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San Jose
GP: 82 | W: 49 | L: 25 | OTL: 8 | P: 106
GF: 309 | GA: 262 | PP%: 18.69% | PK%: 81.25%
DG: Vincent Fournier | Morale : 50 | Moyenne d’équipe : N/A
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Centre de jeu
Tucson
34-38-10, 78pts
2
FINAL
5 San Jose
49-25-8, 106pts
Team Stats
W1StreakW2
20-16-5Home Record24-15-2
14-22-5Away Record25-10-6
4-4-2Last 10 Games8-1-1
2.99Buts par match 3.77
3.91Buts contre par match 3.20
18.54%Pourcentage en avantage numérique18.69%
78.84%Pourcentage en désavantage numérique81.25%
San Jose
49-25-8, 106pts
2
FINAL
1 Texas
52-27-3, 107pts
Team Stats
W2StreakL1
24-15-2Home Record30-9-2
25-10-6Away Record22-18-1
8-1-1Last 10 Games5-5-0
3.77Buts par match 3.35
3.20Buts contre par match 2.71
18.69%Pourcentage en avantage numérique15.54%
81.25%Pourcentage en désavantage numérique86.51%
Meneurs d'équipe
Buts
Luke Glendening
39
Passes
Parker Kelly
51
Points
Parker Kelly
85
Plus/Moins
Alexey Marchenko
32
Victoires
Anton Khudobin
25
Pourcentage d’arrêts
Jakob Markstrom
0.911

Statistiques d’équipe
Buts pour
309
3.77 GFG
Tirs pour
3004
36.63 Avg
Pourcentage en avantage numérique
18.7%
63 GF
Début de zone offensive
42.1%
Buts contre
262
3.20 GAA
Tirs contre
2744
33.46 Avg
Pourcentage en désavantage numérique
81.3%%
60 GA
Début de la zone défensive
40.3%
Informations de l'équipe

Directeur généralVincent Fournier
EntraîneurRalph Krueger
DivisionPacifique
ConférenceConference ouest
Capitaine
Assistant #1Thomas Chabot
Assistant #2Michael Dal Colle


Informations de l’aréna

Capacité3,000
Assistance2,280
Billets de saison300


Informations de la formation

Équipe Pro21
Équipe Mineure19
Limite contact 40 / 50
Espoirs37


Historique d'équipe

Saison actuelle49-25-8 (106PTS)
Historique98-50-16 (0.598%)
Apparitions en séries éliminatoires 0
Historique en séries éliminatoires (W-L)-
Coupe Stanley0


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 moyen
1Beau BennettXX100.00683195767579767472717264775755485000292900,000$
2Dustin BoydXXX100.00531393527869846063646363758066185000351850,000$
3Michael BlundenXX100.00763171577971826457656364737479215000341850,000$
4Luke GlendeningXX100.00913093738080907095687375757383195000321975,000$
5Robert NilssonXX100.00551793486760876272636158738672155000361700,000$
6Justin FontaineX100.00532893667172826668636665726662275000332800,000$
7Freddie HamiltonXXX100.00773077717867886873676964715755355000291800,000$
8Drew ShoreX100.00733088698678906993686865775753515000301500,000$
9Leo KomarovXX100.00663195587770817074687174746963115000341850,000$
10Nathan Bastian (R)X100.00935078759076877070677364754141715000232900,000$
11Noah Gregor (R)XX100.00863090848182877370717170753838725000223500,000$
12Michael Pezzetta (R)XX100.00895574798768836970677061774242645000232500,000$
13Parker Kelly (R)XX100.00874081808273947070687273753838675000223500,000$
14Adam McQuaid X100.00764567658282784850504985727065215000341900,000$
15David SchlemkoX100.00622991638276715250514884787771155000341950,000$
16Justin BraunX100.0062388261727088481444682487159315000332500,000$
17Alexey MarchenkoX100.00653790798785855450504889705351545000293950,000$
18Jake Walman (R)X100.00812591778279844850484887754949675000251500,000$
19Michael SauerX100.00594782588072654915148875579723850003311,200,000$
Rayé
MOYENNE D’ÉQUIPE100.0072348568807483626061627272625939500
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 moyen
1Anton Khudobin100.0064747983759697969790898585395000351975,000$
2Jakob Markstrom100.0067877797809794969586937271505000312975,000$
Rayé
MOYENNE D’ÉQUIPE100.006681789078979696968891797845500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ralph Krueger82828583968661CAN6011,150,000$


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
1Parker KellySan Jose (S J)C/LW82345185295551221992569519713.28%22164220.04418225325310173077347.73%242600111.03001001022
2Luke GlendeningSan Jose (S J)C/RW81394382136151121832827618413.83%20159519.691313267928111281354458.70%236100101.0300000582
3Beau BennettSan Jose (S J)LW/RW8229386729008812688317210.82%10132116.124151968257000047147.57%10300011.0159000535
4Michael PezzettaSan Jose (S J)LW/RW82214162181374516373215611689.77%13130015.8651520392480000242246.67%13500000.9529342253
5Noah GregorSan Jose (S J)LW/RW821744618520109120267842186.37%12171720.94513187528801172886149.07%16100000.7111000213
6Alexey MarchenkoSan Jose (S J)D8216395532471550861475212010.88%129189923.174913732881232241110.00%000000.5800102212
7Leo KomarovSan Jose (S J)LW/RW822325481810013562045213211.27%16124415.18459259510171693151.71%20500100.7700000023
8Jake WalmanSan Jose (S J)D82103646286801547213651857.35%111189123.077916712840003238110.00%000000.4900000142
9Jesper BrattSan JoseLW/RW52202545-1402286234531678.55%395018.28471163182000041549.37%7900000.9501000234
10Nathan BastianSan Jose (S J)RW8219264524771512161199501549.55%7113413.832022398000003352.85%12300000.7906102115
11Adam McQuaid San Jose (S J)D8210304017130101536587185411.49%116146717.8954919750002200100.00%000000.5500011133
12Freddie HamiltonSan Jose (S J)C/LW/RW82142438142805089143331179.79%995611.66011313000053048.65%111400000.7900000211
13David SchlemkoSan Jose (S J)D82151934-95406361127247811.81%105163719.976612642440110115200.00%000000.4200000031
14Michael SauerSan Jose (S J)D8242529-6771596557219505.56%144160919.6303316770001242010.00%000000.3600201111
15Justin BraunSan Jose (S J)D8242428191002828707325.71%95128215.64000116000144100.00%000000.4400000011
16Justin FontaineSan Jose (S J)RW8261622-102045910641925.66%182910.110000800011190045.38%11900000.5300000110
17Michael BlundenSan Jose (S J)C/RW8281119-1527596668330679.64%36608.0500000000000044.53%78600000.5800000102
18Dustin BoydSan Jose (S J)C/LW/RW829413-52072271194512.68%16938.4500000000001052.38%6300000.3800000100
19Drew ShoreSan Jose (S J)C11325540819233713.04%112511.4100003000050066.89%15100000.8000000011
20Robert NilssonSan Jose (S J)LW/RW17213-720041421114.29%01468.5900000000020085.71%700000.4100000000
Statistiques d’équipe totales ou en moyenne1473303524827201847115137914853004853215010.09%8182410516.36631181816722718459392150432351.46%783300320.69826858374141
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
1Anton KhudobinSan Jose (S J)44251440.9013.2526370214314410100.833184438501
2Jakob MarkstromSan Jose (S J)39241140.9112.9823342211613030000.88993844441
Statistiques d’équipe totales ou en moyenne83492580.9063.134972242592744010278282942


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Adam McQuaid San Jose (S J)D341986-10-12 07:23:38No216 Lbs6 ft4NoNoNoNo1Pro & Farm900,000$0$0$NoLien
Alexey MarchenkoSan Jose (S J)D291992-01-02No217 Lbs6 ft3NoNoNoNo3Pro & Farm950,000$0$0$No950,000$950,000$Lien
Anton KhudobinSan Jose (S J)G351986-05-07 10:44:53No215 Lbs5 ft11NoNoNoNo1Pro & Farm975,000$0$0$NoLien
Beau BennettSan Jose (S J)LW/RW291991-11-27No200 Lbs6 ft2NoNoNoNo2Pro & Farm900,000$0$0$No900,000$Lien
David SchlemkoSan Jose (S J)D341987-05-07No191 Lbs6 ft1NoNoNoNo1Pro & Farm950,000$0$0$No
Drew ShoreSan Jose (S J)C301991-01-29No212 Lbs6 ft3NoNoNoNo1Pro & Farm500,000$0$0$NoLien
Dustin BoydSan Jose (S J)C/LW/RW351985-07-16No208 Lbs6 ft0NoNoNoNo1Pro & Farm850,000$0$0$No
Freddie HamiltonSan Jose (S J)C/LW/RW291992-01-01No200 Lbs6 ft1NoNoNoNo1Pro & Farm800,000$0$0$NoLien
Jake WalmanSan Jose (S J)D251996-02-20 04:16:40Yes210 Lbs6 ft1NoNoNoNo1Pro & Farm500,000$0$0$NoLien
Jakob MarkstromSan Jose (S J)G311990-01-31 11:57:02No212 Lbs6 ft6NoNoNoNo2Pro & Farm975,000$0$0$No975,000$Lien
Justin BraunSan Jose (S J)D331987-09-01No204 Lbs6 ft2NoNoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Justin FontaineSan Jose (S J)RW331987-11-06No178 Lbs5 ft10NoNoNoNo2Pro & Farm800,000$0$0$No800,000$Lien
Leo KomarovSan Jose (S J)LW/RW341987-01-23No203 Lbs5 ft11NoNoNoNo1Pro & Farm850,000$0$0$NoLien
Luke GlendeningSan Jose (S J)C/RW321989-04-28 11:45:39No190 Lbs5 ft11NoNoNoNo1Pro & Farm975,000$0$0$NoLien
Michael BlundenSan Jose (S J)C/RW341986-12-15No222 Lbs6 ft3NoNoNoNo1Pro & Farm850,000$0$0$No
Michael PezzettaSan Jose (S J)LW/RW231998-03-13 07:54:14Yes210 Lbs6 ft1NoNoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Michael SauerSan Jose (S J)D331987-08-07No222 Lbs6 ft3NoNoNoNo1Pro & Farm1,200,000$0$0$NoLien
Nathan BastianSan Jose (S J)RW231997-12-06 04:11:27Yes205 Lbs6 ft4NoNoNoNo2Pro & Farm900,000$0$0$No900,000$Lien
Noah GregorSan Jose (S J)LW/RW221998-07-28 04:21:11Yes185 Lbs6 ft0NoNoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Parker KellySan Jose (S J)C/LW221999-05-14 07:56:22Yes190 Lbs6 ft0NoNoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Robert NilssonSan Jose (S J)LW/RW361985-01-10No196 Lbs5 ft11NoNoNoNo1Pro & Farm700,000$0$0$No
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2130.29204 Lbs6 ft11.57789,286$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Beau BennettLuke GlendeningMichael Pezzetta34023
2Noah GregorParker KellyNathan Bastian32005
3Leo KomarovDrew ShoreFreddie Hamilton24014
4Dustin BoydMichael BlundenJustin Fontaine10023
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanAlexey Marchenko36014
2Michael SauerDavid Schlemko34023
3Justin BraunAdam McQuaid 30023
4Jake WalmanAlexey Marchenko0005
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Noah GregorLuke GlendeningNathan Bastian60005
2Beau BennettParker KellyMichael Pezzetta40005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexey MarchenkoJake Walman60014
2Leo KomarovDavid Schlemko40014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Parker KellyNoah Gregor60140
2Leo KomarovJustin Fontaine40140
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanMichael Sauer60140
2Alexey MarchenkoAdam McQuaid 40140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Noah Gregor60140Alexey MarchenkoJake Walman60140
2Parker Kelly40140Michael SauerDavid Schlemko40140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Leo KomarovBeau Bennett60014
2Parker KellyNoah Gregor40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexey MarchenkoJake Walman60023
2Michael SauerDavid Schlemko40023
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Parker KellyLuke GlendeningBeau BennettJake WalmanAlexey Marchenko
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Parker KellyLuke GlendeningNoah GregorJake WalmanAlexey Marchenko
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nathan Bastian, Leo Komarov, Justin FontaineParker Kelly, Leo KomarovJustin Fontaine
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Michael Sauer, Adam McQuaid , David SchlemkoMichael SauerDavid Schlemko, Justin Braun
Tirs de pénalité
Michael Pezzetta, Beau Bennett, Nathan Bastian, Drew Shore, Noah Gregor
Gardien
#1 : Jakob Markstrom, #2 : Anton Khudobin


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
1Abbotsford63201000282263210000016106311010001212080.66728467401105112811322497098310146318847619629413.79%23673.91%11721325752.84%1584311550.85%729136153.56%1946131919496221084541
2Bakersfield6220011020191311000101082311001001011-170.58320335300105112811320297098310146319061819424520.83%32487.50%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
3Charlotte2010000157-21010000023-11000000134-110.250591400105112811386970983101463602218311119.09%9188.89%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
4Cleveland2020000026-41010000013-21010000013-200.0002240010511281136397098310146373244633200.00%10280.00%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
5Grand Rapids21100000880110000005321010000035-220.5008142200105112811394970983101463722014298225.00%6183.33%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
6Hartford3200001017891100000075221000010103761.00017304701105112811398970983101463115332745900.00%11190.91%11721325752.84%1584311550.85%729136153.56%1946131919496221084541
7Hershey32100000121201100000052321100000710-340.6671223350010511281131299709831014638824294612541.67%11281.82%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
8Iowa42200000181622020000069-322000000127540.50018335100105112811313597098310146314331338113538.46%13561.54%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
9Laval210000101293100000105411100000075241.00012172900105112811361970983101463692330425240.00%10370.00%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
10Lehigh Valley20000110880100000105411000010034-130.7508111900105112811368970983101463923432335120.00%70100.00%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
11Manitoba4300100017125220000008622100100096381.00017324900105112811315697098310146311328246120525.00%11372.73%11721325752.84%1584311550.85%729136153.56%1946131919496221084541
12Milwaukee514000001218-630300000915-62110000033020.20012193100105112811320697098310146316848368324520.83%18572.22%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
13Ontario6320100025196321000001311231101000128480.667254469011051128113220970983101463233586810021314.29%28485.71%11721325752.84%1584311550.85%729136153.56%1946131919496221084541
14Providence21000001761110000004221000000134-130.7507101700105112811372970983101463701823271218.33%8187.50%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
15Rochester21100000550110000002111010000034-120.5005813001051128113729709831014635616163715213.33%7271.43%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
16Rockford4200002021101121000010115621000010105581.00021325300105112811315497098310146313032476417529.41%16193.75%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
17San Diego613001011824-630200001511-6311001001313040.333183149001051128113207970983101463245826313220210.00%21576.19%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
18Springfield5310010013121321000007612100010066070.7001324370010511281131629709831014631653758831516.67%22290.91%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
19Texas431000001394211000006512200000074360.75013223500105112811311997098310146311536346517317.65%11190.91%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
20Toronto220000001138110000005321100000060641.0001117280110511281131049709831014635721103515533.33%4175.00%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
21Tucson6300210023167310011001183320010001284110.91723406300105112811322697098310146317171589726311.54%25676.00%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
22Utica21100000761110000003121010000045-120.5007132000105112811375970983101463642618307114.29%9277.78%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
23Wilkes-Barre/Scranton211000007701010000024-21100000053220.50071421001051128113719709831014636726233510220.00%8275.00%01721325752.84%1584311550.85%729136153.56%1946131919496221084541
Total8238250556330926247411915011411481291941191004422161133281060.6463095248330410511281133004970983101463274481884913793376318.69%3206081.25%41721325752.84%1584311550.85%729136153.56%1946131919496221084541
_Since Last GM Reset8238250556330926247411915011411481291941191004422161133281060.6463095248330410511281133004970983101463274481884913793376318.69%3206081.25%41721325752.84%1584311550.85%729136153.56%1946131919496221084541
_Vs Conference56261705431208177312912120112110294827145043101068323730.652208356564021051128113201197098310146318615315639562264118.14%2204280.91%31721325752.84%1584311550.85%729136153.56%1946131919496221084541
_Vs Division3012904311114100141565011115548715640320059527380.633114194308021051128113107997098310146310273193315191201714.17%1292580.62%21721325752.84%1584311550.85%729136153.56%1946131919496221084541

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82106W230952483330042744818849137904
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8238255563309262
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4119151141148129
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4119104422161133
Derniers 10 matchs
WLOTWOTL SOWSOL
810100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3376318.69%3206081.25%4
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
9709831014631051128113
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
1721325752.84%1584311550.85%729136153.56%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1946131919496221084541


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
2 - 2022-11-259Springfield4San Jose2BLSommaire du match
6 - 2022-11-2726Bakersfield3San Jose4BWXXSommaire du match
10 - 2022-11-2948Ontario4San Jose3BLSommaire du match
11 - 2022-11-3056San Jose4Abbotsford3AWXSommaire du match
15 - 2022-12-0273San Jose4Tucson3AWXSommaire du match
16 - 2022-12-0279San Diego6San Jose2BLSommaire du match
18 - 2022-12-0396Abbotsford6San Jose8BWSommaire du match
21 - 2022-12-05110San Jose3Ontario6ALSommaire du match
23 - 2022-12-06122San Jose4Tucson2AWSommaire du match
24 - 2022-12-06125Milwaukee6San Jose5BLSommaire du match
26 - 2022-12-07142San Jose4Bakersfield3AWSommaire du match
28 - 2022-12-08150Tucson2San Jose3BWXSommaire du match
33 - 2022-12-11170Tucson4San Jose3BLXSommaire du match
35 - 2022-12-12185San Jose6San Diego4AWSommaire du match
37 - 2022-12-13192San Jose2Bakersfield3ALSommaire du match
38 - 2022-12-13199Cleveland3San Jose1BLSommaire du match
40 - 2022-12-14215Toronto3San Jose5BWSommaire du match
44 - 2022-12-16233San Jose3Manitoba2AWXSommaire du match
46 - 2022-12-17241San Jose8Iowa5AWSommaire du match
47 - 2022-12-18247Charlotte3San Jose2BLSommaire du match
49 - 2022-12-19265Texas2San Jose1BLSommaire du match
53 - 2022-12-21282San Jose3Grand Rapids5ALSommaire du match
54 - 2022-12-21291Grand Rapids3San Jose5BWSommaire du match
57 - 2022-12-23309San Jose2Springfield3ALXSommaire du match
58 - 2022-12-23314Utica1San Jose3BWSommaire du match
61 - 2022-12-25331San Jose4Hartford3AWXXSommaire du match
63 - 2022-12-26339Hartford5San Jose7BWSommaire du match
67 - 2022-12-28362Rochester1San Jose2BWSommaire du match
69 - 2022-12-29368San Jose4Rockford3AWXXSommaire du match
72 - 2022-12-30385Milwaukee4San Jose3BLSommaire du match
75 - 2023-01-01398San Jose4San Diego5ALXSommaire du match
77 - 2023-01-02409Providence2San Jose4BWSommaire du match
79 - 2023-01-03418San Jose6Toronto0AWSommaire du match
81 - 2023-01-04430San Jose3Charlotte4ALXXSommaire du match
82 - 2023-01-04437Bakersfield2San Jose1BLSommaire du match
86 - 2023-01-06454San Jose1Cleveland3ALSommaire du match
87 - 2023-01-07461Abbotsford4San Jose2BLSommaire du match
90 - 2023-01-08480San Jose6Hartford0AWSommaire du match
91 - 2023-01-09483Ontario4San Jose5BWSommaire du match
94 - 2023-01-10495San Jose6Rockford2AWSommaire du match
96 - 2023-01-11503San Jose4Bakersfield5ALXSommaire du match
97 - 2023-01-12512Ontario3San Jose5BWSommaire du match
100 - 2023-01-13532Abbotsford0San Jose6BWSommaire du match
102 - 2023-01-14545San Jose6Ontario0AWSommaire du match
105 - 2023-01-16556Texas3San Jose5BWSommaire du match
107 - 2023-01-17566San Jose3Rochester4ALSommaire du match
110 - 2023-01-18579Wilkes-Barre/Scranton4San Jose2BLSommaire du match
114 - 2023-01-20598San Jose4Springfield3AWSommaire du match
115 - 2023-01-21604Manitoba3San Jose4BWSommaire du match
121 - 2023-01-24628Rockford4San Jose5BWXXSommaire du match
124 - 2023-01-25642San Jose3Ontario2AWXSommaire du match
125 - 2023-01-26652Manitoba3San Jose4BWSommaire du match
128 - 2023-01-27671Iowa6San Jose5BLSommaire du match
129 - 2023-01-28673San Jose6Manitoba4AWSommaire du match
131 - 2023-01-29680San Jose3Providence4ALXXSommaire du match
134 - 2023-01-30697Iowa3San Jose1BLSommaire du match
136 - 2023-01-31705San Jose4Iowa2AWSommaire du match
138 - 2023-02-01719San Jose4Hershey2AWSommaire du match
140 - 2023-02-02725Rockford1San Jose6BWSommaire du match
142 - 2023-02-03740San Jose1Milwaukee2ALSommaire du match
144 - 2023-02-04746San Jose7Laval5AWSommaire du match
145 - 2023-02-05754Milwaukee5San Jose1BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
148 - 2023-02-06771San Jose4Utica5ALSommaire du match
149 - 2023-02-07777Bakersfield3San Jose5BWSommaire du match
155 - 2023-02-10799Hershey2San Jose5BWSommaire du match
158 - 2023-02-11819Laval4San Jose5BWXXSommaire du match
159 - 2023-02-12828San Jose2Abbotsford6ALSommaire du match
162 - 2023-02-13841San Jose3Hershey8ALSommaire du match
163 - 2023-02-14842San Jose4Tucson3AWSommaire du match
164 - 2023-02-14850Springfield1San Jose2BWSommaire du match
167 - 2023-02-16870San Diego3San Jose2BLXXSommaire du match
172 - 2023-02-18890San Diego2San Jose1BLSommaire du match
174 - 2023-02-19894San Jose3Lehigh Valley4ALXSommaire du match
176 - 2023-02-20905San Jose5Wilkes-Barre/Scranton3AWSommaire du match
178 - 2023-02-21915Lehigh Valley4San Jose5BWXXSommaire du match
182 - 2023-02-23926San Jose6Abbotsford3AWSommaire du match
184 - 2023-02-24937Springfield1San Jose3BWSommaire du match
188 - 2023-02-26951San Jose5Texas3AWSommaire du match
190 - 2023-02-27959San Jose2Milwaukee1AWSommaire du match
191 - 2023-02-28962San Jose3San Diego4ALSommaire du match
194 - 2023-03-01972Tucson2San Jose5BWSommaire du match
195 - 2023-03-02975San Jose2Texas1AWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance62,27131,204
Assistance PCT75.94%76.11%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2280 - 76.00% 133,343$5,467,056$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,813,054$ 1,657,500$ 1,657,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,371$ 1,663,070$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 14,179$ 0$




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
1Michael Frolik146487812612481381544869.88%16316221.66143044132426126247.6500.8006
2Matt Nieto1644874122-1656822225269.13%14310418.93122436108022140044.2400.7922
3Ian McCoshen1602884112-102302521703109.03%282398524.911420341520224400.00%00.5600
4Eric Staal11040661061413821826633611.90%18260523.691016266602246653.4940.8124
5Wayne Simmonds1564858106-162743881645049.52%26286718.381416309600088236.3600.7400

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
1Karri Ramo58243000.8923.6430684018617180221.00010
2Eric Comrie72243080.9003.64389516023623600000.00%0
3Cam Talbot50222240.9192.9128910214017200420.6676

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
Saison régulière
2082294104521256286-3041181702211125132-741112402310131154-2376256447703218873897264584187291229290786796015873125818.59%4057780.99%51486304748.77%1534334645.85%631132247.73%1839121320476451066519
2082294104521256286-3041181702211125132-741112402310131154-2376256447703218873897264584187291229290786796015873125818.59%4057780.99%51486304748.77%1534334645.85%631132247.73%1839121320476451066519
Total Saison régulière16476500101012661852494823830022822962583882382008844322266562126181048166608210224162266008194019662028126548816361698275867412618.69%64012081.25%83442651452.84%3168623050.85%1458272253.56%389326393898124521691082
Séries éliminatoires
Total Séries éliminatoires00000000000000.00%0.00%0.00%0.00%0.00%000000

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