Connexion

Sags
GP: 72 | W: 32 | L: 34 | OTL: 6 | P: 70
GF: 148 | GA: 147 | PP%: 14.69% | PK%: 82.38%
DG: Nick Gagnon | Morale : 50 | Moyenne d’équipe : 59
Prochains matchs #1177 vs Chiefs
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
Stars
44-25-5, 93pts
1
FINAL
2 Sags
32-34-6, 70pts
Team Stats
L2SéquenceW2
21-13-2Fiche domicile17-18-0
23-12-3Fiche domicile15-16-6
6-3-1Derniers 10 matchs5-4-1
2.58Buts par match 2.06
2.01Buts contre par match 2.04
17.89%Pourcentage en avantage numérique14.69%
84.38%Pourcentage en désavantage numérique82.38%
Sags
32-34-6, 70pts
4
FINAL
0 Minnesota
31-39-2, 64pts
Team Stats
W2SéquenceL1
17-18-0Fiche domicile20-15-1
15-16-6Fiche domicile11-24-1
5-4-1Derniers 10 matchs5-5-0
2.06Buts par match 2.54
2.04Buts contre par match 2.75
14.69%Pourcentage en avantage numérique11.71%
82.38%Pourcentage en désavantage numérique81.07%
Sags
32-34-6, 70pts
2024-03-30
Chiefs
43-23-7, 93pts
Statistiques d’équipe
W2SéquenceL1
17-18-0Fiche domicile26-7-3
15-16-6Fiche visiteur17-16-4
5-4-110 derniers matchs5-4-1
2.06Buts par match 2.27
2.04Buts contre par match 2.27
14.69%Pourcentage en avantage numérique13.08%
82.38%Pourcentage en désavantage numérique87.65%
Seattle
51-17-4, 106pts
2024-04-01
Sags
32-34-6, 70pts
Statistiques d’équipe
W9SéquenceW2
31-5-2Fiche domicile17-18-0
20-12-2Fiche visiteur15-16-6
9-1-010 derniers matchs5-4-1
2.69Buts par match 2.06
1.69Buts contre par match 2.06
14.59%Pourcentage en avantage numérique14.69%
89.50%Pourcentage en désavantage numérique82.38%
Monarchs
33-34-5, 71pts
2024-04-04
Sags
32-34-6, 70pts
Statistiques d’équipe
W2SéquenceW2
17-17-1Fiche domicile17-18-0
16-17-4Fiche visiteur15-16-6
4-6-010 derniers matchs5-4-1
1.86Buts par match 2.06
2.28Buts contre par match 2.06
16.08%Pourcentage en avantage numérique14.69%
87.62%Pourcentage en désavantage numérique82.38%
Meneurs d'équipe
Buts
Alex Turcotte
17
Passes
Henry Thrun
28
Points
Henry Thrun
38
Plus/Moins
Jiri Kulich
7
Victoires
Malcolm Subban
31
Pourcentage d’arrêts
Dryden McKay
0.962

Statistiques d’équipe
Buts pour
148
2.06 GFG
Tirs pour
1286
17.86 Avg
Pourcentage en avantage numérique
14.7%
31 GF
Début de zone offensive
39.0%
Buts contre
147
2.04 GAA
Tirs contre
1339
18.60 Avg
Pourcentage en désavantage numérique
82.4%%
34 GA
Début de la zone défensive
39.5%
Informations de l'équipe

Directeur généralNick Gagnon
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,945
Billets de saison300


Informations de la formation

Équipe Pro23
Équipe Mineure20
Limite contact 43 / 50
Espoirs14


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
1Ben Meyers (R)XX100.00654077717574666672606364675650050640233912,500$
2Tyler BensonXX100.00624370676868666241615557615550050600242620,000$
3Jiri Kulich (R)XX100.00594070686157576442626255655050050600183950,000$
4Alex Turcotte (R)X100.00624567706360585945565362605050050590211925,000$
5Jordy BelleriveX100.00605460676365646256595459615251050590232733,333$
6Aatu Raty (R)X100.00634069666357576252615660615050050590193836,667$
7Ty Tullio (R)X100.00574070695760616241595857625050050590203833,333$
8Michal Teply (R)X100.00574573646563626242605552605050050580211825,833$
9Zayde Wisdom (R)X100.00624069656360605851555459595050050580203797,500$
10Reilly WalshX100.00594569726266666640655869655250050640231700,000$
11Henry Thrun (R)X100.00574071717780606540626063665150050640213650,000$
12Michael Kesselring (R)X100.006657646967636366405860686551500506302211,100,000$
13Wyatt KalynukX100.00606057716266656240615568635450050620252925,000$
14Jack Thompson (R)X100.00604071696262626440605966645050050620203828,333$
15Anttoni Honka (R)X100.00564070696062636440635765635050050610213700,000$
16Helge Grans (R)X100.00644672656860606140555462605050050600203847,500$
17Corson Ceulemans (R)X100.00624068646554535640545461585050050580193925,000$
Rayé
1Carter Savoie (R)X100.00564069636260605940545653595050050570203925,000$
2Rory Kerins (R)X100.00624068656258575647545458585050050570203846,667$
3Philippe Daoust (R)X100.00544366705357545450515152585050050550205600,000$
4Demetrios Koumontzis (R)X100.00444478636441533448293041355050050440222650,000$
MOYENNE D’ÉQUIPE100.0059446968646260604557556060515005059
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
1Malcolm Subban100.00747173757270726871737166590506602821,500,000$
2Dryden McKay (R)100.0063575762605959566060535250050550243560,000$
Rayé
MOYENNE D’ÉQUIPE100.006964656966656662666762595505061
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Henry ThrunSags (San)D701028387180789087295511.49%62159122.73491358197101115820100.00%100000.4801000070
2Tyler BensonSags (San)LW/RW70142135526011564123146511.38%7140820.134593016300041041146.23%10600000.5048000603
3Jiri KulichSags (San)C/LW70142135728010381117389711.97%16151521.660551717001121352240.19%41800000.4658000255
4Reilly WalshSags (San)D3982129-1180516347123117.02%3282221.09651130100000176210%000000.7100000405
5Wyatt KalynukSags (San)D7072229-54401038866183510.61%52133419.077411511620000122000%000000.4311000202
6Ty TullioSags (San)RW701017275140596510339699.71%4126318.06178191630000182242.70%8900000.4302000222
7Jack ThompsonSags (San)D7032225-524051746522514.62%50133419.06178361630110128100%000000.3701000222
8Alex TurcotteSags (San)C7217623230010111998177317.35%12127317.681016720002466250.25%99100000.3604000440
9Jordy BelleriveSags (San)C72101323-724010512010128709.90%11125217.391457680000292155.60%67800000.3702000221
10Anttoni HonkaSags (San)D723151852805055336269.09%41105914.720115320000210066.67%300000.3411000111
11Ben MeyersSags (San)C/LW2712517420347669244717.39%959321.9920211741122684161.44%62500100.5711000211
12Aatu RatySags (San)C277714-116037554674015.22%451719.171239590000290052.69%46500000.5401000004
13Michael KesselringSags (San)D2711213526054273415252.94%2957621.360442369000050000%000000.4511000012
14Helge GransSags (San)D704913547591383071613.33%37101314.4810139000060100%000000.2611000211
15Zayde WisdomSags (San)C685712-414046515315429.43%584212.391343580000152049.18%18300000.2811000022
16Matthew PhillipsSan JoseC1556115209464592711.11%433222.200114400000332145.02%33100000.6602000111
17Michal TeplySags (San)LW512810-714043476319383.17%392918.230115640000420031.82%6600000.2200000000
18Givani SmithSan JoseLW/RW153693341052254811416.25%330920.610003401012472046.15%2600000.5801101200
19Carter SavoieSags (San)LW39549-16026293362215.15%168617.610004160000401051.35%3700000.2601000001
20Corson CeulemansSags (San)D4906631803826135130%1952910.8100001000040050.00%1000000.2300000001
21Alex ChiassonSan JoseRW6235300771121218.18%011018.3500029000000066.67%900000.9111000200
Statistiques d’équipe totales ou en moyenne1069142259401284331512531246128534389511.05%4011929918.053058883261738336141232301151.11%403800100.421638101342934
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
1Malcolm SubbanSags (San)70313260.8961.9141392913212640320.64139700364
2Dryden McKaySags (San)41000.9620.57106001260001.0002070000
Statistiques d’équipe totales ou en moyenne74323260.8971.884245291331290032417070364


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 Recrue Poids Taille Non-échange Disponible pour échange Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire moyen 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 10Lien
Aatu RatySags (San)C192002-11-14Yes185 Lbs6 ft2NoNoNoNo3Pro & Farm836,667$91,510$0$0$No836,667$836,667$
Alex TurcotteSags (San)C212001-02-26Yes185 Lbs5 ft11NoNoNoNo1Pro & Farm925,000$101,172$0$0$NoLien
Anttoni HonkaSags (San)D212000-10-05Yes179 Lbs5 ft10NoNoNoNo3Pro & Farm700,000$76,562$0$0$No700,000$700,000$Lien
Ben MeyersSags (San)C/LW231998-11-15Yes194 Lbs5 ft11NoNoNoNo3Pro & Farm912,500$99,805$0$0$No912,500$912,500$
Carter SavoieSags (San)LW202002-01-23Yes192 Lbs5 ft9NoNoNoNo3Pro & Farm925,000$101,172$0$0$No925,000$925,000$
Corson CeulemansSags (San)D192003-05-05Yes198 Lbs6 ft2NoNoNoNo3Pro & Farm925,000$101,172$0$0$No925,000$925,000$
Demetrios KoumontzisSags (San)LW222000-03-24Yes183 Lbs5 ft10NoNoNoNo2Pro & Farm650,000$71,094$0$0$No650,000$Lien
Dryden McKaySags (San)G241997-11-25Yes183 Lbs6 ft0NoNoYesYes3Pro & Farm560,000$61,250$0$0$No560,000$560,000$
Helge GransSags (San)D202002-05-10Yes205 Lbs6 ft3NoNoNoNo3Pro & Farm847,500$92,695$0$0$No847,500$847,500$Lien
Henry ThrunSags (San)D212001-03-12Yes190 Lbs6 ft2NoNoNoNo3Pro & Farm650,000$71,094$0$0$No650,000$650,000$Lien
Jack ThompsonSags (San)D202002-03-19Yes179 Lbs6 ft0NoNoNoNo3Pro & Farm828,333$90,599$0$0$No828,333$828,333$
Jiri KulichSags (San)C/LW182004-04-14Yes179 Lbs5 ft11NoNoNoNo3Pro & Farm950,000$103,906$0$0$No950,000$950,000$
Jordy BelleriveSags (San)C231999-05-02No194 Lbs5 ft11NoNoNoNo2Pro & Farm733,333$80,208$0$0$No733,333$Lien
Malcolm Subban (contrat à 1 volet)Sags (San)G281993-12-21No216 Lbs6 ft2NoNoYesYes2Pro & Farm1,500,000$164,062$600,000$65,625$No1,500,000$Lien
Michael KesselringSags (San)D222000-01-13Yes190 Lbs6 ft4NoNoNoNo1Pro & Farm1,100,000$120,312$0$0$NoLien
Michal TeplySags (San)LW212001-05-27Yes187 Lbs6 ft3NoNoNoNo1Pro & Farm825,833$90,325$0$0$NoLien
Philippe DaoustSags (San)LW202001-11-05Yes150 Lbs6 ft0NoNoNoNo5Pro & Farm600,000$65,625$0$0$No600,000$600,000$600,000$600,000$Lien
Reilly WalshSags (San)D231999-04-21No185 Lbs6 ft0NoNoNoNo1Pro & Farm700,000$76,562$0$0$NoLien
Rory KerinsSags (San)C202002-04-12Yes185 Lbs6 ft0NoNoNoNo3Pro & Farm846,667$92,604$0$0$No846,667$846,667$
Ty TullioSags (San)RW202002-04-05Yes165 Lbs5 ft10NoNoNoNo3Pro & Farm833,333$91,146$0$0$No833,333$833,333$
Tyler BensonSags (San)LW/RW241998-03-15No190 Lbs6 ft0NoNoYesYes2Pro & Farm620,000$67,812$0$0$No620,000$Lien
Wyatt KalynukSags (San)D251997-04-14No181 Lbs6 ft1NoNoYesYes2Pro & Farm925,000$101,172$0$0$No925,000$Lien
Zayde WisdomSags (San)C202002-05-20Yes194 Lbs5 ft11NoNoNoNo3Pro & Farm797,500$87,227$0$0$No797,500$797,500$
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2321.48186 Lbs6 ft02.52834,420$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jiri KulichAatu Raty40122
2Tyler BensonBen MeyersTy Tullio30122
3Alex TurcotteJordy Bellerive20122
4Ben MeyersZayde WisdomJiri Kulich10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henry ThrunMichael Kesselring40122
2Jack ThompsonWyatt Kalynuk30122
3Anttoni HonkaHelge Grans20122
4Michael KesselringHenry Thrun10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jiri KulichBen Meyers60122
2Tyler BensonAatu RatyTy Tullio40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henry ThrunMichael Kesselring60122
2Jack ThompsonWyatt Kalynuk40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Ben MeyersJiri Kulich60122
2Tyler BensonAatu Raty40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henry ThrunMichael Kesselring60122
2Jack ThompsonWyatt Kalynuk40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Ben Meyers60122Henry ThrunMichael Kesselring60122
2Jiri Kulich40122Jack ThompsonWyatt Kalynuk40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Ben MeyersJiri Kulich60122
2Tyler BensonAatu Raty40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henry ThrunMichael Kesselring60122
2Jack ThompsonWyatt Kalynuk40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jiri KulichBen MeyersHenry ThrunMichael Kesselring
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jiri KulichBen MeyersHenry ThrunMichael Kesselring
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Zayde Wisdom, Jordy Bellerive, Zayde Wisdom, Jordy Bellerive
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Anttoni Honka, Helge Grans, Michael KesselringAnttoni HonkaHelge Grans, Michael Kesselring
Tirs de pénalité
, Jiri Kulich, Tyler Benson, Aatu Raty, Jordy Bellerive
Gardien
#1 : Malcolm Subban, #2 : Dryden McKay


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
1Admirals422000001064211000008442110000022040.500101828014351481873434427415528722336314214.29%15380.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
2Baby Hawks30300000511-61010000023-12020000038-500.0005101500435148184543442741552532712601119.09%6266.67%1853178047.92%897180649.67%47498248.27%177512411688509908462
3Bears21001000413110000002021000100021141.000481201435148183843442741552228437900.00%10100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
4Bruins2010000146-21010000034-11000000112-110.250481200435148183143442741552421114347228.57%6350.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
5Cabaret Lady Mary Ann21000001752110000004131000000134-130.750712190043514818484344274155225116298225.00%30100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
6Caroline21100000330110000002021010000013-220.500358114351481827434427415523251044500.00%5180.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
7Chiefs1010000001-11010000001-10000000000000.000000004351481884344274155290616200.00%3166.67%0853178047.92%897180649.67%47498248.27%177512411688509908462
8Chill31101000651100010001012110000055040.66761117014351481850434427415523923145910330.00%6183.33%0853178047.92%897180649.67%47498248.27%177512411688509908462
9Comets4130000079-2211000006422020000015-420.25071320104351481878434427415526518226114214.29%9188.89%0853178047.92%897180649.67%47498248.27%177512411688509908462
10Cougars22000000936110000005141100000042241.0009172600435148182943442741552551016366233.33%8187.50%0853178047.92%897180649.67%47498248.27%177512411688509908462
11Crunch21100000862110000004131010000045-120.500815230043514818484344274155245141041800.00%5260.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
12Heat11000000211000000000001100000021121.00024600435148181543442741552126218000%10100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
13Jayhawks21100000550110000004221010000013-220.500510150043514818534344274155243148352150.00%40100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
14Las Vegas412000108802020000036-32100001052340.5008111901435148186743442741552712324745120.00%9188.89%0853178047.92%897180649.67%47498248.27%177512411688509908462
15Manchots2110000057-2110000003211010000025-320.5005101500435148183843442741552321014267114.29%60100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
16Marlies2020000014-31010000012-11010000002-200.000123004351481829434427415523981236700.00%4175.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
17Minnesota21000100633000000000002100010063330.750610160143514818474344274155255128376233.33%40100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
18Monarchs3030000037-41010000013-22020000024-200.0003690043514818554344274155252131858600.00%8275.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
19Monsters21000010532110000002111000001032141.000581300435148183543442741552301314374125.00%7185.71%0853178047.92%897180649.67%47498248.27%177512411688509908462
20Monsters3120000048-41010000004-42110000044020.333481200435148184643442741552652684411436.36%4250.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
21Oceanics30200010810-22020000036-31000001054120.33381220004351481851434427415526615184912325.00%7271.43%0853178047.92%897180649.67%47498248.27%177512411688509908462
22Oil Kings21000010523210000105230000000000041.0005712014351481843434427415524218647200.00%30100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
23Phantoms2010010025-31010000002-21000010023-110.2502460043514818314344274155240112043700.00%10190.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
24Rocket2010000135-21010000001-11000000134-110.2503690043514818364344274155246102832400.00%12283.33%0853178047.92%897180649.67%47498248.27%177512411688509908462
25Seattle2010000102-21010000001-11000000101-110.2500000043514818324344274155244181240400.00%60100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
26Senators21100000330110000003211010000001-120.5003470043514818494344274155232916327114.29%7185.71%0853178047.92%897180649.67%47498248.27%177512411688509908462
27Sound Tigers211000002111010000001-11100000020220.50024601435148183843442741552207834600.00%30100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
28Spiders2110000023-11010000002-21100000021120.50023500435148182443442741552411710365120.00%50100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
29Stars3210000011832110000056-11100000062440.667112031004351481851434427415526126264814214.29%13469.23%1853178047.92%897180649.67%47498248.27%177512411688509908462
30Thunder22000000725110000003121100000041341.000713200043514818414344274155239181238300.00%60100.00%0853178047.92%897180649.67%47498248.27%177512411688509908462
31Wolf Pack2110000034-1110000002111010000013-220.5003580043514818304344274155235121436500.00%7271.43%0853178047.92%897180649.67%47498248.27%177512411688509908462
Total7226340224414814713515180101072648371116012347683-7700.4861482644122843514818128643442741552133943542512802113114.69%1933482.38%2853178047.92%897180649.67%47498248.27%177512411688509908462
_Since Last GM Reset7226340224414814713515180101072648371116012347683-7700.4861482644122843514818128643442741552133943542512802113114.69%1933482.38%2853178047.92%897180649.67%47498248.27%177512411688509908462
_Vs Conference351217021216567-2177901000323111858011213336-3340.486651161810443514818613434427415526161972216181091412.84%981782.65%0853178047.92%897180649.67%47498248.27%177512411688509908462
_Vs Division1619010114234880501000231310814000111921-270.21942771190043514818311434427415523239111427850714.00%511080.39%0853178047.92%897180649.67%47498248.27%177512411688509908462

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7270W214826441212861339435425128028
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7226342244148147
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
35151810107264
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
37111612347683
Derniers 10 matchs
WLOTWOTL SOWSOL
540100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2113114.69%1933482.38%2
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
4344274155243514818
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
853178047.92%897180649.67%47498248.27%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
177512411688509908462


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
3 - 2023-10-1216Las Vegas4Sags2BLSommaire du match
5 - 2023-10-1429Monsters4Sags0BLSommaire du match
8 - 2023-10-1747Caroline0Sags2BWSommaire du match
10 - 2023-10-1961Bruins4Sags3BLSommaire du match
12 - 2023-10-2174Sags3Chill2AWSommaire du match
15 - 2023-10-2489Sags3Cabaret Lady Mary Ann4ALXXSommaire du match
17 - 2023-10-26106Sags4Thunder1AWSommaire du match
18 - 2023-10-27112Sags1Caroline3ALSommaire du match
20 - 2023-10-29128Sags2Bears1AWXSommaire du match
24 - 2023-11-02156Comets1Sags4BWSommaire du match
26 - 2023-11-04171Manchots2Sags3BWSommaire du match
29 - 2023-11-07189Phantoms2Sags0BLSommaire du match
31 - 2023-11-09203Oil Kings0Sags2BWSommaire du match
32 - 2023-11-10209Sags3Las Vegas2AWXXSommaire du match
34 - 2023-11-12226Sags2Admirals0AWSommaire du match
36 - 2023-11-14237Cabaret Lady Mary Ann1Sags4BWSommaire du match
38 - 2023-11-16250Chiefs1Sags0BLSommaire du match
42 - 2023-11-20278Sags1Comets3ALSommaire du match
44 - 2023-11-22291Sags0Seattle1ALXXSommaire du match
46 - 2023-11-24300Rocket1Sags0BLSommaire du match
47 - 2023-11-25313Comets3Sags2BLSommaire du match
49 - 2023-11-27326Bears0Sags2BWSommaire du match
52 - 2023-11-30340Sags1Bruins2ALXXSommaire du match
53 - 2023-12-01355Sags2Spiders1AWSommaire du match
55 - 2023-12-03370Sags1Wolf Pack3ALSommaire du match
57 - 2023-12-05383Sags2Sound Tigers0AWSommaire du match
59 - 2023-12-07393Sags4Cougars2AWSommaire du match
62 - 2023-12-10427Sags2Las Vegas0AWSommaire du match
64 - 2023-12-12441Oceanics3Sags1BLSommaire du match
67 - 2023-12-15459Sags1Jayhawks3ALSommaire du match
69 - 2023-12-17478Sags3Monsters1AWSommaire du match
71 - 2023-12-19494Monarchs3Sags1BLSommaire du match
73 - 2023-12-21509Jayhawks2Sags4BWSommaire du match
75 - 2023-12-23527Sags0Comets2ALSommaire du match
79 - 2023-12-27541Sags1Monarchs2ALSommaire du match
80 - 2023-12-28545Oil Kings2Sags3BWXXSommaire du match
83 - 2023-12-31571Sags1Monsters3ALSommaire du match
85 - 2024-01-02586Cougars1Sags5BWSommaire du match
87 - 2024-01-04601Oceanics3Sags2BLSommaire du match
89 - 2024-01-06607Marlies2Sags1BLSommaire du match
92 - 2024-01-09627Sags0Marlies2ALSommaire du match
94 - 2024-01-11642Sags3Rocket4ALXXSommaire du match
96 - 2024-01-13655Sags0Senators1ALSommaire du match
98 - 2024-01-15672Sags4Crunch5ALSommaire du match
99 - 2024-01-16686Sags2Baby Hawks4ALSommaire du match
103 - 2024-01-20714Admirals3Sags2BLSommaire du match
105 - 2024-01-22729Sags1Monarchs2ALSommaire du match
106 - 2024-01-23738Wolf Pack1Sags2BWSommaire du match
110 - 2024-01-27761Crunch1Sags4BWSommaire du match
113 - 2024-01-30777Seattle1Sags0BLSommaire du match
114 - 2024-01-31780Sags0Admirals2ALSommaire du match
128 - 2024-02-14834Sags5Oceanics4AWXXSommaire du match
129 - 2024-02-15846Sags2Heat1AWSommaire du match
131 - 2024-02-17861Monsters1Sags2BWSommaire du match
133 - 2024-02-19871Las Vegas2Sags1BLSommaire du match
138 - 2024-02-24913Chill0Sags1BWXSommaire du match
141 - 2024-02-27938Spiders2Sags0BLSommaire du match
143 - 2024-02-29952Admirals1Sags6BWSommaire du match
145 - 2024-03-02966Sags6Stars2AWSommaire du match
146 - 2024-03-03971Sags2Minnesota3ALXSommaire du match
148 - 2024-03-05989Stars5Sags3BLSommaire du match
150 - 2024-03-071004Sound Tigers1Sags0BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
152 - 2024-03-091014Senators2Sags3BWSommaire du match
155 - 2024-03-121035Sags2Phantoms3ALXSommaire du match
157 - 2024-03-141051Sags2Manchots5ALSommaire du match
159 - 2024-03-161066Sags3Monsters2AWXXSommaire du match
160 - 2024-03-171075Sags1Baby Hawks4ALSommaire du match
162 - 2024-03-191088Sags2Chill3ALSommaire du match
164 - 2024-03-211108Thunder1Sags3BWSommaire du match
166 - 2024-03-231122Baby Hawks3Sags2BLSommaire du match
169 - 2024-03-261147Stars1Sags2BWSommaire du match
171 - 2024-03-281156Sags4Minnesota0AWSommaire du match
173 - 2024-03-301177Sags-Chiefs-
175 - 2024-04-011188Seattle-Sags-
178 - 2024-04-041210Monarchs-Sags-
180 - 2024-04-061221Chiefs-Sags-
181 - 2024-04-071231Jayhawks-Sags-
183 - 2024-04-091251Heat-Sags-
185 - 2024-04-111263Sags-Seattle-
187 - 2024-04-131282Minnesota-Sags-
189 - 2024-04-151294Sags-Oil Kings-
192 - 2024-04-181309Sags-Heat-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité17501250
Prix des billets5020
Assistance38,51929,545
Assistance PCT62.89%67.53%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
6 1945 - 64.82% 86,292$3,020,220$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,575,074$ 1,769,166$ 1,769,166$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,214$ 1,575,074$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
517,752$ 21 9,214$ 193,494$




Sags 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

Sags 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

Sags 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

Sags 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

Sags 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