Connexion

Sags
GP: 82 | W: 36 | L: 39 | OTL: 7 | P: 79
GF: 165 | GA: 166 | PP%: 14.94% | PK%: 82.87%
DG: Nick Gagnon | Morale : 50 | Moyenne d’équipe : 59
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Centre de jeu
Sags
36-39-7, 79pts
0
FINAL
2 Oil Kings
34-38-10, 78pts
Team Stats
W1SéquenceW1
20-20-1Fiche domicile19-17-5
16-19-6Fiche domicile15-21-5
4-5-1Derniers 10 matchs6-4-0
2.01Buts par match 2.30
2.02Buts contre par match 2.50
14.94%Pourcentage en avantage numérique14.60%
82.87%Pourcentage en désavantage numérique83.18%
Sags
36-39-7, 79pts
3
FINAL
2 Heat
28-49-5, 61pts
Team Stats
W1SéquenceL2
20-20-1Fiche domicile15-24-2
16-19-6Fiche domicile13-25-3
4-5-1Derniers 10 matchs3-6-1
2.01Buts par match 2.05
2.02Buts contre par match 2.89
14.94%Pourcentage en avantage numérique16.59%
82.87%Pourcentage en désavantage numérique82.99%
Meneurs d'équipe
Buts
Alex Turcotte
20
Passes
Henry Thrun
33
Points
Henry Thrun
45
Plus/Moins
Anttoni Honka
9
Victoires
Malcolm Subban
35
Pourcentage d’arrêts
Dryden McKay
0.962

Statistiques d’équipe
Buts pour
165
2.01 GFG
Tirs pour
1473
17.96 Avg
Pourcentage en avantage numérique
14.9%
36 GF
Début de zone offensive
39.1%
Buts contre
166
2.02 GAA
Tirs contre
1481
18.06 Avg
Pourcentage en désavantage numérique
82.9%%
37 GA
Début de la zone défensive
39.2%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance1,946
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)D801233452200959695336512.63%71182622.836121862224101117821100.00%100000.4901000081
2Jiri KulichSags (San)C/LW801423371320117911344311210.45%18173121.640552019702221532239.63%43400000.4359000255
3Tyler BensonSags (San)LW/RW80142236428012672133187810.53%7159019.894593118400041161146.22%11900000.4548000603
4Wyatt KalynukSags (San)D8072431-6500121977520459.33%61153419.197411551870110137000%000000.4011000202
5Alex TurcotteSags (San)C82209296360115134114228917.54%12144017.571016720002466350.14%110900000.4004000540
6Reilly WalshSags (San)D3982129-1180516347123117.02%3282221.09651130100000176210%000000.7100000405
7Jordy BelleriveSags (San)C82131629-3280113129127338610.24%11142517.391567710000292255.73%68900000.4102000222
8Ty TullioSags (San)RW801118294180657511843809.32%4143117.89178201850000182240.82%9800000.4102000222
9Jack ThompsonSags (San)D8042327-628065827725525.19%56153519.20178431870110146100%000000.3501000222
10Ben MeyersSags (San)C/LW37168243405610497336116.49%1080621.80426171002133926163.19%85300100.6011000421
11Anttoni HonkaSags (San)D824192393206267439289.30%43123015.0111210380000260066.67%300000.3711000122
12Michael KesselringSags (San)D3711617039574434519392.22%3779821.580662693000066000%000000.4311100013
13Helge GransSags (San)D80511167515112473681813.89%39118414.80101311000070200%000000.2711000321
14Aatu RatySags (San)C378715-7180517765105512.31%670819.1412310800000401051.94%62000000.4201000004
15Zayde WisdomSags (San)C785813-414053565317489.43%689011.411453690000152047.09%22300000.2911000022
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 moyenne12091592914501549020145114131472397104010.80%4432185518.0835671023611979459151383341451.60%462800100.411639201383338
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)80353770.8931.90474321115014060320.61041800365
2Dryden McKaySags (San)41000.9620.57106001260001.0002080000
Statistiques d’équipe totales ou en moyenne84363770.8951.8748502111511432032438080365


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$0$0$No836,667$836,667$
Alex TurcotteSags (San)C212001-02-26Yes185 Lbs5 ft11NoNoNoNo1Pro & Farm925,000$0$0$NoLien
Anttoni HonkaSags (San)D212000-10-05Yes179 Lbs5 ft10NoNoNoNo3Pro & Farm700,000$0$0$No700,000$700,000$Lien
Ben MeyersSags (San)C/LW231998-11-15Yes194 Lbs5 ft11NoNoNoNo3Pro & Farm912,500$0$0$No912,500$912,500$
Carter SavoieSags (San)LW202002-01-23Yes192 Lbs5 ft9NoNoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$
Corson CeulemansSags (San)D192003-05-05Yes198 Lbs6 ft2NoNoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$
Demetrios KoumontzisSags (San)LW222000-03-24Yes183 Lbs5 ft10NoNoNoNo2Pro & Farm650,000$0$0$No650,000$Lien
Dryden McKaySags (San)G241997-11-25Yes183 Lbs6 ft0NoNoYesYes3Pro & Farm560,000$0$0$No560,000$560,000$
Helge GransSags (San)D202002-05-10Yes205 Lbs6 ft3NoNoNoNo3Pro & Farm847,500$0$0$No847,500$847,500$Lien
Henry ThrunSags (San)D212001-03-12Yes190 Lbs6 ft2NoNoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Jack ThompsonSags (San)D202002-03-19Yes179 Lbs6 ft0NoNoNoNo3Pro & Farm828,333$0$0$No828,333$828,333$
Jiri KulichSags (San)C/LW182004-04-14Yes179 Lbs5 ft11NoNoNoNo3Pro & Farm950,000$0$0$No950,000$950,000$
Jordy BelleriveSags (San)C231999-05-02No194 Lbs5 ft11NoNoNoNo2Pro & Farm733,333$0$0$No733,333$Lien
Malcolm Subban (contrat à 1 volet)Sags (San)G281993-12-21No216 Lbs6 ft2NoNoYesYes2Pro & Farm1,500,000$600,000$0$No1,500,000$Lien
Michael KesselringSags (San)D222000-01-13Yes190 Lbs6 ft4NoNoNoNo1Pro & Farm1,100,000$0$0$NoLien
Michal TeplySags (San)LW212001-05-27Yes187 Lbs6 ft3NoNoNoNo1Pro & Farm825,833$0$0$NoLien
Philippe DaoustSags (San)LW202001-11-05Yes150 Lbs6 ft0NoNoNoNo5Pro & Farm600,000$0$0$No600,000$600,000$600,000$600,000$Lien
Reilly WalshSags (San)D231999-04-21No185 Lbs6 ft0NoNoNoNo1Pro & Farm700,000$0$0$NoLien
Rory KerinsSags (San)C202002-04-12Yes185 Lbs6 ft0NoNoNoNo3Pro & Farm846,667$0$0$No846,667$846,667$
Ty TullioSags (San)RW202002-04-05Yes165 Lbs5 ft10NoNoNoNo3Pro & Farm833,333$0$0$No833,333$833,333$
Tyler BensonSags (San)LW/RW241998-03-15No190 Lbs6 ft0NoNoYesYes2Pro & Farm620,000$0$0$No620,000$Lien
Wyatt KalynukSags (San)D251997-04-14No181 Lbs6 ft1NoNoYesYes2Pro & Farm925,000$0$0$No925,000$Lien
Zayde WisdomSags (San)C202002-05-20Yes194 Lbs5 ft11NoNoNoNo3Pro & Farm797,500$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
1Admirals422000001064211000008442110000022040.500101828014557571873498489474568722336314214.29%15380.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
2Baby Hawks30300000511-61010000023-12020000038-500.0005101500455757184549848947456532712601119.09%6266.67%1994202849.01%1014203349.88%550112748.80%2033142619085801034526
3Bears21001000413110000002021000100021141.000481201455757183849848947456228437900.00%10100.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
4Bruins2010000146-21010000034-11000000112-110.250481200455757183149848947456421114347228.57%6350.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
5Cabaret Lady Mary Ann21000001752110000004131000000134-130.750712190045575718484984894745625116298225.00%30100.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
6Caroline21100000330110000002021010000013-220.500358114557571827498489474563251044500.00%5180.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
7Chiefs3120000024-2211000002111010000003-320.3332460145575718444984894745638917531119.09%6266.67%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
8Chill31101000651100010001012110000055040.66761117014557571850498489474563923145910330.00%6183.33%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
9Comets4130000079-2211000006422020000015-420.25071320104557571878498489474566518226114214.29%9188.89%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
10Cougars22000000936110000005141100000042241.0009172600455757182949848947456551016366233.33%8187.50%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
11Crunch21100000862110000004131010000045-120.500815230045575718484984894745645141041800.00%5260.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
12Heat33000000633110000001012200000053261.00061117014557571854498489474563396615360.00%3166.67%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
13Jayhawks3210000011742200000010461010000013-240.66711213200455757188049848947456611616663133.33%80100.00%1994202849.01%1014203349.88%550112748.80%2033142619085801034526
14Las Vegas412000108802020000036-32100001052340.5008111901455757186749848947456712324745120.00%9188.89%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
15Manchots2110000057-2110000003211010000025-320.5005101500455757183849848947456321014267114.29%60100.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
16Marlies2020000014-31010000012-11010000002-200.000123004557571829498489474563981236700.00%4175.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
17Minnesota311001006511010000002-22100010063330.5006101601455757185949848947456671714548225.00%70100.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
18Monarchs4040000049-52020000025-32020000024-200.00048120045575718664984894745673172679800.00%11281.82%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
19Monsters21000010532110000002111000001032141.000581300455757183549848947456301314374125.00%7185.71%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
20Monsters3120000048-41010000004-42110000044020.333481200455757184649848947456652684411436.36%4250.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
21Oceanics30200010810-22020000036-31000001054120.33381220004557571851498489474566615184912325.00%7271.43%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
22Oil Kings31100010541210000105231010000002-240.66757120145575718624984894745653221266500.00%5180.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
23Phantoms2010010025-31010000002-21000010023-110.2502460045575718314984894745640112043700.00%10190.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
24Rocket2010000135-21010000001-11000000134-110.2503690045575718364984894745646102832400.00%12283.33%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
25Seattle4020000248-42010000135-22010000113-220.250481200455757187549848947456743426741218.33%120100.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
26Senators21100000330110000003211010000001-120.5003470045575718494984894745632916327114.29%7185.71%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
27Sound Tigers211000002111010000001-11100000020220.50024601455757183849848947456207834600.00%30100.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
28Spiders2110000023-11010000002-21100000021120.50023500455757182449848947456411710365120.00%50100.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
29Stars3210000011832110000056-11100000062440.667112031004557571851498489474566126264814214.29%13469.23%1994202849.01%1014203349.88%550112748.80%2033142619085801034526
30Thunder22000000725110000003121100000041341.000713200045575718414984894745639181238300.00%60100.00%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
31Wolf Pack2110000034-1110000002111010000013-220.5003580045575718304984894745635121436500.00%7271.43%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
Total82303902245165166-141182001011857411411219012348092-12790.48216529646121045575718147349848947456148147848214822413614.94%2163782.87%3994202849.01%1014203349.88%550112748.80%2033142619085801034526
_Since Last GM Reset82303902245165166-141182001011857411411219012348092-12790.48216529646121045575718147349848947456148147848214822413614.94%2163782.87%3994202849.01%1014203349.88%550112748.80%2033142619085801034526
_Vs Conference361218021216669-31871001000333301858011213336-3340.472661181840445575718624498489474566372012296391111412.61%1011783.17%0994202849.01%1014203349.88%550112748.80%2033142619085801034526
_Vs Division16110010114234880601000231310814000111921-270.21942771190045575718311498489474563239111427850714.00%511080.39%0994202849.01%1014203349.88%550112748.80%2033142619085801034526

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8279W1165296461147314814784821482210
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8230392245165166
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
41182010118574
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
41121912348092
Derniers 10 matchs
WLOTWOTL SOWSOL
450001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2413614.94%2163782.87%3
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
4984894745645575718
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
994202849.01%1014203349.88%550112748.80%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2033142619085801034526


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 - 2024-03-301177Sags0Chiefs3ALSommaire du match
175 - 2024-04-011188Seattle4Sags3BLXXSommaire du match
178 - 2024-04-041210Monarchs2Sags1BLSommaire du match
180 - 2024-04-061221Chiefs0Sags2BWSommaire du match
181 - 2024-04-071231Jayhawks2Sags6BWSommaire du match
183 - 2024-04-091251Heat0Sags1BWSommaire du match
185 - 2024-04-111263Sags1Seattle2ALSommaire du match
187 - 2024-04-131282Minnesota2Sags0BLSommaire du match
189 - 2024-04-151294Sags0Oil Kings2ALSommaire du match
192 - 2024-04-181309Sags3Heat2AWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité17501250
Prix des billets5020
Assistance45,06934,703
Assistance PCT62.81%67.71%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 1946 - 64.86% 86,269$3,537,012$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,768,568$ 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$ 1,768,568$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 9,214$ 0$




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