Lbs6 ft2NoNoProspectNoNo12025-09-11FalseFalsePro & Farm725,000$122,692$0$0$No---------------------------Lien NHL
Dominik SimonSan Jose (S J)C/LW/RW291994-08-08CZENo193 Lbs5 ft11NoNoN/ANoNo12024-09-15FalseFalsePro & Farm875,000$148,077$0$0$No---------------------------Lien
Drew LarmanSan Jose (S J)C/LW/RW391985-05-15USANo186 Lbs6 ft3NoNoFree AgentNoNo12025-10-08FalseFalsePro & Farm500,000$84,615$0$0$No---------------------------
Jack JohnsonSan Jose (S J)D371987-01-13USANo238 Lbs6 ft1NoNoFree AgentNoNo22025-09-30FalseFalsePro & Farm800,000$135,385$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$169,231$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$84,615$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$296,154$0$0$No---------------------------Lien
Michael EyssimontSan Jose (S J)C/LW/RW271996-09-09USANo180 Lbs6 ft0NoNoN/ANoNo22024-09-15FalseFalsePro & Farm925,000$156,538$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$126,923$0$0$No750,000$--------750,000$--------No--------Lien
Michael PezzettaSan Jose (S J)LW/RW261998-03-13CANNo210 Lbs6 ft1NoNoN/ANoNo22024-09-15FalseFalsePro & Farm925,000$156,538$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$84,615$0$0$No---------------------------
Ryan SuterSan Jose (S J)D391985-01-21USANo203 Lbs6 ft1NoNoFree AgentNoNo22025-10-06FalseFalsePro & Farm1,150,000$194,615$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$160,769$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$84,615$0$0$No---------------------------Lien / Lien NHL
Sergei KalininSan Jose (S J)C/LW/RW331991-03-17RUSNo205 Lbs6 ft3NoNoFree AgentNoNo22025-09-24FalseFalsePro & Farm750,000$126,923$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$253,846$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1932.32203 Lbs6 ft21.53860,526$



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 Suter33014
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 Suter50005
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 Suter50050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Saku Maenalanen50050Keith YandleCalle Rosen50050
2Michael Eyssimont50050Ryan Suter50050
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 Suter50041
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 : , #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, , 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
1Abbotsford43000010191182200000010552100001096381.000193251007974785163829838856521814554771119.09%22386.36%01311264249.62%1327273348.55%551116547.30%161710901654531912450
2Bakersfield421010001091210010007432110000035-260.750101929007974785139829838856521534349711218.33%17382.35%01311264249.62%1327273348.55%551116547.30%161710901654531912450
3Bridgeport2110000011651010000035-21100000081720.50011203100797478587829838856526520123413538.46%6266.67%01311264249.62%1327273348.55%551116547.30%161710901654531912450
4Charlotte20200000611-51010000035-21010000036-300.000610161079747856982983885652922722288112.50%11190.91%01311264249.62%1327273348.55%551116547.30%161710901654531912450
5Cleveland1000010045-1000000000001000010045-110.5004711007974785378298388565238112318500.00%30100.00%01311264249.62%1327273348.55%551116547.30%161710901654531912450
6Coachella Valley422000001214-2211000008802110000046-240.5001223350079747851248298388565216344308419736.84%15473.33%01311264249.62%1327273348.55%551116547.30%161710901654531912450
7Eagles30300000413-91010000014-32020000039-600.000471100797478583829838856521043133461119.09%14471.43%01311264249.62%1327273348.55%551116547.30%161710901654531912450
8Hartford31200000141222110000010731010000045-120.33314233710797478510182983885652873516541417.14%7357.14%01311264249.62%1327273348.55%551116547.30%161710901654531912450
9Hershey200010017701000000145-11000100032130.75071320007974785688298388565263181822300.00%9277.78%01311264249.62%1327273348.55%551116547.30%161710901654531912450
10Iowa522000012122-1312000001314-12100000188050.50021385900797478521882983885652179534285221150.00%19478.95%01311264249.62%1327273348.55%551116547.30%161710901654531912450
11Laval430000011394210000019722200000042270.8751322350079747851298298388565214540316612216.67%130100.00%01311264249.62%1327273348.55%551116547.30%161710901654531912450
12Lehigh Valley211000005501010000023-11100000032120.5005712007974785788298388565269161735800.00%6266.67%01311264249.62%1327273348.55%551116547.30%161710901654531912450
13Manitoba33000000963220000006421100000032161.000914230079747851378298388565210338244517211.76%12191.67%01311264249.62%1327273348.55%551116547.30%161710901654531912450
14Ontario30200100914-51010000034-120100100610-410.1679172600797478510582983885652107372564700.00%10280.00%01311264249.62%1327273348.55%551116547.30%161710901654531912450
15Providence21100000550110000003121010000024-220.50058130079747856382983885652832516343133.33%8275.00%01311264249.62%1327273348.55%551116547.30%161710901654531912450
16Rochester2110000047-31010000015-41100000032120.5004812007974785908298388565260151734900.00%6183.33%01311264249.62%1327273348.55%551116547.30%161710901654531912450
17Rockford321000001394211000009721100000042240.6671321341079747851038298388565212743264018422.22%13376.92%01311264249.62%1327273348.55%551116547.30%161710901654531912450
18San Diego403010001115-4201010008802020000037-420.2501121320079747851268298388565216861427116318.75%19573.68%11311264249.62%1327273348.55%551116547.30%161710901654531912450
19Springfield40300001916-72010000158-32020000048-410.125916250079747851378298388565213941267817211.76%12375.00%01311264249.62%1327273348.55%551116547.30%161710901654531912450
20Syracuse210001006511000010023-11100000042230.75061117007974785708298388565259198376116.67%4175.00%01311264249.62%1327273348.55%551116547.30%161710901654531912450
21Texas43000001171252200000074321000001108270.8751728450079747851628298388565213039287617635.29%14285.71%01311264249.62%1327273348.55%551116547.30%161710901654531912450
22Utica 330000001861211000000532220000001331061.00018355300797478516682983885652953026436233.33%13376.92%01311264249.62%1327273348.55%551116547.30%161710901654531912450
23Wilkes-Barre/Scranton31200000813-52110000067-11010000026-420.33381624007974785988298388565212541145013215.38%7271.43%01311264249.62%1327273348.55%551116547.30%161710901654531912450
Total69302703315235232335151402103125121434151301212110111-1760.551235416651307974785255382983885652253577259911922675319.85%2605379.62%11311264249.62%1327273348.55%551116547.30%161710901654531912450
_Since Last GM Reset69302703315235232335151402103125121434151301212110111-1760.551235416651307974785255382983885652253577259911922675319.85%2605379.62%11311264249.62%1327273348.55%551116547.30%161710901654531912450
_Vs Conference41171702113134141-72110802001777072079001125771-14440.53713423637010797478514978298388565215544753797371673822.75%1673479.64%11311264249.62%1327273348.55%551116547.30%161710901654531912450
_Vs Division1978021106163-294302000362971035001102534-9210.5536111217300797478565782983885652772230200367651218.46%831779.52%11311264249.62%1327273348.55%551116547.30%161710901654531912450

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6976W123541665125532535772599119230
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6930273315235232
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3515142103125121
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
2675319.85%2605379.62%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
829838856527974785
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
1311264249.62%1327273348.55%551116547.30%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
161710901654531912450


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 Rapids-San Jose-
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
Assistance51,33925,266
Assistance PCT73.34%72.19%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
6 2189 - 72.96% 128,247$4,488,649$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,705,170$ 1,635,000$ 1,635,000$ 1,500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,385$ 1,458,968$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
769,483$ 33 16,077$ 530,541$




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