Day : 77
NYI - 1
BOS - 3
VEG - 4
MTL - 3
NSH - 3
CAR - 2
TOR - 2
NJD - 0
BUF - 3
NYR - 0
DET - 2
WSH - 7
COL - 2
WPG - 5
DAL - 1
ANH - 5
TBL - 2
LOS - 3
UTA - 0
SJS - 2
STL - 5
MIN - 2
MIL - 0
TRL - 1
GAT - 4
BNG - 5
GRG - 5
BRI - 1
PAR - 0
PRO - 5
SJS - 4
NOR - 2
CHA - 3
LAV - 1
Day : 78
(29-7-3) - W2
(8-28-4) - L3
(18-17-4) - W1
(28-4-3) - W3
(26-10-1) - W3
(25-6-5) - W2
(17-18-4) - W2
(17-18-2) - W1
(20-15-3) - SOL1
(21-12-4) - L2
(19-16-4) - L1
(18-19-0) - L2
(12-26-0) - L10
(12-19-3) - L4
(22-11-3) - L2
(22-10-1) - L1
(13-17-5) - L2
(13-16-4) - L2
(14-19-3) - L1
(14-10-4) - W4
(18-13-4) - W3
(18-14-2) - W1
(11-21-4) - L2
(11-9-2) - W1
(20-17-2) - W1
(20-12-2) - W4
(12-23-1) - W1
(12-16-5) - W1
(28-10-0) - W2
(28-16-5) - L1
(17-17-2) - L1
(17-18-2) - W5

Connecticut Whale
GP: 36 | W: 22 | L: 11 | OTL: 3 | P: 47
GF: 144 | GA: 122 | PP%: 21.85% | PK%: 83.76%
DG: Francis Bérubé | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #598 vs Wilkes-Barre/Scranton Penguins
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Centre de jeu
Connecticut Whale
22-11-3, 47pts
2
FINAL
8 Milwaukee Admirals
27-4-5, 59pts
Team Stats
L2SéquenceL1
12-4-2Fiche domicile15-1-2
10-7-1Fiche domicile12-3-3
4-5-1Derniers 10 matchs7-1-2
4.00Buts par match 4.67
3.39Buts contre par match 2.97
21.85%Pourcentage en avantage numérique30.00%
83.76%Pourcentage en désavantage numérique84.33%
Norfolk Admirals
13-17-4, 30pts
6
FINAL
4 Connecticut Whale
22-11-3, 47pts
Team Stats
L1SéquenceL2
7-10-2Fiche domicile12-4-2
6-7-2Fiche domicile10-7-1
7-3-0Derniers 10 matchs4-5-1
3.21Buts par match 4.00
3.76Buts contre par match 3.39
18.40%Pourcentage en avantage numérique21.85%
70.77%Pourcentage en désavantage numérique83.76%
Connecticut Whale
22-11-3, 47pts
Jour 78
Wilkes-Barre/Scranton Penguins
23-10-1, 47pts
Statistiques d’équipe
L2SéquenceL1
12-4-2Fiche domicile14-3-1
10-7-1Fiche visiteur9-7-0
4-5-110 derniers matchs8-2-0
4.00Buts par match 4.76
3.39Buts contre par match 4.76
21.85%Pourcentage en avantage numérique33.63%
83.76%Pourcentage en désavantage numérique75.44%
Lake Erie Monsters
12-22-3, 27pts
Jour 81
Connecticut Whale
22-11-3, 47pts
Statistiques d’équipe
L1SéquenceL2
7-11-0Fiche domicile12-4-2
5-11-3Fiche visiteur10-7-1
3-5-210 derniers matchs4-5-1
3.73Buts par match 4.00
4.78Buts contre par match 4.00
22.48%Pourcentage en avantage numérique21.85%
70.64%Pourcentage en désavantage numérique83.76%
Connecticut Whale
22-11-3, 47pts
Jour 83
Rochester Americans
21-12-2, 44pts
Statistiques d’équipe
L2SéquenceW4
12-4-2Fiche domicile12-6-0
10-7-1Fiche visiteur9-6-2
4-5-110 derniers matchs7-2-1
4.00Buts par match 4.11
3.39Buts contre par match 4.11
21.85%Pourcentage en avantage numérique33.58%
83.76%Pourcentage en désavantage numérique81.65%
Meneurs d'équipe
Buts
Nick Robertson
25
Passes
Ryan Strome
25
Points
Nick Robertson
44
Plus/Moins
Dominik Bokk
15
Victoires
Felix Sandström
13
Pourcentage d’arrêts
Clay Stevenson
0.891

Statistiques d’équipe
Buts pour
144
4.00 GFG
Tirs pour
1166
32.39 Avg
Pourcentage en avantage numérique
21.8%
26 GF
Début de zone offensive
36.2%
Buts contre
122
3.39 GAA
Tirs contre
1084
30.11 Avg
Pourcentage en désavantage numérique
83.8%%
19 GA
Début de la zone défensive
36.8%
Informations de l'équipe

Directeur généralFrancis Bérubé
EntraîneurDave Hakstol
DivisionNilan
ConférenceFortunus
CapitaineMattias Ekholm
Assistant #1Jonathan Audy-Marchessault
Assistant #2Nick Robertson


Informations de l’aréna

Capacité3,000
Assistance2,977
Billets de saison300


Informations de la formation

Équipe Pro23
Équipe Mineure20
Limite contact 43 / 50
Espoirs38


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
1Walker DuehrX100.00865077798680817873747570757578650002731,500,000$
2Lauri Pajuniemi (R)X100.0072308278817781787273726883747155000252950,000$
3Aidan Dudas (R)X100.0067378479718176757171707371687865000242850,000$
4Cam Hillis (R)X100.0062308077668167757469687171637255000242850,000$
5Glenn GawdinXX100.00824081798083837971727269717575550002731,050,000$
6Marcus Sylvegård (R)X100.0083307383828381797174736879706865000251950,000$
7Nick Robertson (R) (A)X100.00712595817683778475767768837572750002311,500,000$
8Dakota JoshuaX100.00814081798182828075747369737779550002811,200,000$
9Ryan StromeXX100.0071338683778379857673746584999915000311950,000$
10Jonathan Audy-Marchessault (A)XXX100.0070358576727673757671726676899215000341900,000$
11Trent FredericXX100.00884078818683808073727368727070650002631,500,000$
12Dominik Bokk (R)XX100.00733396847986808364757566767677750002412,000,000$
13Drew Helleson (R)X100.0077257476818581765074678564727565000233850,000$
14Scott Walford (R)X100.00914476768884837750746787637685650002511,250,000$
15Vladislav GavrikovX100.00864088778682817850736788608577550002911,900,000$
16Mattias Ekholm (C)X100.00773388737875727550716486609191705000341950,000$
17Filip Westerlund (R)X100.0066358776727964745067628355656455000252800,000$
18Josh MahuraX99.78793381808180717950756587637876650002611,600,000$
Rayé
1Michael Brandsegg-Nygard (R)X85.1773257876807878756871706473646075000193950,000$
2William LagessonX100.00884578768580727650716486617876550002811,500,000$
MOYENNE D’ÉQUIPE99.207735827879817778647370747176779500
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
1Stuart Skinner (R)100.00858384868586858685868579736500N02621,467,000$
2Clay Stevenson (R)100.008383848787868785868585717085000251850,000$
3Felix Sandström100.0085818484888787888788867071850002732,000,000$
Rayé
MOYENNE D’ÉQUIPE100.00848284868786868686868573717500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dave Hakstol83848282848270USA5531,500,000$


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 POSGP 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
1Nick RobertsonLW3625194412002516111417022.52%754715.20941330112000056157.14%49606001.6102000334
2Dominik BokkLW/RW3622204215202718104365921.15%556615.7427925112000004142.31%26542011.4800000534
3Ryan StromeC/RW361325381240202786415015.12%453814.973692594000132052.04%392557011.4102000242
4JJ PeterkaC/LW/RW221322351320151355283823.64%735015.9256111370000151145.10%102501012.0002000330
5Walker DuehrRW36722297220722964194110.94%1866518.50145128600041370162.86%35308000.8700000111
6Dakota JoshuaC36121325980692984215414.29%856415.6941515860222321154.74%369394000.8900000132
7Trent FredericC/LW331010207180371777254012.99%443813.28011061012261040.00%25346000.9100000011
8Scott WalfordD3621719-638096845917193.39%5985223.690336771123114100.00%0436000.4500000121
9Marcus SylvegårdRW36117182160541767263616.42%844912.4900012000001053.33%15463000.8000000120
10Lauri PajuniemiRW3610717-3100302164225215.63%842411.7800000000000240.91%22368000.8000000001
11Glenn GawdinC/RW3651015-36052307125487.04%651414.29000001011382047.16%229386000.5800000102
12Drew HellesonD3311314-116041453617182.78%2656017.000779103000062000.00%0328000.5000000100
13Michael Brandsegg-NygardRW2431013110020152981810.34%537915.80279569000000042.31%26164000.6900000000
14Vladislav GavrikovD291101196046583719202.70%5161021.07011330000150000.00%0433000.3600000001
15Declan ChisholmD282911-116028363317236.06%2752818.87134992000153100.00%0524000.4200000000
16Aidan DudasC361910-48019605612361.79%1361817.1800082401161531050.74%5423210000.3200000000
17Jonathan Audy-MarchessaultC/LW/RW36448-154030135218397.69%043412.0800000000000060.87%23524000.3700000100
18Josh MahuraD341781226036624317222.33%5373021.47112748000152100.00%0144000.2200000001
19Mattias EkholmD20156460153119585.26%2934717.36022741011058000.00%0123000.3500000000
20William LagessonD1723541603034197810.53%2430918.1900013000018010.00%0015000.3200000001
21Cam HillisC19134-7606101210108.33%31779.3400000000010040.16%12281000.4500000000
22Filip WesterlundD25033900746171290.00%2641716.710000000000000.00%0011000.1400000000
Statistiques d’équipe totales ou en moyenne680147248395762400775711119544371812.30%3911102716.2228538117610623582381422850.43%1977568284030.7206000202221
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
1Felix SandströmConnecticut Whale (NYR)2113420.8883.2211744063563282000.60051816100
2Clay StevensonConnecticut Whale (NYR)157510.8913.307640042387199000.00001420000
3Stuart SkinnerConnecticut Whale (NYR)42200.8883.75240001513470100.000040000
Statistiques d’équipe totales ou en moyenne40221130.8893.3021794012010845511053636100


Nom du joueur POS Âge Date de naissance Termes Contrat Cap % Année 2024Année 2025Année 2026Année 2027Année 2028Année 2029Année 2030
Attaquant
Aidan DudasC242000-01-02TW 20.00%850,000$850,000$RFA ( Groupe: 2 ) [Age: 26]
Cam HillisC242000-01-02TW 20.00%850,000$850,000$RFA ( Groupe: 2 ) [Age: 26]
Dakota JoshuaC281996-01-02TW 10.00%1,200,000$UFA [Age: 29]
Dominik BokkLW/RW242000-01-22TW 10.00%2,000,000$RFA ( Groupe: 2 ) [Age: 25]
Glenn GawdinC/RW271997-01-02TW 30.00%1,050,000$1,050,000$1,050,000$UFA [Age: 30]
Jonathan Audy-MarchessaultC/LW/RW341990-01-22TW 10.00%900,000$UFA [Age: 35]
Lauri PajuniemiRW251999-01-02TW 20.00%950,000$950,000$RFA ( Groupe: 2 ) [Age: 27]
Marcus SylvegårdRW251999-01-02TW 10.00%950,000$RFA ( Groupe: 2 ) [Age: 26]
Michael Brandsegg-NygardRW192005-01-02IN TW 30.00%950,000$950,000$950,000$RFA ( Groupe: 1 )[Age: 22]
Nick RobertsonLW232001-01-02TW 10.00%1,500,000$RFA ( Groupe: 2 ) [Age: 24]
Ryan StromeC/RW311993-01-22TW 10.00%950,000$UFA [Age: 32]
Trent FredericC/LW261998-01-22TW 30.00%1,500,000$1,500,000$1,500,000$UFA [Age: 29]
Walker DuehrRW271997-01-02TW 30.00%1,500,000$1,500,000$1,500,000$UFA [Age: 30]
MOYENNE (13)25.920.00%0$7,650,000$5,000,000$0$0$0$0$
Défenseur
Drew HellesonD232001-01-02TW 30.00%850,000$850,000$850,000$RFA ( Groupe: 2 ) [Age: 26]
Filip WesterlundD251999-01-22TW 20.00%800,000$800,000$RFA ( Groupe: 2 ) [Age: 27]
Josh MahuraD261998-01-22TW 10.00%1,600,000$RFA ( Groupe: 2 ) [Age: 27]
Mattias EkholmD341990-01-22TW 10.00%950,000$UFA [Age: 35]
Scott WalfordD251999-01-22TW 10.00%1,250,000$RFA ( Groupe: 2 ) [Age: 26]
Vladislav GavrikovD291995-01-02TW 10.00%1,900,000$UFA [Age: 30]
William LagessonD281996-01-02TW 10.00%1,500,000$UFA [Age: 29]
MOYENNE (7)27.140.00%0$1,650,000$850,000$0$0$0$0$
Gardiens
Clay StevensonG251999-01-02TW 10.00%850,000$RFA ( Groupe: 2 ) [Age: 26]
Felix SandströmG271997-01-22TW 30.00%2,000,000$2,000,000$2,000,000$UFA [Age: 30]
Stuart SkinnerG261998-01-02NT TW 20.00%1,467,000$1,467,000$UFA [Age: 28]

Légendes des Termes : FV = Ballotage forcé / NT = Non-échange / IN = Blessure / TW = Contract Deux Côté ('Can Play Pro' + 'Can Play Farm')

Note: Les montants de cap salarial pour l’année courant et le % de cap salariale sont basé sur un calcul du plafond salariale simple (Salaire Moyen ou Salaire de l’année selon vos options). Si votre plafond salarial est basé sur la calcul complexe, les résultats de cette analyse pourrait être légèrement incorrects. Le plafond salarial professionnel de l’année en cours est : 89,000,050$.




Attaque à 5 contre 5
Ligne # Ailier gauche Centre Ailier droit % temps PHY DF OF
1Nick RobertsonRyan StromeWalker Duehr25113
2Dominik BokkDakota JoshuaMarcus Sylvegård25122
3Trent FredericAidan DudasLauri Pajuniemi25122
4Jonathan Audy-MarchessaultCam HillisGlenn Gawdin25122
Défense à 5 contre 5
Ligne # Défense Défense % temps PHY DF OF
1Josh MahuraMattias Ekholm25122
2Drew HellesonScott Walford25122
3Filip WesterlundVladislav Gavrikov25122
4Scott WalfordJosh Mahura25122
Attaque en avantage numérique
Ligne # Ailier gauche Centre Ailier droit % temps PHY DF OF
1Nick RobertsonRyan StromeDominik Bokk60122
2Aidan DudasDakota JoshuaWalker Duehr40122
Défense en avantage numérique
Ligne # Défense Défense % temps PHY DF OF
1Drew HellesonMattias Ekholm60122
2Scott WalfordJosh Mahura40122
Attaque à 4 en désavantage numérique
Ligne # Centre Ailier % temps PHY DF OF
1Aidan DudasWalker Duehr60122
2Dakota JoshuaRyan Strome40122
Défense à 4 en désavantage numérique
Ligne # Défense Défense % temps PHY DF OF
1Mattias EkholmScott Walford60122
2Josh MahuraDrew Helleson40122
3 joueurs en désavantage numérique
Ligne # Ailier % temps PHY DF OF Défense Défense % temps PHY DF OF
1Aidan Dudas60122Mattias EkholmScott Walford60122
2Walker Duehr40122Josh MahuraDrew Helleson40122
Attaque à 4 contre 4
Ligne # Centre Ailier % temps PHY DF OF
1Walker DuehrMarcus Sylvegård60122
2Aidan DudasLauri Pajuniemi40122
Défense à 4 contre 4
Ligne # Défense Défense % temps PHY DF OF
1Josh MahuraDrew Helleson60122
2Scott WalfordMattias Ekholm40122
Attaque dernière minute
Ailier gauche Centre Ailier droit Défense Défense
Nick RobertsonRyan StromeDominik BokkDrew HellesonMattias Ekholm
Défense dernière minute
Ailier gauche Centre Ailier droit Défense Défense
Ryan StromeAidan DudasWalker DuehrDrew HellesonScott Walford
Attaquants supplémentaires
Normal Avantage numérique Désavantage numérique
Dominik Bokk, Nick Robertson, Walker DuehrMarcus Sylvegård, Lauri PajuniemiGlenn Gawdin
Défenseurs supplémentaires
Normal Avantage numérique Désavantage numérique
Drew Helleson, Josh Mahura, Scott WalfordJosh MahuraMattias Ekholm, Drew Helleson
Tirs de pénalité
Ryan Strome, Nick Robertson, Dominik Bokk, Lauri Pajuniemi, Marcus Sylvegård
Gardien
#1 : Felix Sandström, #2 : Clay Stevenson, #3 : Stuart Skinner
Lignes d’attaque personnalisées en prolongation
Nick Robertson, Dominik Bokk, Walker Duehr, Marcus Sylvegård, Ryan Strome, Dakota Joshua, Dakota Joshua, Lauri Pajuniemi, Jonathan Audy-Marchessault, Aidan Dudas, Glenn Gawdin
Lignes de défense personnalisées en prolongation
Josh Mahura, Drew Helleson, Mattias Ekholm, Scott Walford, Vladislav Gavrikov


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
1Blainville-Boisbriand Armada20100001412-80000000000020100001412-810.25047110053394756739239236919722818414125.00%9455.56%035569850.86%37570952.89%25652149.14%842550793285543271
2Bridgeport Sound Tigers33000000155101100000051422000000104661.00015223700533947510439239236919712712558112.50%60100.00%035569850.86%37570952.89%25652149.14%842550793285543271
3Charlotte Checkers1010000035-2000000000001010000035-200.00035800533947529392392369193313419100.00%20100.00%035569850.86%37570952.89%25652149.14%842550793285543271
4Chicago Wolves2200000010552200000010550000000000041.0001017270053394757439239236919551518398112.50%9188.89%035569850.86%37570952.89%25652149.14%842550793285543271
5Chisinau Pelicans10001000431000000000001000100043121.000461000533947531392392369193121620300.00%30100.00%035569850.86%37570952.89%25652149.14%842550793285543271
6Danbury Trashers5410000024121233000000176112110000076180.80024416500533947517039239236919135503611918738.89%18288.89%135569850.86%37570952.89%25652149.14%842550793285543271
7Gatineau Olympiques1000010034-11000010034-10000000000010.5003360053394754039239236919307426400.00%20100.00%035569850.86%37570952.89%25652149.14%842550793285543271
8Grand Rapids Griffins11000000431110000004310000000000021.0004812005339475353923923691930132256233.33%10100.00%035569850.86%37570952.89%25652149.14%842550793285543271
9Hamilton Bulldogs11000000211000000000001100000021121.00024600533947525392392369192786176116.67%30100.00%035569850.86%37570952.89%25652149.14%842550793285543271
10Joliette Sportif11000000523110000005230000000000021.0005611005339475293923923691932134243133.33%2150.00%035569850.86%37570952.89%25652149.14%842550793285543271
11Lake Erie Monsters10001000541100010005410000000000021.0005611005339475263923923691938111422200.00%7185.71%035569850.86%37570952.89%25652149.14%842550793285543271
12Manitoba Moose522010001917211000000633412010001314-160.6001933520053394751393923923691915454329819315.79%16381.25%035569850.86%37570952.89%25652149.14%842550793285543271
13Milwaukee Admirals1010000028-6000000000001010000028-600.00024600533947540392392369193112824300.00%4250.00%035569850.86%37570952.89%25652149.14%842550793285543271
14Norfolk Admirals31200000141221010000046-221100000106420.333142337005339475102392392369198423205411436.36%10280.00%035569850.86%37570952.89%25652149.14%842550793285543271
15Portland Crying Chiwawas10001000431000000000001000100043121.000461000533947525392392369194115425100.00%20100.00%035569850.86%37570952.89%25652149.14%842550793285543271
16Providence Bruins2010000168-22010000168-20000000000010.250611170053394757139239236919622418474125.00%9277.78%035569850.86%37570952.89%25652149.14%842550793285543271
17Quebec Stars1010000025-31010000025-30000000000000.00023500533947526392392369193611213300.00%10100.00%035569850.86%37570952.89%25652149.14%842550793285543271
18Springfield Falcons1010000025-31010000025-30000000000000.0002460053394753039239236919356223200.00%10100.00%035569850.86%37570952.89%25652149.14%842550793285543271
19The Nuuk Vikings11000000422000000000001100000042221.0004812005339475313923923691928138224125.00%40100.00%135569850.86%37570952.89%25652149.14%842550793285543271
20Trois-Rivières Lions2100100012662100100012660000000000041.0001221330053394757239239236919592216429333.33%8187.50%135569850.86%37570952.89%25652149.14%842550793285543271
Total361711051021441222218104021018158231877030016364-1470.65314423838200533947511663923923691910843862347551192621.85%1171983.76%335569850.86%37570952.89%25652149.14%842550793285543271
_Since Last GM Reset361711051021441222218104021018158231877030016364-1470.65314423838200533947511663923923691910843862347551192621.85%1171983.76%335569850.86%37570952.89%25652149.14%842550793285543271
_Vs Conference21108020018767209530000140291112550200047389250.5958714523200533947567039239236919615212128440641625.00%64985.94%135569850.86%37570952.89%25652149.14%842550793285543271
_Vs Division1173000013649-134420000117152731000001934-15150.682366197005339475333392392369193611297622337616.22%381073.68%035569850.86%37570952.89%25652149.14%842550793285543271

Total pour les joueurs
Matchs joués Points Séquence Buts Passes Points Tirs pour Tirs contre Tirs bloqués Minutes de pénalités Mises en échec Buts en filet désert Blanchissages
3647L21442383821166108438623475500
Tous les matchs
GP W L OTW OTL SOWSOL GF GA
3617115102144122
Matchs locaux
GP W L OTW OTL SOWSOL GF GA
1810421018158
Matchs extérieurs
GP W L OTW OTL SOWSOL GF GA
187730016364
Derniers 10 matchs
W L OTW OTL SOWSOL
450100
Tentatives en avantage numérique Buts en avantage numérique % en avantage numérique Tentatives en désavantage numérique Buts contre en désavantage numérique % en désavantage numérique Buts pour en désavantage numérique
1192621.85%1171983.76%3
Tirs en 1e période Tirs en 2e période Tirs en 3e période Tirs en 4e période Buts en 1e période Buts en 2e période Buts en 3e période Buts en 4e période
392392369195339475
Mises en jeu
Gagnées en zone offensive Total en zone offensive % gagnées en zone offensive Gagnées en zone défensive Total en zone défensive % gagnées en zone défensive Gagnées en zone neutre Total en zone neutre % gagnées en zone neutre
35569850.86%37570952.89%25652149.14%
Temps avec la rondelle
En zone offensive Contrôle en zone offensive En zone défensive Contrôle en zone défensive En zone neutre Contrôle en zone neutre
842550793285543271


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
Jour:1
17Connecticut Whale1Norfolk Admirals3LSommaire du match
Jour:2
222Trois-Rivières Lions3Connecticut Whale8WSommaire du match
Jour:5
537Connecticut Whale4Manitoba Moose3WXSommaire du match
Jour:8
859Lake Erie Monsters4Connecticut Whale5WXSommaire du match
Jour:11
1175Danbury Trashers3Connecticut Whale8WSommaire du match
Jour:14
1494Connecticut Whale2Blainville-Boisbriand Armada9LSommaire du match
Jour:15
1599Connecticut Whale1Manitoba Moose4LSommaire du match
Jour:18
18122Grand Rapids Griffins3Connecticut Whale4WSommaire du match
Jour:20
20136Connecticut Whale3Bridgeport Sound Tigers2WSommaire du match
Jour:21
21148Connecticut Whale9Norfolk Admirals3WSommaire du match
Jour:23
23163Trois-Rivières Lions3Connecticut Whale4WXSommaire du match
Jour:25
25185Connecticut Whale2Blainville-Boisbriand Armada3LXXSommaire du match
Jour:27
27200Danbury Trashers2Connecticut Whale5WSommaire du match
Jour:28
28217Bridgeport Sound Tigers1Connecticut Whale5WSommaire du match
Jour:30
30230Connecticut Whale4Chisinau Pelicans3WXSommaire du match
Jour:32
32251Danbury Trashers1Connecticut Whale4WSommaire du match
Jour:37
37268Connecticut Whale2Manitoba Moose3LSommaire du match
Jour:39
39285Providence Bruins6Connecticut Whale5LXXSommaire du match
Jour:41
41301Connecticut Whale6Manitoba Moose4WSommaire du match
Jour:43
43315Connecticut Whale4Danbury Trashers2WSommaire du match
Jour:44
44324Springfield Falcons5Connecticut Whale2LSommaire du match
Jour:46
46346Chicago Wolves4Connecticut Whale6WSommaire du match
Jour:49
49365Connecticut Whale4The Nuuk Vikings2WSommaire du match
Jour:51
51382Manitoba Moose3Connecticut Whale6WSommaire du match
Jour:54
54411Providence Bruins2Connecticut Whale1LSommaire du match
Jour:56
56424Connecticut Whale7Bridgeport Sound Tigers2WSommaire du match
Jour:57
57441Connecticut Whale3Charlotte Checkers5LSommaire du match
Jour:59
59453Connecticut Whale3Danbury Trashers4LSommaire du match
Jour:60
60459Quebec Stars5Connecticut Whale2LSommaire du match
Jour:62
62483Joliette Sportif2Connecticut Whale5WSommaire du match
Jour:65
65501Connecticut Whale2Hamilton Bulldogs1WSommaire du match
Jour:68
68514Chicago Wolves1Connecticut Whale4WSommaire du match
Jour:70
70536Connecticut Whale4Portland Crying Chiwawas3WXSommaire du match
Jour:71
71548Gatineau Olympiques4Connecticut Whale3LXSommaire du match
Jour:73
73568Connecticut Whale2Milwaukee Admirals8LSommaire du match
Jour:75
75580Norfolk Admirals6Connecticut Whale4LSommaire du match
Jour:78
78598Connecticut Whale-Wilkes-Barre/Scranton Penguins-
Jour:81
81616Lake Erie Monsters-Connecticut Whale-
Jour:83
83633Connecticut Whale-Rochester Americans-
Jour:85
85647Henderson Silver Knights-Connecticut Whale-
Jour:89
89669Connecticut Whale-Verdun Junior-
Jour:91
91681Verdun Junior-Connecticut Whale-
Jour:93
93690Connecticut Whale-Providence Bruins-
Jour:95
95705Connecticut Whale-San Jose Barracuda-
Jour:97
97720Chisinau Pelicans-Connecticut Whale-
Jour:99
99734Connecticut Whale-Chicago Wolves-
Jour:100
100749Laval Chiefs-Connecticut Whale-
Jour:103
103771Connecticut Whale-Blainville-Boisbriand Armada-
Jour:104
104784San Antonio Rampage-Connecticut Whale-
Jour:107
107800Connecticut Whale-San Antonio Rampage-
Jour:109
109817Albany Devils-Connecticut Whale-
Jour:110
110830Connecticut Whale-Chisinau Pelicans-
Jour:112
112847Connecticut Whale-Providence Bruins-
Jour:114
114853Rochester Americans-Connecticut Whale-
Jour:117
117874Connecticut Whale-San Antonio Rampage-
Jour:118
118886Charlotte Checkers-Connecticut Whale-
Jour:122
122911Connecticut Whale-Chicoutimi Saguenéens-
Jour:124
124918Connecticut Whale-Henderson Silver Knights-
Jour:125
125928Albany Devils-Connecticut Whale-
Jour:127
127951Roberval Dwarfs-Connecticut Whale-
Jour:129
129971Connecticut Whale-Houston Aeros-
Jour:131
131985Wilkes-Barre/Scranton Penguins-Connecticut Whale-
Jour:135
1351011Grand Rapids Griffins-Connecticut Whale-
Jour:139
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1391043Houston Aeros-Connecticut Whale-
Jour:143
1431069Trois-Rivières Lions-Connecticut Whale-
Jour:144
1441073Connecticut Whale-Springfield Falcons-
Jour:149
1491101San Jose Barracuda-Connecticut Whale-
Jour:151
1511120Connecticut Whale-Bridgeport Sound Tigers-
Jour:152
1521133Lake Erie Monsters-Connecticut Whale-
Jour:156
1561162Grand Rapids Griffins-Connecticut Whale-
Jour:159
1591178Connecticut Whale-Albany Devils-
Jour:161
1611196Danbury Trashers-Connecticut Whale-
Jour:163
1631208Connecticut Whale-Springfield Falcons-
Jour:165
1651227Danbury Trashers-Connecticut Whale-
Jour:169
1691252Connecticut Whale-Binghamton Senators-
Jour:171
1711260Chicoutimi Saguenéens-Connecticut Whale-
Jour:175
1751286Connecticut Whale-Binghamton Senators-
Jour:177
1771294San Jose Barracuda-Connecticut Whale-
Jour:178
1781304Connecticut Whale-Norfolk Admirals-
Jour:180
1801323Portland Crying Chiwawas-Connecticut Whale-
Jour:182
1821330Connecticut Whale-Norfolk Admirals-
Jour:183
1831336Connecticut Whale-Albany Devils-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1 Niveau 2

Revenu
Matchs à domicile restants Assistance moyenne - % Revenu moyen par match Revenu annuel à ce jour Capacité Popularité de l’équipe

Dépenses
Dépenses annuelles à ce jour Salaire total des joueurs Salaire total moyen des joueurs Salaire des entraineurs
Plafond salarial par jour Plafond salarial à ce jour Joueurs Inclus dans le plafond salarial Joueurs exclut du plafond Salarial

Estimation
Revenus de la saison estimés Jours restants de la saison Dépenses par jour Dépenses de la saison estimées




Connecticut Whale 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

Connecticut Whale 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

Connecticut Whale Statistiques de l'Équipe de Carrière

Total Domicile Visiteur
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

Connecticut Whale 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

Connecticut Whale 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