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Connexion

Oilers
GP: 82 | W: 50 | L: 26 | OTL: 6 | P: 106
GF: 286 | GA: 245 | PP%: 21.76% | PK%: 82.53%
DG: Alain Bard | Morale : 99 | Moyenne d’équipe : 69
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Centre de jeu
Sharks
31-39-12, 74pts
2
FINAL
5 Oilers
50-26-6, 106pts
Team Stats
W1SéquenceW10
16-19-6Fiche domicile26-11-4
15-20-6Fiche domicile24-15-2
4-5-1Derniers 10 matchs10-0-0
2.88Buts par match 3.49
3.35Buts contre par match 2.99
19.42%Pourcentage en avantage numérique21.76%
79.77%Pourcentage en désavantage numérique82.53%
Oilers
50-26-6, 106pts
3
FINAL
0 Ducks
37-31-14, 88pts
Team Stats
W10SéquenceL3
26-11-4Fiche domicile18-17-6
24-15-2Fiche domicile19-14-8
10-0-0Derniers 10 matchs4-6-0
3.49Buts par match 3.00
2.99Buts contre par match 3.12
21.76%Pourcentage en avantage numérique19.35%
82.53%Pourcentage en désavantage numérique84.64%
Meneurs d'équipe
Buts
Shane Pinto
38
Passes
Trevor Zegras
49
Points
Shane Pinto
86
Plus/Moins
Dante Fabbro
32
Victoires
Jeremy Swayman
40
Pourcentage d’arrêts
Christopher Gibson
0.917

Statistiques d’équipe
Buts pour
286
3.49 GFG
Tirs pour
2762
33.68 Avg
Pourcentage en avantage numérique
21.8%
57 GF
Début de zone offensive
37.8%
Buts contre
245
2.99 GAA
Tirs contre
2651
32.33 Avg
Pourcentage en désavantage numérique
82.5%%
47 GA
Début de la zone défensive
39.3%
Informations de l'équipe

Directeur généralAlain Bard
EntraîneurJack Capuano
DivisionPacifique
ConférenceOuest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,470
Billets de saison2,100


Informations de la formation

Équipe Pro35
Équipe Mineure20
Limite contact 55 / 60
Espoirs25


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
1Charles Hudon X100.0070438871717090987498917567858647867902913,000,000$
2Kailer Yamamoto (R)X100.0077457990688784785083818125807664867602511,000,000$
3Shane Pinto (R)X100.007445888387868084787678712582615290740231925,000$
4Trevor Zegras (R)X100.007053638280888089668479602584615289730231925,000$
5Trent Frederic (R)X100.007979687587838582507475742579715986720262575,000$
6Taylor Raddysh (R)X100.007445907683867883557678672580594990720262758,333$
7Jack McBain (R)X100.008776678187857879697472752578594983721243925,000$
8Brendan Lemieux (R)X100.008378597184818169557873722569766482700281800,000$
9Kevin Rooney (R)X100.0070506970766979678566659261857926917003031,000,000$
10Ryan McLeod (R)X100.007145857687857875737271722575615290700241834,167$
11Liam Foudy (R)X100.007540917682828173406766692573665490680241894,167$
12Kiefer Sherwood (R)X100.007860647477847571456566652572715993660292700,000$
13Jake Walman (R)X100.0069556979848881824069748625796654867502832,000,000$
14Janis Moser (R)X100.006955749177917882407972812581594988752233886,667$
15Jordan Oesterle (R)X100.0065557974748484724085788525718472887403121,500,000$
16Dante Fabbro (R)X100.007551707978858576406962812574715991730252800,000$
17Victor Mete (R)X100.005540757475837166406864742568766444670251800,000$
18Vincent Desharnais (R)X100.006555627187826568406559742567534984672273762,500$
Rayé
1Dylan Holloway (R)X100.007755727485787070506663662569535037652223925,000$
2Maxim Mamin (R)X100.004525956975537770607166715173584321640291575,000$
3Josh Currie (R)X100.007129796772636063716258745176612820620313575,000$
4Tanner Fritz (R)X100.005716976572578661716254685184692319610331575,000$
5Anthony Angello (R)X100.006737976579708348666358642572685519610281725,000$
6Brad Malone (R)X100.006040646179676767805451716275696319600343575,000$
7Rhett Gardner (R)X100.006637996080507155776864572576725820600283575,000$
8Dustin Jeffrey (R)X100.006451996276497053925242745683833330590361575,000$
9Thomas Bordeleau (R)X100.005340727058606165436162502566505020571223916,667$
10James Hamblin (R)X100.005440736957636363576155552562525020572253807,500$
11Dylan Samberg (R)X100.007555787588837672406663822571594965710252925,000$
12Victor Bartley (R)X100.00889343627542625957524182549992119650361700,000$
13Matt Kiersted (R)X100.005640757576796567407370652568605320650262762,500$
14Paul Postma (R)X100.002512996976556659235845726099912219620352575,000$
MOYENNE D’ÉQUIPE100.00684878737874757156696672347768495968
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
1Jeremy Swayman (R)100.00888485819099999999893084615291880251925,000$
2Christopher Gibson (R)100.007789888082919399997776869249918603132,000,000$
Rayé
1Lukas Dostal (R)100.00817575767882808083783080585120760232822,500$
MOYENNE D’ÉQUIPE100.0082838379839191939481458370516783
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jack Capuano8573756657551USA5625,000,000$


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Shane PintoOilers (EDM)C803848861537251411882647214914.39%29155719.476182424202202111305154.22%17894131031.1001212784
2Kailer YamamotoOilers (EDM)RW82324577171251721402569016012.50%36172921.09612183122821382317044.75%1817427000.8924212466
3Taylor RaddyshOilers (EDM)RW823737741037351201152587515214.34%25142817.43971618176000075242.68%824721011.0401124544
4Charles Hudon Oilers (EDM)LW72314172-53010921472336316113.30%41154321.431310234719611252214055.20%5005615110.9324002633
5Trevor ZegrasOilers (EDM)C81224971-811640181162290791727.59%29154619.1051015292000226984048.88%17456630000.9200224134
6Janis MoserOilers (EDM)D82153348-2804011516816558639.09%95194723.7610616302490006249120%05268000.4901242033
7Jack McBainOilers (EDM)C792027479173851641071984410610.10%24103013.04022030000183146.83%7413522000.91003113411
8Trent FredericOilers (EDM)LW70132639131811151419015339808.50%22119517.082911151540003120246.05%762224000.65005315132
9Ryan McLeodOilers (EDM)RW821818361128207867144458612.50%34101612.401122110000122140.38%522815000.7100013143
10Brendan LemieuxOilers (EDM)LW811118291175951697986306412.79%25112013.830332470001622034.00%502312000.5200577221
11Jake WalmanOilers (EDM)D81719260905013914512146445.79%111192923.82347132480111246500%03250000.2700163012
12Liam FoudyOilers (EDM)LW8281826121515514310635557.55%166888.40000020000130047.62%211711000.7600012021
13Dante FabbroOilers (EDM)D820242432113351461289338290%78168620.5602271490000149000%01847000.2800223002
14Jordan OesterleOilers (EDM)D79616222310660761198642286.98%85167721.2422451510112155100%03859000.2600183001
15Kevin RooneyOilers (EDM)C821181994810659192205111.96%217719.41000010001904055.21%3171416000.4900110103
16Kiefer SherwoodOilers (EDM)RW82108189195662979204212.66%85656.9000002000012116.67%12115000.6400100112
17Dylan SambergOilers (EDM)D4711314-4282043433010123.33%5669914.880220600006000%0631000.4000013011
18Vincent DesharnaisOilers (EDM)D7501010-1742066815915170%64118615.8200009000041000%0632000.1701121000
19Victor MeteOilers (EDM)D3917812952455221094.55%2663516.2900008000028100%0424000.2500010000
20Dylan HollowayOilers (EDM)LW22246300961781011.76%51416.440000000000100%591000.8500000010
21Victor BartleyOilers (EDM)D3011-21210731010%34414.790000000005000%001000.4500101000
22Brad MaloneOilers (EDM)LW10011040862160%1727.250000000000000%000000.2800000000
23Thomas BordeleauOilers (EDM)C3011055001200%1217.0300000000000050.00%410000.9500010000
24Dylan DeMelo OilersD3000020856230%07324.57000113000012000%02100000000000
25Dustin JeffreyOilers (EDM)C3000100071020%0175.9000000000000050.00%121100000000000
26Maxim MaminOilers (EDM)LW1000000000000%055.450000000000000%00000000000000
27Matt KierstedOilers (EDM)D1000-300101000%21818.050000000001000%00100000000000
Statistiques d’équipe totales ou en moyenne14862834727551361453725208220242764844150210.24%8372435116.39578814522420915611451785471050.65%5587603545150.62412304570334343
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
1Jeremy SwaymanOilers (EDM)64401940.9062.9737580118619877871221.00036319741
2Christopher GibsonOilers (EDM)2310720.9172.7412040155661282010.85771963312
Statistiques d’équipe totales ou en moyenne87502660.9092.91496302241264810691231082821053


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 Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Type Salaire actuel Salaire restantPlafond salarial Non Activé 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 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
Anthony AngelloOilers (EDM)RW281996-03-06 03:41:22Yes209 Lbs6 ft5NoNoN/ANoNo1Pro & Farm725,000$0$0$No------------------
Brad MaloneOilers (EDM)LW341989-05-20 11:11:13Yes216 Lbs6 ft2NoNoTrade2024-03-30NoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Brendan LemieuxOilers (EDM)LW281996-03-15 14:23:45Yes215 Lbs6 ft1NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------
Charles Hudon Oilers (EDM)LW291994-06-22 05:11:43No190 Lbs5 ft10NoNoN/ANoNo1Pro & Farm3,000,000$0$0$No------------------
Christopher GibsonOilers (EDM)G311992-12-27 05:11:14Yes216 Lbs6 ft2NoNoN/ANoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$-------NoNo-------
Dante FabbroOilers (EDM)D251998-06-20 11:37:54Yes189 Lbs6 ft0NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------
Dustin JeffreyOilers (EDM)C361988-02-27 04:25:12Yes207 Lbs6 ft1NoNoTrade2024-03-30NoNo1Pro & Farm575,000$0$0$No------------------
Dylan HollowayOilers (EDM)LW222001-09-23 13:51:22Yes203 Lbs6 ft1NoNoN/ANoNo3Pro & Farm925,000$0$0$No925,000$925,000$-------NoNo-------
Dylan SambergOilers (EDM)D251999-01-24 13:37:06Yes219 Lbs6 ft4NoNoN/ANoNo2Pro & Farm925,000$0$0$No925,000$--------No--------
Jack McBainOilers (EDM)C242000-01-06 13:53:01Yes201 Lbs6 ft3NoNoN/ANoNo3Pro & Farm925,000$0$0$No925,000$925,000$-------NoNo-------
Jake WalmanOilers (EDM)D281996-02-20 06:56:22Yes215 Lbs6 ft2NoNoN/ANoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$-------NoNo-------
James HamblinOilers (EDM)C251999-04-27 03:23:37Yes174 Lbs5 ft9NoNoN/ANoNo3Pro & Farm807,500$0$0$No807,500$807,500$-------NoNo-------
Janis MoserOilers (EDM)D232000-06-06 13:55:04Yes173 Lbs6 ft1NoNoN/ANoNo3Pro & Farm886,667$0$0$No886,667$886,667$-------NoNo-------
Jeremy SwaymanOilers (EDM)G251998-11-24 10:23:28Yes194 Lbs6 ft2NoNoN/ANoNo1Pro & Farm925,000$0$0$No------------------
Jordan OesterleOilers (EDM)D311992-06-25 06:39:21Yes187 Lbs6 ft0NoNoN/ANoNo2Pro & Farm1,500,000$0$0$No1,500,000$--------No--------
Josh CurrieOilers (EDM)RW311992-10-29 08:46:08Yes190 Lbs5 ft11NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Kailer YamamotoOilers (EDM)RW251998-09-29 14:20:42Yes153 Lbs5 ft8NoNoN/ANoNo1Pro & Farm1,000,000$0$0$No------------------
Kevin RooneyOilers (EDM)C301993-05-21 04:57:57Yes201 Lbs6 ft2NoNoN/ANoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------NoNo-------
Kiefer SherwoodOilers (EDM)RW291995-03-31 05:04:59Yes194 Lbs6 ft0NoNoN/ANoNo2Pro & Farm700,000$0$0$No700,000$--------No--------
Liam FoudyOilers (EDM)LW242000-02-04 10:26:37Yes188 Lbs6 ft2NoNoN/ANoNo1Pro & Farm894,167$0$0$No------------------
Lukas DostalOilers (EDM)G232000-06-22 13:39:26Yes174 Lbs6 ft2NoNoN/ANoNo2Pro & Farm822,500$0$0$No822,500$--------No--------
Matt KierstedOilers (EDM)D261998-04-14 10:20:39Yes181 Lbs6 ft0NoNoN/ANoNo2Pro & Farm762,500$0$0$No762,500$--------No--------
Maxim MaminOilers (EDM)LW291995-01-13 04:51:05Yes191 Lbs6 ft2NoNoN/ANoNo1Pro & Farm575,000$0$0$No------------------
Paul PostmaOilers (EDM)D351989-02-22 11:11:13Yes195 Lbs6 ft3NoNoN/ANoNo2Pro & Farm575,000$0$0$No575,000$--------No--------
Rhett GardnerOilers (EDM)LW281996-02-28 06:59:34Yes225 Lbs6 ft3NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Ryan McLeodOilers (EDM)RW241999-09-21 10:30:39Yes207 Lbs6 ft2NoNoN/ANoNo1Pro & Farm834,167$0$0$No------------------
Shane PintoOilers (EDM)C232000-11-12 10:32:44Yes201 Lbs6 ft3NoNoN/ANoNo1Pro & Farm925,000$0$0$No------------------
Tanner FritzOilers (EDM)RW331991-01-08 05:24:17Yes192 Lbs5 ft11NoNoTrade2024-03-30NoNo1Pro & Farm575,000$0$0$No------------------
Taylor RaddyshOilers (EDM)RW261998-02-18 13:41:25Yes198 Lbs6 ft3NoNoN/ANoNo2Pro & Farm758,333$0$0$No758,333$--------No--------
Thomas BordeleauOilers (EDM)C222002-01-03 13:56:45Yes174 Lbs5 ft10NoNoN/ANoNo3Pro & Farm916,667$0$0$No916,667$916,667$-------NoNo-------
Trent FredericOilers (EDM)LW261998-02-11 11:40:05Yes214 Lbs6 ft3NoNoN/ANoNo2Pro & Farm575,000$0$0$No575,000$--------No--------
Trevor ZegrasOilers (EDM)C232001-03-20 10:34:51Yes185 Lbs6 ft0NoNoN/ANoNo1Pro & Farm925,000$0$0$No------------------
Victor BartleyOilers (EDM)D361988-02-17 05:11:13Yes208 Lbs6 ft0NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------
Victor MeteOilers (EDM)D251998-06-07 14:19:19Yes183 Lbs5 ft9NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------
Vincent DesharnaisOilers (EDM)D271996-05-29 12:36:41Yes215 Lbs6 ft6NoNoN/ANoNo3Pro & Farm762,500$0$0$No762,500$762,500$-------NoNo-------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3527.40196 Lbs6 ft11.94932,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Charles Hudon Shane PintoKailer Yamamoto35122
2Trent FredericTrevor ZegrasTaylor Raddysh35122
3Brendan LemieuxJack McBainRyan McLeod25122
4Liam FoudyKevin RooneyKiefer Sherwood5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanJanis Moser35122
2Jordan OesterleDante Fabbro35122
3Vincent DesharnaisVictor Mete30122
4Jake WalmanJanis Moser0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Charles Hudon Shane PintoKailer Yamamoto60122
2Trent FredericTrevor ZegrasTaylor Raddysh40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanJanis Moser60122
2Jordan OesterleDante Fabbro40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Charles Hudon Kailer Yamamoto60122
2Shane PintoTrevor Zegras40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanJanis Moser60122
2Jordan OesterleDante Fabbro40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Charles Hudon 60122Jake WalmanJanis Moser60122
2Kailer Yamamoto40122Jordan OesterleDante Fabbro40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Charles Hudon Kailer Yamamoto60122
2Shane PintoTrevor Zegras40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanJanis Moser60122
2Jordan OesterleDante Fabbro40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Charles Hudon Shane PintoKailer YamamotoJake WalmanJanis Moser
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Charles Hudon Shane PintoKailer YamamotoJake WalmanJanis Moser
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Jack McBain, Ryan McLeod, Kevin RooneyJack McBain, Ryan McLeodKevin Rooney
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Vincent Desharnais, Victor Mete, Jordan OesterleVincent DesharnaisVictor Mete, Jordan Oesterle
Tirs de pénalité
Charles Hudon , Kailer Yamamoto, Shane Pinto, Trevor Zegras, Jack McBain
Gardien
#1 : Christopher Gibson, #2 : Jeremy Swayman
Lignes d’attaque personnalisées en prolongation
Charles Hudon , Kailer Yamamoto, Shane Pinto, Trevor Zegras, Jack McBain, Taylor Raddysh, Taylor Raddysh, Trent Frederic, Ryan McLeod, Kevin Rooney, Brendan Lemieux
Lignes de défense personnalisées en prolongation
Jake Walman, Janis Moser, Jordan Oesterle, Dante Fabbro, Vincent Desharnais


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
1Avalanche3120000069-32110000056-11010000013-220.33361016107597103129492989090250851945768112.50%5260.00%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
2Blackhawks30200010511-61000001021120200000310-720.3335813007597103121119298909025093325873900.00%14285.71%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
3Blues30101100912-31000010023-12010100079-230.500912210075971031299929890902509830307317529.41%11190.91%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
4Bruins43100000191273210000011831100000084460.750193150017597103121349298909025014642841018112.50%7271.43%11079209451.53%1122217751.54%629126949.57%1801107617867261380687
5Canadiens31100100913-4210001006601010000037-430.5009142300759710312979298909025098223168400.00%13376.92%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
6Canucks502011101619-32010001078-130101100911-250.50016284410759710312163929890902501715214113121628.57%23865.22%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
7Capitals32100000954110000004132110000054140.667917260075971031210492989090250105401180100.00%3166.67%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
8Devils320010001174210010008531100000032161.000112031007597103121099298909025098322272500.00%6183.33%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
9Ducks5320000015132312000001012-22200000051460.60015223701759710312161929890902501634618514629413.79%27485.19%21079209451.53%1122217751.54%629126949.57%1801107617867261380687
10Flames550000001910922000000743330000001266101.00019315000759710312155929890902501443610711533618.18%31293.55%11079209451.53%1122217751.54%629126949.57%1801107617867261380687
11Flyers312000001012-220200000611-51100000041320.3331018280075971031299929890902501034216694125.00%30100.00%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
12Islanders3120000079-21010000024-22110000055020.3337111800759710312108929890902509534972600.00%20100.00%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
13Kings512020001919031002000161152020000038-560.60019325100759710312171929890902501614114212622731.82%26580.77%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
14Maple Leafs43001000155101100000051432001000104681.000152237007597103121449298909025013243189413323.08%30100.00%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
15Penguins3120000078-12020000036-31100000042220.33371219007597103129292989090250944345603133.33%100100.00%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
16Predators320000011156110000005142100000164250.833111728007597103129992989090250943060829444.44%15286.67%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
17Rangers311000101113-2210000109541010000028-640.66711182900759710312108929890902501012977733133.33%6183.33%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
18Red Wings31100100660210001005411010000012-130.500612180075971031210292989090250963214833133.33%7185.71%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
19Sabres321000001385110000005232110000086240.6671321341075971031210692989090250983737768112.50%6183.33%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
20Senateurs42001100191542100010087121001000118370.87519294800759710312144929890902501364147958225.00%6266.67%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
21Sharks5410000022157220000001055321000001210280.80022375900759710312172929890902501495016013824833.33%20765.00%11079209451.53%1122217751.54%629126949.57%1801107617867261380687
22Stars31101000131121010000035-221001000106440.66713233600759710312919298909025010242529114214.29%16287.50%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
23Wild3210000015872200000014681010000012-140.6671526410075971031299929890902508921588010330.00%90100.00%01079209451.53%1122217751.54%629126949.57%1801107617867261380687
Total8239260853128624541412011034301531223141191505101133123101060.646286471757327597103122762929890902502651836144920742625721.76%2694782.53%51079209451.53%1122217751.54%629126949.57%1801107617867261380687
_Since Last GM Reset8239260853128624541412011034301531223141191505101133123101060.646286471757327597103122762929890902502651836144920742625721.76%2694782.53%51079209451.53%1122217751.54%629126949.57%1801107617867261380687
_Vs Conference431914052211501321820105021208162192399031016970-1550.640150246396217597103121415929890902501349399103811311964623.47%1973582.23%41079209451.53%1122217751.54%629126949.57%1801107617867261380687
_Vs Division251370311091761512630201050401013740110041365350.7009115024111759710312822929890902507882257356561293124.03%1272679.53%41079209451.53%1122217751.54%629126949.57%1801107617867261380687

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82106W10286471757276226518361449207432
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8239268531286245
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4120113430153122
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4119155101133123
Derniers 10 matchs
WLOTWOTL SOWSOL
1000000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2625721.76%2694782.53%5
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
92989090250759710312
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
1079209451.53%1122217751.54%629126949.57%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1801107617867261380687


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
15Oilers5Flames3AWR5Sommaire du match
316Ducks2Oilers4BWSommaire du match
529Oilers3Maple Leafs2AWSommaire du match
738Kings3Oilers4BWXR5Sommaire du match
851Oilers4Sharks2AWR5Sommaire du match
1161Bruins0Oilers5BWSommaire du match
1577Penguins3Oilers2BLSommaire du match
1683Oilers3Canucks4ALXR5Sommaire du match
20105Ducks5Oilers3BLSommaire du match
22116Oilers2Islanders3ALSommaire du match
24126Oilers2Kings5ALR5Sommaire du match
25135Flyers6Oilers2BLSommaire du match
28151Oilers6Stars5AWXSommaire du match
30159Avalanche4Oilers5BWR2Sommaire du match
33177Oilers6Senateurs4AWSommaire du match
35184Red Wings2Oilers1BLXSommaire du match
36194Oilers2Capitals3ALSommaire du match
39202Oilers5Senateurs4AWXSommaire du match
41213Senateurs4Oilers6BWSommaire du match
43225Oilers3Canucks5ALR5Sommaire du match
45235Avalanche2Oilers0BLR2Sommaire du match
48248Oilers4Flyers1AWSommaire du match
49258Canucks4Oilers5BWXXR5Sommaire du match
52275Blues3Oilers2BLXSommaire du match
56295Maple Leafs1Oilers5BWSommaire du match
58310Oilers2Rangers8ALSommaire du match
60317Oilers1Kings3ALR5Sommaire du match
62329Wild2Oilers6BWSommaire du match
65344Oilers1Avalanche3ALR2Sommaire du match
67353Predators1Oilers5BWSommaire du match
69368Islanders4Oilers2BLSommaire du match
73387Oilers4Stars1AWSommaire du match
75395Rangers3Oilers4BWXXSommaire du match
78406Oilers2Maple Leafs1AWXSommaire du match
81419Rangers2Oilers5BWSommaire du match
84433Oilers3Sharks4ALR5Sommaire du match
85441Ducks5Oilers3BLSommaire du match
90462Red Wings2Oilers4BWSommaire du match
92475Oilers2Blues5ALR2Sommaire du match
94487Penguins3Oilers1BLSommaire du match
97497Oilers5Sabres1AWSommaire du match
99509Bruins5Oilers2BLSommaire du match
101521Oilers3Flames1AWR5Sommaire du match
103533Oilers3Canucks2AWXSommaire du match
104540Kings3Oilers6BWR5Sommaire du match
108554Oilers5Sharks4AWR5Sommaire du match
110565Bruins3Oilers4BWSommaire du match
114582Senateurs3Oilers2BLXSommaire du match
116596Oilers4Penguins2AWSommaire du match
118604Oilers4Flames2AWR5Sommaire du match
119611Wild4Oilers8BWSommaire du match
122629Oilers3Capitals1AWSommaire du match
123635Stars5Oilers3BLSommaire du match
126649Oilers1Blackhawks6ALR2Sommaire du match
127656Devils3Oilers4BWXSommaire du match
130669Oilers3Sabres5ALSommaire du match
132677Oilers3Canadiens7ALSommaire du match
134687Flyers5Oilers4BLSommaire du match
137703Oilers5Maple Leafs1AWSommaire du match
139711Oilers1Wild2ALR2Sommaire du match
140716Blackhawks1Oilers2BWXXSommaire du match
142734Sabres2Oilers5BWSommaire du match
145747Oilers2Blackhawks4ALR2Sommaire du match
147755Devils2Oilers4BWSommaire du match
150769Oilers1Red Wings2ALSommaire du match
152780Canucks4Oilers2BLR5Sommaire du match
153788Oilers3Islanders2AWSommaire du match
156805Canadiens2Oilers3BWSommaire du match
158819Oilers5Blues4AWXR2Sommaire du match
160830Kings5Oilers6BWXR5Sommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
161834Oilers2Predators3ALXXSommaire du match
164852Canadiens4Oilers3BLXSommaire du match
168873Flames3Oilers5BWR5Sommaire du match
169881Oilers8Bruins4AWSommaire du match
172896Capitals1Oilers4BWSommaire du match
173906Oilers3Devils2AWSommaire du match
175920Oilers4Predators1AWR2Sommaire du match
176923Oilers2Ducks1AWR5Sommaire du match
178930Flames1Oilers2BWR5Sommaire du match
184954Sharks3Oilers5BWR5Sommaire du match
189968Sharks2Oilers5BWSommaire du match
191978Oilers3Ducks0AWR5Sommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4525
Assistance61,08540,172
Assistance PCT74.49%97.98%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2470 - 82.32% 123,578$5,066,714$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
8,030,832$ 3,262,001$ 1,902,001$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 3,030,834$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 42,808$ 0$




Oilers 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

Oilers 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

Oilers 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

Oilers 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

Oilers 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