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San Diego
GP: 37 | W: 21 | L: 12 | OTL: 4 | P: 46
GF: 118 | GA: 104 | PP%: 22.15% | PK%: 79.55%
DG: Michael Chouinard | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #446 vs San Jose

Centre de jeu
Lehigh Valley
19-11-2, 40pts
5
FINAL
2 San Diego
21-12-4, 46pts
Team Stats
L1SéquenceL2
10-6-2Fiche domicile10-4-3
9-5-0Fiche domicile11-8-1
8-2-0Derniers 10 matchs5-5-0
3.63Buts par match 3.19
3.03Buts contre par match 2.81
19.23%Pourcentage en avantage numérique22.15%
77.68%Pourcentage en désavantage numérique79.55%
San Diego
21-12-4, 46pts
2
FINAL
3 Ontario
22-12-1, 45pts
Team Stats
L2SéquenceW4
10-4-3Fiche domicile13-5-0
11-8-1Fiche domicile9-7-1
5-5-0Derniers 10 matchs7-3-0
3.19Buts par match 3.86
2.81Buts contre par match 3.09
22.15%Pourcentage en avantage numérique26.95%
79.55%Pourcentage en désavantage numérique85.09%
San Jose
18-13-4, 40pts
Jour 86
San Diego
21-12-4, 46pts
Statistiques d’équipe
L2SéquenceL2
9-7-2Fiche domicile10-4-3
9-6-2Fiche visiteur11-8-1
6-4-010 derniers matchs5-5-0
3.37Buts par match 3.19
3.43Buts contre par match 3.19
21.01%Pourcentage en avantage numérique22.15%
77.17%Pourcentage en désavantage numérique79.55%
San Diego
21-12-4, 46pts
Jour 87
Grand Rapids
20-14-1, 41pts
Statistiques d’équipe
L2SéquenceL1
10-4-3Fiche domicile10-6-1
11-8-1Fiche visiteur10-8-0
5-5-010 derniers matchs6-4-0
3.19Buts par match 3.31
2.81Buts contre par match 3.31
22.15%Pourcentage en avantage numérique23.13%
79.55%Pourcentage en désavantage numérique83.33%
Grand Rapids
20-14-1, 41pts
Jour 90
San Diego
21-12-4, 46pts
Statistiques d’équipe
L1SéquenceL2
10-6-1Fiche domicile10-4-3
10-8-0Fiche visiteur11-8-1
6-4-010 derniers matchs5-5-0
3.31Buts par match 3.19
3.09Buts contre par match 3.19
23.13%Pourcentage en avantage numérique22.15%
83.33%Pourcentage en désavantage numérique79.55%
Meneurs d'équipe
Buts
Peyton Krebs
16
Passes
Matt Dumba
26
Points
Matt Dumba
35
Plus/Moins
Caleb Jones
10
Calvin PickardVictoires
Calvin Pickard
16
Casey DeSmithPourcentage d’arrêts
Casey DeSmith
0.943

Statistiques d’équipe
Buts pour
118
3.19 GFG
Tirs pour
1331
35.97 Avg
Pourcentage en avantage numérique
22.2%
35 GF
Début de zone offensive
43.4%
Buts contre
104
2.81 GAA
Tirs contre
1251
33.81 Avg
Pourcentage en désavantage numérique
79.5%%
27 GA
Début de la zone défensive
39.8%
Informations de l'équipe

Directeur généralMichael Chouinard
EntraîneurJared Bednar
DivisionPacifique
ConférenceConference ouest
CapitaineAdam Henrique
Assistant #1Mikko Lehtonen
Assistant #2Joe Colborne


Informations de l’aréna

Capacité3,000
Assistance2,201
Billets de saison300


Informations de la formation

Équipe Pro24
Équipe Mineure18
Limite contact 42 / 50
Espoirs60


Historique d'équipe

Saison actuelle21-12-4 (46PTS)
Historique70-41-10 (0.579%)
Apparitions en séries éliminatoires 3
Historique en séries éliminatoires (W-L)20 - 18 (0.526%)
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
1Karson KulhmanXX100.00693092787976997171677172765958445000282900,000$
2Jakob SilfverbergXX100.00663393717380867563727370827259325000332550,000$
3Adam Henrique (C)XX100.00673687637585887089677163847880315000342951,000$
4Joe Colborne (A)XXX100.00673780638476886599676759796867385000342956,000$
5Chris TierneyXX100.006925997584879969976669678157454950003031,100,000$
6Brayden SchennXXX100.008449787576787974736976728172613650003212,000,000$
7Sam LaffertyXXX100.00823474778180867191727073756055495000291950,000$
8Jansen HarkinsXX100.00672990828374916873687064775250545000273875,000$
9Michael BuntingXX100.00823185798084906568636863736052585000282825,000$
10Vladislav NamestnikovXXX100.006530978470879971796868637955505250003111,160,000$
11Peyton Krebs (R)XXX100.00865583818079997185727366704242735000232900,000$
12Gage Goncalves (R)XX100.00783594787978997070697165704242695000232500,000$
13Nikolai Kovalenko (R)XX100.00813092797879917070717065704545695000242500,000$
14Matt DumbaX100.007437759693909971536560808161535850002931,760,000$
15Mikko Lehtonen (A)X100.00712778788280836550555089766457435000304990,000$
16Caleb JonesX100.00762977798491995753575587795453615000271925,000$
17Nick Blankenburg (R)X100.00753093827584935150525292705252695000261500,000$
18Jacob Bernard-Docker (R)X100.00714090698177894650464789704545685000242800,000$
19Tobias Bjornfot (R)X100.00703096788378994050404087704242595000232900,000$
Rayé
1Steven LorentzXX100.00662991769875906590656564775644525000282956,000$
2Joakim NygardX100.00652191757673826270636461756761355000312825,000$
3Brendan SmithX100.00713271638674915450514588757764315000352725,000$
MOYENNE D’ÉQUIPE100.0073338776818092657063637376585451500
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
1Calvin Pickard100.00689088787787888787857575755350003231,000,000$
2Casey DeSmith97.0068838574748687878781736868535000322961,000$
Rayé
MOYENNE D’ÉQUIPE98.506887877676878887878374727253500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jared Bednar82879692898981CAN5222,510,000$


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
1Matt DumbaSan Diego (ANA)D37926359535423190317110.00%3578321.195101543135000023100%000000.8902100023
2Sam LaffertySan Diego (ANA)C/LW/RW37724312355677211630816.03%873119.7628102512700021001255.25%105700000.8500010322
3Nikolai KovalenkoSan Diego (ANA)LW/RW3710192911604742122331008.20%472519.62281023133000013144.12%6800000.8000000201
4Caleb JonesSan Diego (ANA)D377202710320293056233912.50%5386223.315611291370001103120%000000.6300000121
5Chris TierneySan Diego (ANA)C/LW3762026610027698023807.50%757115.44099201310000102056.12%83400000.9102000032
6Peyton KrebsSan Diego (ANA)C/LW/RW37161026240107055129358912.40%370319.0044828132000001052.84%75700000.7400101230
7Karson KulhmanSan Diego (ANA)LW/RW37101424-140174710548859.52%671619.383811241280006971138.78%4900100.6700000121
8Mikko LehtonenSan Diego (ANA)D37915247340515274195412.16%8185923.224610311280000100200%000000.5600000121
9Brayden SchennSan Diego (ANA)C/LW/RW2661218021547258933776.74%850519.43551027990002622050.89%16900000.7112100212
10Vladislav NamestnikovSan Diego (ANA)C/LW/RW3731417104018327916693.80%853514.480003900021081046.15%5200000.6312000101
11Adam HenriqueSan Diego (ANA)C/LW3783114135341563153912.70%347512.84000221000023147.62%4200000.4602001011
12Nick BlankenburgSan Diego (ANA)D25381154021234223277.14%2451720.700222395000265100%000000.4300000001
13Gage GoncalvesSan Diego (ANA)C/LW36551038022246316627.94%560016.68000010000220041.67%7200000.3300000000
14Jansen HarkinsSan Diego (ANA)LW/RW37459-420995510337.27%12416.5300000000000052.17%2300000.7512000101
15Jakob SilfverbergSan Diego (ANA)LW/RW7527655372161023.81%011216.09202316000000038.89%1800011.2400001100
16Tobias BjornfotSan Diego (ANA)D37145-71402229278193.70%3451013.7900001000016000%000000.2000000000
17Joe ColborneSan Diego (ANA)C/LW/RW37224-2751219269217.69%12566.94000000000240060.53%30400000.3102100010
18Jacob Bernard-DockerSan Diego (ANA)D37224-1228103719285197.14%5769618.84101210000093100%000000.1100011010
19Brendan SmithSan Diego (ANA)D712324072102310.00%1812618.12101615000012000%000000.4700000000
20Michael BuntingSan Diego (ANA)LW/RW37213-5602217388275.26%12135.7700000000000062.50%2400000.2800000001
21Cal FooteAnaheimD41231401177414.29%87919.8810128000012000%000000.7500000001
22Steven LorentzSan Diego (ANA)C/LW5000000228150%2377.5800000000000050.00%40000000000000
23Joakim NygardSan Diego (ANA)LW2000000203100%0147.48000000000000100.00%10000000000000
Statistiques d’équipe totales ou en moyenne6671172103273734450609622133140210148.79%3671087816.31356610129113350001585820754.17%347400110.60314424152019
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
1Calvin PickardSan Diego (ANA)31161040.9132.901839238910200010.78614316511
2Casey DeSmithSan Diego (ANA)75200.9431.98395011323000000629211
Statistiques d’équipe totales ou en moyenne38211240.9182.742235241021250001143735722


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 Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer 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
Adam HenriqueSan Diego (ANA)C/LW341990-02-06CANNo199 Lbs6 ft0NoNoFree AgentNoNo22025-09-23FalseFalsePro & Farm951,000$541,338$0$0$No951,000$--------951,000$--------No--------Lien / Lien NHL
Brayden Schenn (contrat à 1 volet)San Diego (ANA)C/LW/RW321991-08-22CANNo198 Lbs6 ft1NoNoTrade2025-09-12YesYes12025-09-12FalseFalsePro & Farm2,000,000$1,160,000$20,000$11,600$No---------------------------Lien / Lien NHL
Brendan SmithSan Diego (ANA)D351989-02-08CANNo216 Lbs6 ft2NoNoN/ANoNo22025-09-11FalseFalsePro & Farm725,000$412,692$0$0$No725,000$--------725,000$--------No--------Lien / Lien NHL
Caleb JonesSan Diego (ANA)D271997-06-06USANo194 Lbs6 ft1NoNoN/ANoNo12024-09-15FalseFalsePro & Farm925,000$526,538$0$0$No---------------------------
Calvin PickardSan Diego (ANA)G321992-04-15CANNo205 Lbs6 ft1NoNoFree AgentNoNo32025-09-21FalseFalsePro & Farm1,000,000$569,231$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien / Lien NHL
Casey DeSmithSan Diego (ANA)G321991-08-13USANo186 Lbs6 ft0NoNoFree AgentNoNo22024-09-24FalseFalsePro & Farm961,000$547,031$0$0$No961,000$--------961,000$--------No--------Lien / Lien NHL
Chris TierneySan Diego (ANA)C/LW301994-07-01CANNo201 Lbs6 ft1NoNoFree Agent2024-09-14NoNo32025-09-21FalseFalsePro & Farm1,100,000$626,154$0$0$No1,100,000$1,100,000$-------1,100,000$1,100,000$-------NoNo-------Lien / Lien NHL
Gage GoncalvesSan Diego (ANA)C/LW232001-01-16CANYes181 Lbs6 ft0NoNoProspectNoNo22025-10-16FalseFalsePro & Farm500,000$284,615$0$0$No500,000$--------500,000$--------No--------
Jacob Bernard-DockerSan Diego (ANA)D242000-06-30CANYes177 Lbs5 ft9NoNoProspectNoNo22025-10-17FalseFalsePro & Farm800,000$455,385$0$0$No800,000$--------800,000$--------No--------
Jakob SilfverbergSan Diego (ANA)LW/RW331990-10-13SWENo210 Lbs6 ft1NoNoFree AgentNoNo22024-11-01FalseFalsePro & Farm550,000$313,077$0$0$No550,000$--------550,000$--------No--------Lien / Lien NHL
Jansen HarkinsSan Diego (ANA)LW/RW271997-05-23USANo182 Lbs6 ft1NoNoTrade2024-11-07NoNo32025-09-09FalseFalsePro & Farm875,000$498,077$0$0$No875,000$875,000$-------875,000$875,000$-------NoNo-------Lien
Joakim NygardSan Diego (ANA)LW311993-01-08SWENo180 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm825,000$469,615$0$0$No825,000$--------825,000$--------No--------Lien
Joe ColborneSan Diego (ANA)C/LW/RW341990-01-30CANNo218 Lbs6 ft5NoNoFree AgentNoNo22025-09-30FalseFalsePro & Farm956,000$544,185$0$0$No956,000$--------956,000$--------No--------Lien
Karson KulhmanSan Diego (ANA)LW/RW281995-10-26USANo184 Lbs5 ft11NoNoN/ANoNo22024-09-15FalseFalsePro & Farm900,000$512,308$0$0$No900,000$--------900,000$--------No--------
Matt DumbaSan Diego (ANA)D291994-07-25CANNo199 Lbs6 ft0NoNoFree AgentNoNo32025-09-30FalseFalsePro & Farm1,760,000$1,001,846$0$0$No1,760,000$1,760,000$-------1,760,000$1,760,000$-------NoNo-------Lien
Michael BuntingSan Diego (ANA)LW/RW281995-09-17CANNo197 Lbs5 ft11NoNoTrade2025-01-04NoNo22025-09-09FalseFalsePro & Farm825,000$469,615$0$0$No825,000$--------825,000$--------No--------Lien / Lien NHL
Mikko LehtonenSan Diego (ANA)D301994-01-16FINNo196 Lbs6 ft0NoNoN/ANoNo42025-09-09FalseFalsePro & Farm990,000$563,538$0$0$No990,000$990,000$990,000$------990,000$990,000$990,000$------NoNoNo------Lien
Nick BlankenburgSan Diego (ANA)D261998-05-12USAYes177 Lbs5 ft9NoNoProspectNoNo12025-10-17FalseFalsePro & Farm500,000$284,615$0$0$No---------------------------
Nikolai KovalenkoSan Diego (ANA)LW/RW241999-10-17USAYes180 Lbs5 ft10NoNoProspectNoNo22025-10-16FalseFalsePro & Farm500,000$284,615$0$0$No500,000$--------500,000$--------No--------
Peyton KrebsSan Diego (ANA)C/LW/RW232001-01-26NAYes187 Lbs6 ft0NoNoProspectNoNo22025-10-16FalseFalsePro & Farm900,000$512,308$0$0$No900,000$--------900,000$--------No--------
Sam LaffertySan Diego (ANA)C/LW/RW291995-03-06USANo198 Lbs6 ft1NoNoN/ANoNo12024-09-15FalseFalsePro & Farm950,000$540,769$0$0$No---------------------------Lien / Lien NHL
Steven LorentzSan Diego (ANA)C/LW281996-04-13CANNo208 Lbs6 ft4NoNoFree Agent2025-08-19NoNo22025-09-30FalseFalsePro & Farm956,000$544,185$0$0$No956,000$--------956,000$--------No--------Lien / Lien NHL
Tobias BjornfotSan Diego (ANA)D232001-04-06SWEYes200 Lbs6 ft0NoNoProspectNoNo22025-10-17FalseFalsePro & Farm900,000$512,308$0$0$No900,000$--------900,000$--------No--------
Vladislav NamestnikovSan Diego (ANA)C/LW/RW311992-11-22RUSNo188 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,160,000$660,308$0$0$No---------------------------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2428.88194 Lbs6 ft02.04937,875$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nikolai KovalenkoPeyton KrebsGage Goncalves35014
2Jakob SilfverbergSam LaffertyKarson Kulhman30014
3Adam HenriqueChris TierneyBrayden Schenn25122
4Jansen HarkinsJoe ColborneVladislav Namestnikov10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Matt DumbaCaleb Jones35023
2Mikko LehtonenNick Blankenburg30023
3Tobias BjornfotJacob Bernard-Docker25023
4Mikko LehtonenJacob Bernard-Docker10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Peyton KrebsSam LaffertyNikolai Kovalenko50014
2Jakob SilfverbergChris TierneyBrayden Schenn50014
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mikko LehtonenNick Blankenburg50014
2Caleb JonesMatt Dumba50014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Joe ColborneKarson Kulhman50122
2Sam LaffertyVladislav Namestnikov50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nick BlankenburgMikko Lehtonen50122
2Caleb JonesJacob Bernard-Docker50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Sam Lafferty50122Caleb JonesJacob Bernard-Docker50122
2Joe Colborne50122Tobias BjornfotNick Blankenburg50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jakob SilfverbergMichael Bunting50122
2Joe ColborneGage Goncalves50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tobias BjornfotMikko Lehtonen50122
2Caleb JonesJacob Bernard-Docker50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nikolai KovalenkoSam LaffertyJakob SilfverbergMikko LehtonenMatt Dumba
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Adam HenriqueSam LaffertyKarson KulhmanMikko LehtonenNick Blankenburg
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nikolai Kovalenko, Gage Goncalves, Peyton KrebsVladislav Namestnikov, Adam HenriqueGage Goncalves
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Mikko Lehtonen, Jacob Bernard-Docker, Matt DumbaNick BlankenburgMikko Lehtonen, Caleb Jones
Tirs de pénalité
Adam Henrique, Chris Tierney, Jansen Harkins, Joe Colborne, Vladislav Namestnikov
Gardien
#1 : Casey DeSmith, #2 : Calvin Pickard, #3 : 0
Lignes d’attaque personnalisées en prolongation
Sam Lafferty, Nikolai Kovalenko, Chris Tierney, Gage Goncalves, Adam Henrique, Jakob Silfverberg, Peyton Krebs, Karson Kulhman, Joe Colborne, Michael Bunting
Lignes de défense personnalisées en prolongation
Mikko Lehtonen, Matt Dumba, Nick Blankenburg, Tobias Bjornfot, Jacob Bernard-Docker


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
1Abbotsford3300000016881100000063322000000105561.000163046005229354114453419442319421224211654.55%11372.73%0814149354.52%738136853.95%33157657.47%928640834274478246
2Bridgeport1000010034-11000010034-10000000000010.50035800522935437453419442313110619200.00%10100.00%0814149354.52%738136853.95%33157657.47%928640834274478246
3Charlotte21000100743210001007430000000000030.75071017015229354834534194423159206279222.22%3166.67%0814149354.52%738136853.95%33157657.47%928640834274478246
4Cleveland11000000523110000005230000000000021.00051015005229354454534194423130156166116.67%30100.00%0814149354.52%738136853.95%33157657.47%928640834274478246
5Coachella Valley2110000046-2110000003121010000015-420.500471100522935465453419442318892033700.00%10280.00%0814149354.52%738136853.95%33157657.47%928640834274478246
6Eagles4120100010912010100056-12110000053240.5001019291152293541384534194423114546398118422.22%15193.33%0814149354.52%738136853.95%33157657.47%928640834274478246
7Hershey210000014401000000123-11100000021130.7504711005229354674534194423167920299333.33%9188.89%0814149354.52%738136853.95%33157657.47%928640834274478246
8Iowa11000000321110000003210000000000021.000369005229354334534194423132131516400.00%40100.00%0814149354.52%738136853.95%33157657.47%928640834274478246
9Laval11000000321000000000001100000032121.000358005229354394534194423128106146116.67%3233.33%0814149354.52%738136853.95%33157657.47%928640834274478246
10Lehigh Valley2020000048-41010000025-31010000023-100.000481200522935474453419442317023233710330.00%8362.50%0814149354.52%738136853.95%33157657.47%928640834274478246
11Manitoba211000005501010000024-21100000031220.5005914005229354784534194423150144258112.50%2150.00%0814149354.52%738136853.95%33157657.47%928640834274478246
12Ontario21100000660110000004311010000023-120.500611170052293546845341944231771742369111.11%10280.00%0814149354.52%738136853.95%33157657.47%928640834274478246
13Providence22000000743110000005411100000020241.000713200152293546845341944231801918437114.29%8187.50%0814149354.52%738136853.95%33157657.47%928640834274478246
14Rochester2020000057-2000000000002020000057-200.000581300522935474453419442315817214015320.00%7271.43%0814149354.52%738136853.95%33157657.47%928640834274478246
15Rockford31100100660000000000003110010066030.5006101600522935499453419442318739394514321.43%12191.67%0814149354.52%738136853.95%33157657.47%928640834274478246
16San Jose11000000761000000000001100000076121.00071421005229354454534194423141912103266.67%6266.67%0814149354.52%738136853.95%33157657.47%928640834274478246
17Springfield11000000422000000000001100000042221.000471100522935432453419442313912811400.00%4175.00%0814149354.52%738136853.95%33157657.47%928640834274478246
18Syracuse10000010541100000105410000000000021.000561100522935450453419442314517624200.00%30100.00%0814149354.52%738136853.95%33157657.47%928640834274478246
19Texas21100000911-20000000000021100000911-220.500915240052293546845341944231661821298225.00%8362.50%0814149354.52%738136853.95%33157657.47%928640834274478246
20Wilkes-Barre/Scranton21100000541211000005410000000000020.500510150152293545445341944231642912326233.33%5180.00%0814149354.52%738136853.95%33157657.47%928640834274478246
Total371912013111181041417840121157498201180010061556460.62211821032814522935413314534194423112513673466091583522.15%1322779.55%0814149354.52%738136853.95%33157657.47%928640834274478246
_Since Last GM Reset371912013111181041417840121157498201180010061556460.62211821032814522935413314534194423112513673466091583522.15%1322779.55%0814149354.52%738136853.95%33157657.47%928640834274478246
_Vs Conference211270110070619742010002319414850010047425270.6437012819811522935474045341944231719198222328861922.09%821680.49%0814149354.52%738136853.95%33157657.47%928640834274478246
_Vs Division86200000332673300000013765320000020191120.75033629500522935429245341944231300569612130930.00%37975.68%0814149354.52%738136853.95%33157657.47%928640834274478246

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
3746L21182103281331125136734660914
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
3719121311118104
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
178412115749
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2011801006155
Derniers 10 matchs
WLOTWOTL SOWSOL
550000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1583522.15%1322779.55%0
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
453419442315229354
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
814149354.52%738136853.95%33157657.47%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
928640834274478246


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
16Eagles2San Diego3WXSommaire du match
419San Diego3Rochester4LSommaire du match
936San Diego4Abbotsford3WSommaire du match
1143Wilkes-Barre/Scranton0San Diego2WSommaire du match
1356Eagles4San Diego2LSommaire du match
1569San Diego3Texas6LSommaire du match
1671San Diego2Rockford3LXSommaire du match
2090Coachella Valley1San Diego3WSommaire du match
23106Iowa2San Diego3WSommaire du match
25115San Diego3Manitoba1WSommaire du match
26122San Diego4Rockford2WSommaire du match
29134San Diego6Texas5WSommaire du match
31145Ontario3San Diego4WSommaire du match
34163Manitoba4San Diego2LSommaire du match
36175San Diego2Rochester3LSommaire du match
38186San Diego2Eagles3LSommaire du match
40195Charlotte0San Diego4WSommaire du match
42206San Diego2Hershey1WSommaire du match
43218Charlotte4San Diego3LXSommaire du match
48236San Diego1Coachella Valley5LSommaire du match
50244Hershey3San Diego2LXXSommaire du match
52259San Diego2Providence0WSommaire du match
55271Bridgeport4San Diego3LXSommaire du match
57282San Diego6Abbotsford2WSommaire du match
59293Syracuse4San Diego5WXXSommaire du match
62310San Diego3Laval2WSommaire du match
63316Cleveland2San Diego5WSommaire du match
66327San Diego2Lehigh Valley3LSommaire du match
68336San Diego3Eagles0WSommaire du match
70347Providence4San Diego5WSommaire du match
72361San Diego7San Jose6WSommaire du match
74371San Diego0Rockford1LSommaire du match
75376Abbotsford3San Diego6WSommaire du match
77395Wilkes-Barre/Scranton4San Diego3LSommaire du match
79408San Diego4Springfield2WSommaire du match
82422Lehigh Valley5San Diego2LSommaire du match
83432San Diego2Ontario3LSommaire du match
86446San Jose-San Diego-
87458San Diego-Grand Rapids-
90471Grand Rapids-San Diego-
92481San Diego-Wilkes-Barre/Scranton-
94489San Diego-Rochester-
96499San Jose-San Diego-
98509San Diego-Bridgeport-
100519San Diego-Hartford-
101525Laval-San Diego-
104545San Diego-Charlotte-
105550Wilkes-Barre/Scranton-San Diego-
107563San Diego-Ontario-
109575Abbotsford-San Diego-
111591San Diego-Iowa-
113601Springfield-San Diego-
114609San Diego-Syracuse-
118625Coachella Valley-San Diego-
121644San Diego-Texas-
122649Hartford-San Diego-
126669San Diego-Manitoba-
127675Rockford-San Diego-
130691San Diego-Abbotsford-
132699San Diego-Iowa-
133706Ontario-San Diego-
135722San Diego-Bakersfield-
137730Rockford-San Diego-
139747San Diego-Bakersfield-
141758Bakersfield-San Diego-
143773Iowa-San Diego-
146784San Diego-San Jose-
149799Springfield-San Diego-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
151809San Diego-Cleveland-
153824Utica -San Diego-
154832San Diego-Springfield-
156841San Diego-Utica -
158850Hershey-San Diego-
160865San Diego-Rockford-
162875Eagles-San Diego-
164888San Diego-Coachella Valley-
166900Bakersfield-San Diego-
171924Rochester-San Diego-
177950Texas-San Diego-
182973Rochester-San Diego-
188997Texas-San Diego-
1931020Manitoba-San Diego-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance25,16012,249
Assistance PCT74.00%72.05%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
24 2201 - 73.35% 129,081$2,194,384$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,962,508$ 2,050,900$ 2,050,900$ 2,510,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,517$ 881,266$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
3,097,954$ 111 23,389$ 2,596,179$




San Diego 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
1Sam Lafferty109386710523732212513979.57%19216919.901123349910165555.47%00.9700
2Richard Panik823456902220588929711.45%11142217.351322356700006148.65%01.2700
3Nick Spaling8035458027212217829311.95%14161420.181015257311257151.88%00.9903
4Sam Carrick82393978148920912929513.22%19169020.62712195611296151.74%00.9200
5Mikko Lehtonen111205676201021521202019.95%198243021.90816241000112400%00.6300

San Diego 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
1Casey DeSmith61362120.9162.8035588316619840210.80010
2Justin Pogge2616720.9132.83148501708020200.6679
3Calvin Pickard31161040.9132.901839238910200010.78614

San Diego 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
2082422905123303244594124130111116011743411816040121431271610230353784014106949683021993926106853274073070013723187724.21%2974883.84%41750332652.62%1560306750.86%729139852.15%1991136118796081083549
233719120131111810414178401211574982011800100615564611821032814522935413314534194423112513673466091583522.15%1322779.55%0814149354.52%738136853.95%33157657.47%928640834274478246
Total Saison régulière119614106434421348735832170232221716651612924041122041822214842174711682815812313112435214461345151084399110971046198147611223.53%4297582.52%42564481953.21%2298443551.82%1060197453.70%2920200227138831562795
Séries éliminatoires
20514000001721-421100000119230300000612-6217314800584017448567001785246821600.00%21290.48%110418955.03%10920852.40%548762.07%11277122386432
21116500000513813523000001819-16420000033191412519014100201615054017017117524461131108196601321.67%471176.60%030152657.22%26251351.07%9519748.22%2811952518814875
222213900000797091082000004029111257000003941-22679140219112724244866277254292438322202593881072220.56%962079.17%052494955.22%47791452.19%19835855.31%565392521170291146
Total Séries éliminatoires382018000001471291817116000006957122191200000787264014726140811524843415804954815376714714034136661833519.13%1643379.88%1929166455.83%848163551.87%34764254.05%958665895296505253

San Diego 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
1Jordan Weal381519347610369615.63%465417.231451100012055.56%01.0400
2Wyatt Johnston221714311316242911414.91%246821.3146103400024054.39%21.3200
3Sam Lafferty3810182801479841119.01%564917.0946104400030153.75%00.8600
4Richard Panik38151227415133311912.61%466917.632793200001148.00%10.8100
5Mikko Lehtonen38818269343550849.52%6285522.505510470000110%00.6100

San Diego 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
1Carter Hart 1811610.9182.951120205567401100
2Casey DeSmith135610.8973.88727014745800000
3Ilya Samsonov74210.9262.92432002128501000
4Justin Pogge20100.9063.90770055300000