Votre version du STHS est obsolète! Veuillez mettre à jour votre version du STHS!
Connexion

San Diego
GP: 82 | W: 49 | L: 29 | OTL: 4 | P: 102
GF: 303 | GA: 244 | PP%: 24.21% | PK%: 83.84%
DG: Michael Chouinard | Morale : 50 | Moyenne d’équipe : N/A
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
San Diego
49-29-4, 102pts
3
FINAL
2 Springfield
44-33-5, 93pts
Team Stats
W4StreakL3
26-13-2Home Record29-9-3
23-16-2Away Record15-24-2
8-2-0Last 10 Games5-5-0
3.70Buts par match 3.26
2.98Buts contre par match 2.93
24.21%Pourcentage en avantage numérique16.32%
83.84%Pourcentage en désavantage numérique84.36%
San Diego
49-29-4, 102pts
5
FINAL
2 Abbotsford
26-49-7, 59pts
Team Stats
W4StreakL1
26-13-2Home Record15-22-4
23-16-2Away Record11-27-3
8-2-0Last 10 Games1-9-0
3.70Buts par match 2.88
2.98Buts contre par match 4.09
24.21%Pourcentage en avantage numérique17.80%
83.84%Pourcentage en désavantage numérique76.28%
Meneurs d'équipe
Buts
Sam Carrick
39
Passes
Richard Panik
56
Points
Richard Panik
90
Plus/Moins
Nick Spaling
27
Victoires
Casey DeSmith
31
Pourcentage d’arrêts
Casey DeSmith
0.913

Statistiques d’équipe
Buts pour
303
3.70 GFG
Tirs pour
3021
36.84 Avg
Pourcentage en avantage numérique
24.2%
77 GF
Début de zone offensive
42.7%
Buts contre
244
2.98 GAA
Tirs contre
2740
33.41 Avg
Pourcentage en désavantage numérique
83.8%%
48 GA
Début de la zone défensive
39.4%
Informations de l'équipe

Directeur généralMichael Chouinard
EntraîneurScott Arniel
DivisionPacifique
ConférenceConference ouest
CapitaineMike Green
Assistant #1
Assistant #2Trevor Daley


Informations de l’aréna

Capacité3,000
Assistance2,276
Billets de saison300


Informations de la formation

Équipe Pro21
Équipe Mineure18
Limite contact 39 / 50
Espoirs51


Historique d'équipe

Saison actuelle49-29-4 (102PTS)
Historique98-58-16 (0.570%)
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
1Max Veronneau (R)X100.00632797768870816471646663764748565000251500,000$
2Luke AdamXX100.00633193627577916680656566735546375000312750,000$
3Nick SpalingXX100.006437916674798872837275717665532850003211,170,000$
4Marc-Antoine PouliotXX100.00661996547366836574636564798276195000362550,000$
5Matt FrattinXX100.00572392707871766355606457846664205000331550,000$
6Sam CarrickXX100.008940857785758071856874707562623950002931,170,000$
7Richard PanikXX100.007236897076768574747273677363614650003031,170,000$
8Sam LaffertyXXX100.00883581797981847089687177774951635000262775,000$
9Kris VersteegXX100.00572694676973806970677162797169325000352957,000$
10James NealXX100.008336836576848173706972648077674950003321,160,000$
11Jordan WealXXX100.006827897474798576887472657858555150002931,000,000$
12Joakim NygardX100.00712593777775816670666864755959465000281700,000$
13Andrew MacDonaldX100.00612683607677875250464484767471125000341550,000$
14Mike Green (C)X100.006627796773848364505857867980752350003521,170,000$
15Mikko LehtonenX100.00832591807882805950524286755454575000272750,000$
16Christian WolaninX100.00762581758881854250404084754948595000263750,000$
17Nick SeelerX100.00734763729175924850475185765552565000281750,000$
18Igor OzhiganovX100.00733377739478855050505288715551605000281700,000$
19Trevor Daley (A)X100.006031875871768755505652896874851650003711,040,000$
Rayé
MOYENNE D’ÉQUIPE100.0070308770797784636661627376636040500
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
1Justin Pogge100.0061878691799796989984788382225000351956,000$
2Casey DeSmith100.0074838689839495969791836262605000292900,000$
Rayé
MOYENNE D’ÉQUIPE100.006885869081969697988881737241500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Scott Arniel73798080959263CAN592500,000$


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
1Richard PanikSan Diego (ANA)LW/RW823456902220058892979019311.45%11142217.3513223567257000006148.65%11100001.2700000543
2Nick SpalingSan Diego (ANA)C/LW8035458027215221782939020011.95%14161420.181015257325511251797151.88%225900200.99030013512
3Sam CarrickSan Diego (ANA)C/RW823939781489152091292959223613.22%19169020.62712195625611292046151.74%51600000.9200201585
4Sam LaffertySan Diego (ANA)C/LW/RW72314374213801541792817319711.03%11143819.98915247423210141334355.57%217200101.0300000755
5Jordan WealSan Diego (ANA)C/LW/RW712644701480201032517920110.36%6141119.88513185021900051055355.78%19900000.9901000291
6James NealSan Diego (ANA)LW/RW8227396621480168662476218610.93%2143917.555162165265000002146.43%11200000.9215000136
7Trevor DaleySan Diego (ANA)D8213496292604676133491119.77%117196323.95121325652550223229310.00%000000.6300000133
8Mikko LehtonenSan Diego (ANA)D74114152136801016812739888.66%117157121.2341014692390112196200.00%000000.6600000042
9Igor OzhiganovSan Diego (ANA)D7774249118951275713745835.11%94152919.8621921712420110186110.00%000100.6400010300
10Mike GreenSan Diego (ANA)D8212334515395739016850867.14%139175821.4596151032670001229100.00%000000.5114010122
11Joakim NygardSan Diego (ANA)LW82161430-6340747919039988.42%3100412.25011270001133252.56%7800000.6000000223
12Nick SeelerSan Diego (ANA)D82721281112101054156213512.50%73113913.901012600007210.00%000000.4900020001
13Luke AdamSan Diego (ANA)C/LW82101323-61604312712836837.81%12119814.610000010142362051.38%130200000.3800000202
14Andrew MacDonaldSan Diego (ANA)D8241822716024474617388.70%70120814.7401103000097210.00%000000.3600000101
15Kris VersteegSan Diego (ANA)LW/RW8210919-5115283310227779.80%36047.3700004000001047.50%4000000.6302010001
16Max VeronneauSan Diego (ANA)RW8210818-9100345914543906.90%294411.5100013000000148.53%6800000.3800000100
17Matt FrattinSan Diego (ANA)LW/RW71671304015196320449.52%35517.77000010005850051.43%3500000.4713000000
18Marc-Antoine PouliotSan Diego (ANA)C/RW8011011-110047474116542.44%65146.43000000000170053.11%64400000.4300000000
19Christian WolaninSan Diego (ANA)D80268-13152415201810.00%274005.0100000000019000.00%000000.4000000000
Statistiques d’équipe totales ou en moyenne15073015378381476905013721502302088921089.97%7292340515.537714322069825184610391942471752.88%753600400.72318252344547
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
1Casey DeSmithSan Diego (ANA)54311920.9132.9031628215317540210.800105131451
2Justin PoggeSan Diego (ANA)2616720.9132.83148501708020200.66792650331
Statistiques d’équipe totales ou en moyenne80472640.9132.884647832232556041197781782


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
Andrew MacDonaldSan Diego (ANA)D341986-09-07No213 Lbs6 ft1NoNoNoNo1Pro & Farm550,000$0$0$NoLien
Casey DeSmithSan Diego (ANA)G291991-08-13 06:42:45No186 Lbs6 ft0NoNoNoNo2Pro & Farm900,000$0$0$No900,000$Lien
Christian WolaninSan Diego (ANA)D261995-03-17No192 Lbs6 ft2NoNoNoNo3Pro & Farm750,000$0$0$No750,000$750,000$Lien
Igor OzhiganovSan Diego (ANA)D281992-10-13No212 Lbs6 ft2NoNoNoNo1Pro & Farm700,000$0$0$NoLien
James NealSan Diego (ANA)LW/RW331987-09-03No226 Lbs6 ft2NoNoNoNo2Pro & Farm1,160,000$0$0$No1,160,000$Lien
Joakim NygardSan Diego (ANA)LW281993-01-08No180 Lbs6 ft0NoNoNoNo1Pro & Farm700,000$0$0$NoLien
Jordan WealSan Diego (ANA)C/LW/RW291992-04-15No181 Lbs5 ft10NoNoNoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$Lien
Justin PoggeSan Diego (ANA)G351986-04-22 23:37:02No225 Lbs6 ft3NoNoNoNo1Pro & Farm956,000$0$0$No
Kris VersteegSan Diego (ANA)LW/RW351986-05-13No179 Lbs5 ft11NoNoNoNo2Pro & Farm957,000$0$0$No957,000$Lien
Luke AdamSan Diego (ANA)C/LW311990-01-01No216 Lbs6 ft2NoNoNoNo2Pro & Farm750,000$0$0$No750,000$Lien
Marc-Antoine PouliotSan Diego (ANA)C/RW361985-01-10No211 Lbs6 ft1NoNoNoNo2Pro & Farm550,000$0$0$No550,000$
Matt FrattinSan Diego (ANA)LW/RW331988-01-03No207 Lbs6 ft0NoNoNoNo1Pro & Farm550,000$0$0$NoLien
Max VeronneauSan Diego (ANA)RW251995-12-12Yes195 Lbs6 ft1NoNoNoNo1Pro & Farm500,000$0$0$NoLien
Mike GreenSan Diego (ANA)D351985-10-12No211 Lbs6 ft1NoNoNoNo2Pro & Farm1,170,000$0$0$No1,170,000$Lien
Mikko LehtonenSan Diego (ANA)D271994-01-16 06:34:35No196 Lbs6 ft0NoNoNoNo2Pro & Farm750,000$0$0$No750,000$Lien
Nick SeelerSan Diego (ANA)D281993-06-03No199 Lbs6 ft2NoNoNoNo1Pro & Farm750,000$0$0$NoLien
Nick SpalingSan Diego (ANA)C/LW321988-09-19No214 Lbs6 ft1NoNoNoNo1Pro & Farm1,170,000$0$0$NoLien
Richard PanikSan Diego (ANA)LW/RW301991-02-07No212 Lbs6 ft1NoNoNoNo3Pro & Farm1,170,000$0$0$No1,170,000$1,170,000$Lien
Sam CarrickSan Diego (ANA)C/RW291992-02-04 12:28:46No205 Lbs6 ft0NoNoNoNo3Pro & Farm1,170,000$0$0$No1,170,000$1,170,000$Lien
Sam LaffertySan Diego (ANA)C/LW/RW261995-03-06No198 Lbs6 ft1NoNoNoNo2Pro & Farm775,000$0$0$No775,000$Lien
Trevor DaleySan Diego (ANA)D371983-10-09No199 Lbs5 ft11NoNoNoNo1Pro & Farm1,040,000$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2130.76203 Lbs6 ft11.76858,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jordan WealNick SpalingSam Carrick33005
2Richard PanikSam LaffertyJames Neal30005
3Joakim NygardLuke AdamMax Veronneau24041
4Kris VersteegMarc-Antoine PouliotMatt Frattin13041
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Igor OzhiganovTrevor Daley33023
2Mike GreenMikko Lehtonen30023
3Nick SeelerAndrew MacDonald24023
4Trevor DaleyChristian Wolanin13050
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jordan WealNick SpalingSam Carrick50005
2Richard PanikSam LaffertyJames Neal50005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Igor OzhiganovTrevor Daley50005
2Mike GreenMikko Lehtonen50005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Nick SpalingJordan Weal50050
2Sam CarrickLuke Adam50050
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Igor OzhiganovTrevor Daley50050
2Mikko LehtonenMike Green50050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Sam Carrick50050Igor OzhiganovTrevor Daley50050
2Nick Spaling50050Nick SeelerMike Green50050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Luke AdamJoakim Nygard50014
2Sam CarrickSam Lafferty50014
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nick SeelerIgor Ozhiganov50014
2Christian WolaninAndrew MacDonald50014
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jordan WealNick SpalingJames NealMike GreenTrevor Daley
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jordan WealNick SpalingSam LaffertyMikko LehtonenTrevor Daley
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Joakim Nygard, Nick Spaling, Richard PanikJoakim Nygard, Max VeronneauJordan Weal
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Trevor Daley, Igor Ozhiganov, Mike GreenNick SeelerTrevor Daley, Andrew MacDonald
Tirs de pénalité
Nick Spaling, James Neal, Mike Green, Kris Versteeg, Marc-Antoine Pouliot
Gardien
#1 : Casey DeSmith, #2 : Justin Pogge


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
1Abbotsford76100000251114330000001028431000001596120.85725457001106949682559939261068531924152121411126.83%26292.31%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
2Bakersfield633000002119232100000139431200000810-260.500213960001069496821599392610685318153651052314.35%21385.71%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
3Charlotte211000007701010000045-11100000032120.50071118001069496864993926106853821718259222.22%90100.00%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
4Cleveland31200000910-1211000006601010000034-120.33391726001069496810199392610685310625304513323.08%14192.86%11750332652.62%1560306750.86%729139852.15%1991136118796081083549
5Grand Rapids21000001651110000003121000000134-130.75061218001069496868993926106853852520215240.00%10190.00%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
6Hartford220000001248110000005141100000073441.0001221330010694968869939261068537521143710330.00%5180.00%11750332652.62%1560306750.86%729139852.15%1991136118796081083549
7Hershey2110000011101110000006421010000056-120.5001120310010694968699939261068539129103910330.00%5260.00%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
8Iowa42200000151142110000054121100000107340.500152641001069496814299392610685313835386318316.67%18288.89%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
9Laval201010009901010000056-11000100043120.50091625001069496875993926106853752240237114.29%9366.67%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
10Lehigh Valley211000008801010000056-11100000032120.50081321001069496853993926106853621516406350.00%8362.50%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
11Manitoba440000001688220000007432200000094581.000162945001069496817699392610685312327206921314.29%6350.00%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
12Milwaukee4210100014104220000008442010100066060.750142741001069496815899392610685313543317016637.50%10190.00%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
13Ontario623000011722-5311000011010031200000712-550.417173047001069496822699392610685324052549322522.73%27774.07%11750332652.62%1560306750.86%729139852.15%1991136118796081083549
14Providence21100000752110000003031010000045-120.50071320011069496877993926106853642416387228.57%7271.43%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
15Rochester42200000181172110000012662110000065140.500183351011069496812599392610685311836287317635.29%13192.31%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
16Rockford4120100013130211000006512010100078-140.500132336101069496813899392610685313439287711327.27%130100.00%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
17San Jose63101010241863110100013130320000101156100.8332438620010694968245993926106853207385110121523.81%20290.00%11750332652.62%1560306750.86%729139852.15%1991136118796081083549
18Springfield412001001012-22010010046-22110000066030.37510182800106949681479939261068531132228641400.00%13192.31%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
19Texas422000001112-12110000078-12110000044040.500112031001069496815299392610685313036366215320.00%18477.78%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
20Toronto2010100068-21010000014-31000100054120.50061218001069496870993926106853732414358225.00%7185.71%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
21Tucson6320000124195330000001761130200001713-670.5832442660110694968226993926106853193555411411218.18%22577.27%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
22Utica210000101082100000106511100000043141.000101525001069496874993926106853622615257457.14%5180.00%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
23Wilkes-Barre/Scranton220000001046110000004221100000062441.000101727001069496879993926106853612522326466.67%11281.82%01750332652.62%1560306750.86%729139852.15%1991136118796081083549
Total8242290512330324459412413011111601174341181604012143127161020.62230353784014106949683021993926106853274073070013723187724.21%2974883.84%41750332652.62%1560306750.86%729139852.15%1991136118796081083549
_Since Last GM Reset8242290512330324459412413011111601174341181604012143127161020.62230353784014106949683021993926106853274073070013723187724.21%2974883.84%41750332652.62%1560306750.86%729139852.15%1991136118796081083549
_Vs Conference5529190311219015535271770110110071292812120201190846690.6271903375271210694968208099392610685317864414579392134219.72%1943084.54%21750332652.62%1560306750.86%729139852.15%1991136118796081083549
_Vs Division31171001012111892215103010016340231677000114849-1400.6451111943050210694968116799392610685310132392765341182420.34%1161983.62%21750332652.62%1560306750.86%729139852.15%1991136118796081083549

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82102W430353784030212740730700137214
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8242295123303244
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4124131111160117
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4118164012143127
Derniers 10 matchs
WLOTWOTL SOWSOL
820000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3187724.21%2974883.84%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
99392610685310694968
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
1750332652.62%1560306750.86%729139852.15%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1991136118796081083549


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
1 - 2022-11-253San Diego4Abbotsford2AWSommaire du match
3 - 2022-11-2614Abbotsford1San Diego4BWSommaire du match
6 - 2022-11-2729San Diego2Ontario6ALSommaire du match
8 - 2022-11-2841Ontario5San Diego4BLXXSommaire du match
10 - 2022-11-2952San Diego2Tucson6ALSommaire du match
12 - 2022-11-3061Bakersfield2San Diego4BWSommaire du match
13 - 2022-12-0168San Diego1Bakersfield3ALSommaire du match
16 - 2022-12-0279San Diego6San Jose2AWSommaire du match
17 - 2022-12-0391Tucson2San Diego4BWSommaire du match
21 - 2022-12-05111Cleveland2San Diego1BLSommaire du match
22 - 2022-12-05119San Diego3Milwaukee2AWXSommaire du match
25 - 2022-12-07133Bakersfield4San Diego3BLSommaire du match
27 - 2022-12-08147Ontario1San Diego5BWSommaire du match
32 - 2022-12-10168San Diego3Ontario5ALSommaire du match
33 - 2022-12-11172San Diego1Abbotsford2ALSommaire du match
35 - 2022-12-12185San Jose6San Diego4BLSommaire du match
38 - 2022-12-13200San Diego5Toronto4AWXSommaire du match
39 - 2022-12-14208Grand Rapids1San Diego3BWSommaire du match
42 - 2022-12-15225San Diego4Laval3AWXSommaire du match
44 - 2022-12-16232Springfield2San Diego1BLXSommaire du match
46 - 2022-12-17244San Diego4Utica3AWSommaire du match
48 - 2022-12-18254Cleveland4San Diego5BWSommaire du match
49 - 2022-12-19264San Diego3Tucson4ALXXSommaire du match
53 - 2022-12-21278Tucson4San Diego9BWSommaire du match
55 - 2022-12-22292San Diego5Hershey6ALSommaire du match
56 - 2022-12-22302Iowa1San Diego3BWSommaire du match
59 - 2022-12-24319San Diego4Providence5ALSommaire du match
60 - 2022-12-24326Charlotte5San Diego4BLSommaire du match
63 - 2022-12-26338San Diego4Iowa5ALSommaire du match
64 - 2022-12-26348Toronto4San Diego1BLSommaire du match
67 - 2022-12-28363San Diego6Iowa2AWSommaire du match
69 - 2022-12-29371Providence0San Diego3BWSommaire du match
73 - 2022-12-31390San Diego2Tucson3ALSommaire du match
75 - 2023-01-01398San Jose4San Diego5BWXSommaire du match
77 - 2023-01-02407San Diego3Grand Rapids4ALXXSommaire du match
79 - 2023-01-03419San Diego2Rochester0AWSommaire du match
81 - 2023-01-04428Springfield4San Diego3BLSommaire du match
83 - 2023-01-05441San Diego0Texas3ALSommaire du match
85 - 2023-01-06449Lehigh Valley6San Diego5BLSommaire du match
87 - 2023-01-07465San Diego4Texas1AWSommaire du match
89 - 2023-01-08473Laval6San Diego5BLSommaire du match
91 - 2023-01-09484San Diego6Wilkes-Barre/Scranton2AWSommaire du match
94 - 2023-01-10497San Diego4Manitoba2AWSommaire du match
95 - 2023-01-11502Hartford1San Diego5BWSommaire du match
98 - 2023-01-12519Wilkes-Barre/Scranton2San Diego4BWSommaire du match
100 - 2023-01-13530San Diego7Hartford3AWSommaire du match
102 - 2023-01-14541San Diego4Rochester5ALSommaire du match
104 - 2023-01-15551Hershey4San Diego6BWSommaire du match
108 - 2023-01-17569Iowa3San Diego2BLSommaire du match
111 - 2023-01-19582San Diego3Lehigh Valley2AWSommaire du match
113 - 2023-01-20594Milwaukee1San Diego4BWSommaire du match
117 - 2023-01-22613Milwaukee3San Diego4BWSommaire du match
122 - 2023-01-24634Tucson0San Diego4BWSommaire du match
125 - 2023-01-26648San Diego3Charlotte2AWSommaire du match
126 - 2023-01-26657Ontario4San Diego1BLSommaire du match
130 - 2023-01-28678San Diego4Rockford3AWXSommaire du match
132 - 2023-01-29683Rockford2San Diego1BLSommaire du match
135 - 2023-01-31701Rochester2San Diego1BLSommaire du match
137 - 2023-02-01713San Diego3Rockford5ALSommaire du match
139 - 2023-02-02720San Diego5Manitoba2AWSommaire du match
141 - 2023-02-03729Rochester4San Diego11BWSommaire du match
145 - 2023-02-05752Abbotsford0San Diego2BWSommaire du match
147 - 2023-02-06765San Diego4Bakersfield3AWSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-02-07775Abbotsford1San Diego4BWSommaire du match
151 - 2023-02-08786San Diego3Cleveland4ALSommaire du match
155 - 2023-02-10801Bakersfield3San Diego6BWSommaire du match
157 - 2023-02-11814San Diego3Bakersfield4ALSommaire du match
159 - 2023-02-12824Manitoba2San Diego4BWSommaire du match
160 - 2023-02-12831San Diego3Milwaukee4ALSommaire du match
163 - 2023-02-14846Manitoba2San Diego3BWSommaire du match
165 - 2023-02-15854San Diego2Ontario1AWSommaire du match
167 - 2023-02-16870San Diego3San Jose2AWXXSommaire du match
169 - 2023-02-17874Texas3San Diego5BWSommaire du match
172 - 2023-02-18890San Diego2San Jose1AWSommaire du match
174 - 2023-02-19896Rockford3San Diego5BWSommaire du match
175 - 2023-02-20903San Diego3Springfield4ALSommaire du match
180 - 2023-02-22919Utica5San Diego6BWXXSommaire du match
185 - 2023-02-25942Texas5San Diego2BLSommaire du match
187 - 2023-02-26946San Diego5Abbotsford3AWSommaire du match
191 - 2023-02-28962San Jose3San Diego4BWSommaire du match
193 - 2023-03-01971San Diego3Springfield2AWSommaire du match
195 - 2023-03-02979San Diego5Abbotsford2AWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance62,17731,134
Assistance PCT75.83%75.94%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2276 - 75.86% 133,119$5,457,870$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,271,852$ 1,801,800$ 1,801,800$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,100$ 1,771,897$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 11,625$ 0$




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
1Richard Panik16468112180444011617859411.45%22284517.35264470134000012248.6501.2700
2Nick Spaling160709016054424435658611.95%28322820.182030501462241014251.8800.9906
3Sam Carrick16478781562817841825859013.22%38338120.621424381122241812251.7400.9200
4Sam Lafferty1446286148427630835856211.03%22287619.9818304814820288655.5701.0300
5Jordan Weal142528814028164020650210.36%12282219.881026361000001010655.7800.9902

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 DeSmith108623840.9132.90632416430635080420.80020
2Justin Pogge52321440.9132.8329700214016040400.66718

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
2082422905123303244594124130111116011743411816040121431271610230353784014106949683021993926106853274073070013723187724.21%2974883.84%41750332652.62%1560306750.86%729139852.15%1991136118796081083549
Total Saison régulière1648458010246606488118824826022223202348682363208024286254322046061074168028212188192166042198618522136106548014601400274463615424.21%5949683.84%83500665252.62%3120613450.86%1458279652.15%398327233759121621671098
Séries éliminatoires
Total Séries éliminatoires00000000000000.00%0.00%0.00%0.00%0.00%000000

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

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