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Red Wings
GP: 82 | W: 42 | L: 31 | OTL: 9 | P: 93
GF: 268 | GA: 248 | PP%: 20.07% | PK%: 83.07%
DG: Martin Dufour | Morale : 57 | Moyenne d’équipe : 66
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Centre de jeu
Red Wings
42-31-9, 93pts
1
FINAL
2 Islanders
38-31-13, 89pts
Team Stats
W1StreakL1
23-17-1Home Record20-14-7
19-14-8Away Record18-17-6
6-2-2Last 10 Games6-4-0
3.27Buts par match 3.07
3.02Buts contre par match 3.18
20.07%Pourcentage en avantage numérique18.37%
83.07%Pourcentage en désavantage numérique83.01%
Red Wings
42-31-9, 93pts
4
FINAL
3 Penguins
34-40-8, 76pts
Team Stats
W1StreakW1
23-17-1Home Record18-20-3
19-14-8Away Record16-20-5
6-2-2Last 10 Games5-5-0
3.27Buts par match 3.01
3.02Buts contre par match 3.32
20.07%Pourcentage en avantage numérique16.73%
83.07%Pourcentage en désavantage numérique81.44%
Meneurs d'équipe
Buts
Kyle Clifford
38
Passes
Pius Suter
48
Points
Brady Tkachuk
80
Plus/Moins
Dylan Coghlan
16
Victoires
Kevin Lankinen
28
Pourcentage d’arrêts
Kevin Lankinen
0.905

Statistiques d’équipe
Buts pour
268
3.27 GFG
Tirs pour
2563
31.26 Avg
Pourcentage en avantage numérique
20.1%
56 GF
Début de zone offensive
39.2%
Buts contre
248
3.02 GAA
Tirs contre
2511
30.62 Avg
Pourcentage en désavantage numérique
83.1%%
43 GA
Début de la zone défensive
37.1%
Informations de l'équipe

Directeur généralMartin Dufour
EntraîneurCraig MacTavish
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,428
Billets de saison2,400


Informations de la formation

Équipe Pro37
Équipe Mineure19
Limite contact 56 / 60
Espoirs45


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
1Brady Tkachuk (R)X100.0081996683827894826084837325656876807502333,000,000$
2Kyle Clifford (R)X100.0077458271836588806474738765999239817403221,750,000$
3Dominik Kubalik (R)X100.007443898082709274257887702577767471730271925,000$
4Oskar Lindblom (R)X100.0063309568737780835279817072747151807202621,250,000$
5Pius Suter (R)X100.007641917682738376817773682573767157710262925,000$
6Teddy Blueger (R)X100.0075438870836883658376698125787471727002821,000,000$
7Tomas Nosek (R)X100.007545917483637972867471772582766880700301600,000$
8Ilya Mikheyev (R)X100.007743967782677672257672782578746868700281925,000$
9Logan Brown (R)X100.007285807081738262797267715168676084670252700,000$
10Logan O'Connor (R)X100.007943917284576265447270712575737179670261725,000$
11Scott Wilson (R)X100.005542906772727468536963706282754973660313600,000$
12Eetu Luostarinen (R)X100.007744916783647864777468672567666626660241897,500$
13Steven Santini (R)X100.0095557065766692823079759153777264667502811,000,000$
14Will Butcher (R)X100.0065397466727591963095806561666249557202821,500,000$
15Madison Bowey (R)X100.0077739966808178733077677351757050667002821,000,000$
16Dylan Coghlan (R)X100.007343977584626870257369672570685978680252762,500$
17Urho Vaakanainen (R)X100.007241926883766260257269762566675843670243700,000$
18Jamie Drysdale (R)X100.007241917482787065257369622565696137670212925,000$
Rayé
1Wade Allison (R)X100.007745907483635371257472662568667320660252925,000$
2Ryan Poehling (R)X100.008073977473686966806561716264676819650243575,000$
3Par Lindholm (R)X100.005329996871818357865655876184732820650313575,000$
4John Hayden (R)X100.007847656883556163677368646272696220640281575,000$
5Connor Bunnaman (R)X100.007545966884596655767368682567666219640251736,666$
6Joseph Gambardella (R)X100.006135736472645771657363725169573820630292575,000$
7Gabriel Fortier (R)X100.007362976662677154683737615544446020530233791,667$
8Scott Reedy (R)X100.008076896476535356703838655744446119530243842,500$
9Juuso Valimaki (R)X100.007343857382675672257470732569717920670243800,000$
10Tyler Wotherspoon (R)X100.004916996077556777256649825485805519660301575,000$
11Sami Niku (R)X100.007141766881664865247368682572694819650263575,000$
12Guillaume Brisebois (R)X100.007067926180545658257166723969665220630253575,000$
13Cam York (R)X100.007363856984504860257268645362645920630222880,833$
14Kaedan Korczak (R)X100.007674795974555846253131613744445020540223789,167$
15Lassi Thomson (R)X100.007570885870596251253333613844445320540223863,333$
MOYENNE D’ÉQUIPE100.00735187697966716849696571417067594566
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
1Kevin Lankinen (R)100.00848783858792948391768076807278840282800,000$
2Josef Korenar (R)100.00757671757382837776737268725881740252750,000$
Rayé
1Joel Hofer (R)100.00526176664966556163613044445520580223795,000$
2Justus Annunen (R)100.00504860825055566050503044445119540233880,833$
MOYENNE D’ÉQUIPE100.0065687377657472707065535860595068
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Craig MacTavish72617188988176CAN6231,500,000$


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 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
1Brady TkachukRed Wings (DET)LW82374380-3163452171582889517612.85%44167320.411313264924300021726345.41%1968024000.9604441185
2Kyle CliffordRed Wings (DET)LW8238367417151831272798715913.62%48158719.35712192819600051447040.19%1075243020.9313100853
3Oskar LindblomRed Wings (DET)RW82264773560116992548614610.24%30145117.7071219241980000211042.47%732920001.0100000545
4Pius SuterRed Wings (DET)C7916486402610127190170441039.41%25135717.195152016195000021152.06%15772412000.9400002361
5Dominik KubalikRed Wings (DET)RW79233255-9295147118171579413.45%28151019.1271017302360113754035.63%875122000.7311001423
6Nick SuzukiRed WingsC64262854-430101281732106213412.38%44133820.9189173117400051666351.20%17052925100.8114002423
7Ilya MikheyevRed Wings (DET)RW792121421609774181519711.60%27102813.010113121013584226.67%604014100.8201000353
8Will ButcherRed Wings (DET)D7663339-857513813611472655.26%78180223.722810152620001200100.00%04238000.4300001022
9Tomas NosekRed Wings (DET)LW82152439-311512996151541109.93%30107313.091121120003471062.22%452718000.7300001314
10Teddy BluegerRed Wings (DET)C82122032232013413095265412.63%34114313.940551750001222055.05%8811425000.5601000212
11Steven SantiniRed Wings (DET)D7522628-186102211609834322.04%120176323.51268152460111182100.00%02344000.3201011032
12Logan O'ConnorRed Wings (DET)RW821610261080835898246916.33%146437.8501113000012150.00%162712000.8100000201
13Madison BoweyRed Wings (DET)D8241822-239251201368129324.94%92179221.86303101860002176000.00%02234100.2500113201
14Logan BrownRed Wings (DET)C827142176220739266273810.61%107949.69000010000740052.94%340810000.5300400110
15Scott WilsonRed Wings (DET)LW8261218100032426321479.52%136167.5100000000040053.33%1599000.5800000012
16Dylan CoghlanRed Wings (DET)D773151816141077947217344.17%75141818.42011281000082000.00%01629000.2500101012
17Urho VaakanainenRed Wings (DET)D7511112922064944930252.04%55120716.10000114000048100.00%01127000.2000000000
18Jamie DrysdaleRed Wings (DET)D52191021005655361392.78%3882715.9200008000038000.00%01112000.2400000001
19Juuso ValimakiRed Wings (DET)D49246-828049764718134.26%6697919.981015100000067000.00%01230000.1200000000
20Eetu LuostarinenRed Wings (DET)C202240201812229129.09%51447.2500000000012041.82%5512000.5500000001
21Wade AllisonRed Wings (DET)RW61010007512498.33%1457.510000000000000.00%011000.4400000000
22Sami NikuRed Wings (DET)D6000240746200.00%19315.660000000004000.00%002000.00%00000000
Statistiques d’équipe totales ou en moyenne147526545371827706150222321292563862145810.34%8782429316.4756941502322251123261594391051.11%5157529453320.5931511613384241
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
1Kevin LankinenRed Wings (DET)58282360.9052.943368221651743736320.8758587612
2Josef KorenarRed Wings (DET)2813730.8962.9714542072695312001.00042259003
3Joel HoferRed Wings (DET)31100.9003.161330077042010.00%0215000
Statistiques d’équipe totales ou en moyenne89423190.9032.954956422442508109033128281615


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Brady TkachukRed Wings (DET)LW231999-09-16 14:34:31Yes196 Lbs6 ft3NoNoNo3Pro & Farm3,000,000$15,075$0$0$No3,000,000$3,000,000$
Cam YorkRed Wings (DET)D222001-01-05 13:24:35Yes174 Lbs5 ft11NoNoNo2Pro & Farm880,833$4,426$0$0$No880,833$
Connor BunnamanRed Wings (DET)C251998-04-16 13:28:38Yes207 Lbs6 ft1NoNoNo1Pro & Farm736,666$3,702$0$0$No
Dominik KubalikRed Wings (DET)RW271995-08-21 06:40:03Yes179 Lbs6 ft2NoNoNo1Pro & Farm925,000$4,648$0$0$No
Dylan CoghlanRed Wings (DET)D251998-02-19 03:19:24Yes190 Lbs6 ft2NoNoNo2Pro & Farm762,500$3,832$0$0$No762,500$
Eetu LuostarinenRed Wings (DET)C241998-09-02 13:31:44Yes190 Lbs6 ft3NoNoNo1Pro & Farm897,500$4,510$0$0$No
Gabriel FortierRed Wings (DET)LW232000-02-06 04:05:24Yes183 Lbs5 ft10NoNoNo3Pro & Farm791,667$3,978$0$0$No791,667$791,667$
Guillaume BriseboisRed Wings (DET)D251997-07-21 14:26:41Yes174 Lbs6 ft2NoNoNo3Pro & Farm575,000$2,889$0$0$No575,000$575,000$
Ilya MikheyevRed Wings (DET)RW281994-10-10 05:54:37Yes194 Lbs6 ft2NoNoNo1Pro & Farm925,000$4,648$0$0$No
Jamie DrysdaleRed Wings (DET)D212002-04-08 13:27:26Yes174 Lbs5 ft11NoNoNo2Pro & Farm925,000$4,648$0$0$No925,000$
Joel HoferRed Wings (DET)G222000-07-30 04:07:52Yes172 Lbs6 ft5NoNoNo3Pro & Farm795,000$3,995$0$0$No795,000$795,000$
John HaydenRed Wings (DET)RW281995-02-14 11:00:55Yes215 Lbs6 ft3NoNoNo1Pro & Farm575,000$2,889$0$0$No
Josef KorenarRed Wings (DET)G251998-01-31 13:55:25Yes185 Lbs6 ft1NoNoNo2Pro & Farm750,000$3,769$0$0$No750,000$
Joseph GambardellaRed Wings (DET)C291993-12-01 08:29:15Yes196 Lbs5 ft10NoNoNo2Pro & Farm575,000$2,889$0$0$No575,000$
Justus AnnunenRed Wings (DET)G232000-03-11 04:12:58Yes209 Lbs6 ft4NoNoNo3Pro & Farm880,833$4,426$0$0$No880,833$880,833$
Juuso ValimakiRed Wings (DET)D241998-10-06 05:14:16Yes212 Lbs6 ft2NoNoNo3Pro & Farm800,000$4,020$0$0$No800,000$800,000$
Kaedan KorczakRed Wings (DET)D222001-01-29 04:16:55Yes192 Lbs6 ft4NoNoNo3Pro & Farm789,167$3,966$0$0$No789,167$789,167$
Kevin LankinenRed Wings (DET)G281995-04-28 03:45:22Yes185 Lbs6 ft2NoNoNo2Pro & Farm800,000$4,020$0$0$No800,000$
Kyle CliffordRed Wings (DET)LW321991-01-13 11:11:13Yes211 Lbs6 ft2NoNoNo2Pro & Farm1,750,000$8,794$0$0$No1,750,000$
Lassi ThomsonRed Wings (DET)D222000-09-24 04:20:00Yes192 Lbs6 ft0NoNoNo3Pro & Farm863,333$4,338$0$0$No863,333$863,333$
Logan BrownRed Wings (DET)C251998-03-05 09:29:54Yes220 Lbs6 ft6NoNoNo2Pro & Farm700,000$3,518$0$0$No700,000$
Logan O'ConnorRed Wings (DET)RW261996-08-14 12:23:27Yes174 Lbs6 ft0NoNoNo1Pro & Farm725,000$3,643$0$0$No
Madison BoweyRed Wings (DET)D281995-04-22 09:27:31Yes198 Lbs6 ft2NoNoNo2Pro & Farm1,000,000$5,025$0$0$No1,000,000$
Oskar LindblomRed Wings (DET)RW261996-08-15 11:12:26Yes191 Lbs6 ft1NoNoNo2Pro & Farm1,250,000$6,281$0$0$No1,250,000$
Par LindholmRed Wings (DET)LW311991-10-05 04:11:59Yes183 Lbs5 ft11NoNoNo3Pro & Farm575,000$2,889$0$0$No575,000$575,000$
Pius SuterRed Wings (DET)C261996-05-24 03:52:07Yes176 Lbs5 ft11NoNoNo2Pro & Farm925,000$4,648$0$0$No925,000$
Ryan PoehlingRed Wings (DET)C241999-01-03 14:22:24Yes183 Lbs6 ft2NoNoNo3Pro & Farm575,000$2,889$0$0$No575,000$575,000$
Sami NikuRed Wings (DET)D261996-10-10 05:12:25Yes176 Lbs6 ft1NoNoNo3Pro & Farm575,000$2,889$0$0$No575,000$575,000$
Scott ReedyRed Wings (DET)C241999-04-04 04:23:08Yes214 Lbs6 ft2NoNoNo3Pro & Farm842,500$4,234$0$0$No842,500$842,500$
Scott WilsonRed Wings (DET)LW311992-04-24 05:11:13Yes185 Lbs5 ft11NoNoNo3Pro & Farm600,000$3,015$0$0$No600,000$600,000$
Steven SantiniRed Wings (DET)D281995-03-07 09:26:46Yes205 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$5,025$0$0$No
Teddy BluegerRed Wings (DET)C281994-08-15 14:16:07Yes185 Lbs6 ft0NoNoNo2Pro & Farm1,000,000$5,025$0$0$No1,000,000$
Tomas NosekRed Wings (DET)LW301992-09-01 11:05:59Yes210 Lbs6 ft3NoNoNo1Pro & Farm600,000$3,015$0$0$No
Tyler WotherspoonRed Wings (DET)D301993-03-12 11:11:13Yes217 Lbs6 ft2NoNoNo1Pro & Farm575,000$2,889$0$0$No
Urho VaakanainenRed Wings (DET)D241999-01-01 14:29:18Yes185 Lbs6 ft1NoNoNo3Pro & Farm700,000$3,518$0$0$No700,000$700,000$
Wade AllisonRed Wings (DET)RW251997-10-14 13:21:46Yes205 Lbs6 ft2NoNoNo2Pro & Farm925,000$4,648$0$0$No925,000$
Will ButcherRed Wings (DET)D281995-01-06 11:14:31Yes190 Lbs5 ft10NoNoNo2Pro & Farm1,500,000$7,538$0$0$No1,500,000$
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3725.89193 Lbs6 ft12.14893,649$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Brady TkachukPius SuterDominik Kubalik35122
2Kyle CliffordTeddy BluegerOskar Lindblom35122
3Tomas NosekLogan BrownIlya Mikheyev25122
4Scott WilsonEetu LuostarinenLogan O'Connor5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Steven SantiniWill Butcher35122
2Madison BoweyDylan Coghlan35122
3Urho VaakanainenJamie Drysdale30122
4Steven SantiniWill Butcher0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Brady TkachukPius SuterDominik Kubalik60122
2Kyle CliffordTeddy BluegerOskar Lindblom40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Steven SantiniWill Butcher60122
2Madison BoweyDylan Coghlan40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Brady TkachukKyle Clifford60122
2Dominik KubalikOskar Lindblom40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Steven SantiniWill Butcher60122
2Madison BoweyDylan Coghlan40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Brady Tkachuk60122Steven SantiniWill Butcher60122
2Kyle Clifford40122Madison BoweyDylan Coghlan40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Brady TkachukKyle Clifford60122
2Dominik KubalikOskar Lindblom40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Steven SantiniWill Butcher60122
2Madison BoweyDylan Coghlan40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Brady TkachukPius SuterDominik KubalikSteven SantiniWill Butcher
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Brady TkachukPius SuterDominik KubalikSteven SantiniWill Butcher
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Tomas Nosek, Ilya Mikheyev, Logan BrownTomas Nosek, Ilya MikheyevLogan Brown
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Urho Vaakanainen, Jamie Drysdale, Madison BoweyUrho VaakanainenJamie Drysdale, Madison Bowey
Tirs de pénalité
Brady Tkachuk, Kyle Clifford, Dominik Kubalik, Oskar Lindblom, Pius Suter
Gardien
#1 : Kevin Lankinen, #2 : Josef Korenar
Lignes d’attaque personnalisées en prolongation
Brady Tkachuk, Kyle Clifford, Dominik Kubalik, Oskar Lindblom, Pius Suter, Teddy Blueger, Teddy Blueger, Tomas Nosek, Ilya Mikheyev, Logan Brown, Logan O'Connor
Lignes de défense personnalisées en prolongation
Steven Santini, Will Butcher, Madison Bowey, Dylan Coghlan, Urho Vaakanainen


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
1Avalanche321000001082110000003122110000077040.6671016261073919591097978468943894384704125.00%2150.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
2Blackhawks3200010015962200000011471000010045-150.83315274200739195990797846894381023718804125.00%40100.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
3Blues22000000835110000005141100000032141.0008122000739195964797846894386013449200.00%20100.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
4Bruins624000002219331200000141223120000087140.33322396100739195916779784689438178598617025520.00%23578.26%01044200352.12%958189850.47%635120952.52%1795103017137461454732
5Canadiens66000000321616330000001688330000001688121.00032568800739195922379784689438182577215932721.88%21290.48%01044200352.12%958189850.47%635120952.52%1795103017137461454732
6Canucks2010000168-21010000023-11000000145-110.2506111700739195968797846894386326458500.00%20100.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
7Capitals4120001011110211000005412010001067-140.5001118290173919591067978468943810652301151417.14%15193.33%01044200352.12%958189850.47%635120952.52%1795103017137461454732
8Devils412010001214-220200000510-52100100074340.50012183000739195911579784689438116402811418527.78%140100.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
9Ducks22000000633110000003211100000031241.00061117007391959667978468943858248403133.33%4175.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
10Flames20200000610-41010000056-11010000014-300.000610160073919596979784689438542316533266.67%8187.50%01044200352.12%958189850.47%635120952.52%1795103017137461454732
11Flyers52101100131123110100010822100010033070.7001319320073919591477978468943816451421261218.33%21195.24%01044200352.12%958189850.47%635120952.52%1795103017137461454732
12Islanders4100012015105200000208622100010074370.8751524390073919591277978468943813550189313430.77%8187.50%01044200352.12%958189850.47%635120952.52%1795103017137461454732
13Kings21001000752100010005411100000021141.0007121900739195958797846894388223645400.00%2150.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
14Maple Leafs713012002023-331001100128440300100815-760.42920335310739195920979784689438208767821435514.29%30873.33%01044200352.12%958189850.47%635120952.52%1795103017137461454732
15Oilers2010010058-31010000024-21000010034-110.2505813007391959687978468943863199525120.00%20100.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
16Penguins42101000151322010100078-12200000085360.75015254000739195913279784689438118426011213538.46%10190.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
17Predators2020000025-31010000012-11010000013-200.00024600739195963797846894385825658300.00%3233.33%01044200352.12%958189850.47%635120952.52%1795103017137461454732
18Rangers42200000131302020000069-32200000074340.50013203300739195913679784689438124411011416425.00%50100.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
19Sabres614001001221-930300000512-73110010079-230.2501221331073919591827978468943817759971712428.33%411173.17%11044200352.12%958189850.47%635120952.52%1795103017137461454732
20Senateurs624000001723-63210000087130300000916-740.33317314801739195918879784689438187687716933721.21%26580.77%01044200352.12%958189850.47%635120952.52%1795103017137461454732
21Sharks21000100752110000005231000010023-130.750713200073919596079784689438692329406116.67%70100.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
22Stars21001000945110000006241000100032141.00091625007391959507978468943856174452150.00%2150.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
23Wild2110000056-1110000004221010000014-320.5005914007391959667978468943857154763266.67%2150.00%01044200352.12%958189850.47%635120952.52%1795103017137461454732
Total8233310683126824820411717041201481252341161402711120123-3930.567268453721327391959256379784689438251187871022232795620.07%2544383.07%11044200352.12%958189850.47%635120952.52%1795103017137461454732
_Since Last GM Reset8233310683126824820411717041201481252341161402711120123-3930.567268453721327391959256379784689438251187871022232795620.07%2544383.07%11044200352.12%958189850.47%635120952.52%1795103017137461454732
_Vs Conference5621230453018217482891303120969242812100141086824610.545182304486227391959173279784689438169559559815572354619.57%2143583.64%11044200352.12%958189850.47%635120952.52%1795103017137461454732
_Vs Division311215013001031021157601100554781659002004855-7290.468103180283217391959969797846894389323194108831492617.45%1413178.01%11044200352.12%958189850.47%635120952.52%1795103017137461454732

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8293W126845372125632511878710222332
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8233316831268248
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4117174120148125
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4116142711120123
Derniers 10 matchs
WLOTWOTL SOWSOL
620200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2795620.07%2544383.07%1
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
797846894387391959
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
1044200352.12%958189850.47%635120952.52%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1795103017137461454732


Derniers matchs joués
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
1 - 2022-10-182Red Wings5Bruins1AWSommaire du match
3 - 2022-10-2014Maple Leafs1Red Wings5BWSommaire du match
6 - 2022-10-2328Senateurs4Red Wings2BLSommaire du match
7 - 2022-10-2430Red Wings2Maple Leafs4ALSommaire du match
10 - 2022-10-2747Red Wings6Canadiens2AWR5Sommaire du match
13 - 2022-10-3063Canadiens4Red Wings6BWSommaire du match
15 - 2022-11-0170Red Wings2Senateurs7ALSommaire du match
19 - 2022-11-0589Bruins5Red Wings4BLSommaire du match
22 - 2022-11-08104Sabres6Red Wings2BLSommaire du match
24 - 2022-11-10112Red Wings2Maple Leafs3ALXSommaire du match
27 - 2022-11-13127Flyers3Red Wings4BWXSommaire du match
29 - 2022-11-15134Red Wings2Maple Leafs4ALSommaire du match
30 - 2022-11-16140Red Wings1Sabres3ALSommaire du match
33 - 2022-11-19158Penguins4Red Wings5BWXSommaire du match
37 - 2022-11-23176Red Wings4Canadiens2AWR5Sommaire du match
39 - 2022-11-25184Flyers2Red Wings4BWSommaire du match
42 - 2022-11-28198Red Wings4Avalanche2AWSommaire du match
44 - 2022-11-30206Red Wings3Stars2AWXSommaire du match
46 - 2022-12-02214Red Wings4Penguins2AWSommaire du match
47 - 2022-12-03219Ducks2Red Wings3BWSommaire du match
51 - 2022-12-07235Red Wings1Wild4ALSommaire du match
52 - 2022-12-08240Predators2Red Wings1BLSommaire du match
56 - 2022-12-12258Senateurs3Red Wings4BWSommaire du match
59 - 2022-12-15272Red Wings4Canucks5ALXXSommaire du match
61 - 2022-12-17278Red Wings3Avalanche5ALSommaire du match
62 - 2022-12-18287Blues1Red Wings5BWSommaire du match
65 - 2022-12-21298Red Wings2Maple Leafs4ALSommaire du match
68 - 2022-12-24310Flames6Red Wings5BLSommaire du match
70 - 2022-12-26325Red Wings1Bruins2ALSommaire du match
72 - 2022-12-28334Sharks2Red Wings5BWSommaire du match
74 - 2022-12-30349Red Wings4Capitals3AWXXSommaire du match
76 - 2023-01-01357Wild2Red Wings4BWSommaire du match
78 - 2023-01-03373Red Wings2Bruins4ALSommaire du match
80 - 2023-01-05383Devils4Red Wings3BLSommaire du match
83 - 2023-01-08394Red Wings1Flyers2ALXSommaire du match
85 - 2023-01-10406Kings4Red Wings5BWXSommaire du match
87 - 2023-01-12421Red Wings4Blackhawks5ALXSommaire du match
89 - 2023-01-14429Capitals0Red Wings2BWSommaire du match
91 - 2023-01-16441Red Wings6Canadiens4AWR5Sommaire du match
94 - 2023-01-19452Penguins4Red Wings2BLSommaire du match
96 - 2023-01-21464Red Wings2Capitals4ALSommaire du match
98 - 2023-01-23477Devils6Red Wings2BLSommaire du match
100 - 2023-01-25486Red Wings1Predators3ALSommaire du match
102 - 2023-01-27501Islanders2Red Wings3BWXXSommaire du match
106 - 2023-01-31520Islanders4Red Wings5BWXXSommaire du match
108 - 2023-02-02530Red Wings3Ducks1AWSommaire du match
110 - 2023-02-04543Maple Leafs5Red Wings4BLXSommaire du match
112 - 2023-02-06553Red Wings2Sharks3ALXSommaire du match
114 - 2023-02-08568Bruins1Red Wings8BWSommaire du match
115 - 2023-02-09576Red Wings2Kings1AWSommaire du match
119 - 2023-02-13592Canucks3Red Wings2BLSommaire du match
121 - 2023-02-15602Red Wings1Flames4ALSommaire du match
124 - 2023-02-18618Bruins6Red Wings2BLSommaire du match
126 - 2023-02-20634Red Wings3Blues2AWSommaire du match
128 - 2023-02-22642Rangers6Red Wings5BLSommaire du match
131 - 2023-02-25661Rangers3Red Wings1BLSommaire du match
133 - 2023-02-27670Red Wings3Oilers4ALXSommaire du match
135 - 2023-03-01685Senateurs0Red Wings2BWSommaire du match
138 - 2023-03-04702Red Wings4Rangers3AWSommaire du match
140 - 2023-03-06710Stars2Red Wings6BWSommaire du match
144 - 2023-03-10730Sabres3Red Wings1BLSommaire du match
149 - 2023-03-15751Maple Leafs2Red Wings3BWXSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
151 - 2023-03-17764Red Wings4Devils2AWSommaire du match
153 - 2023-03-19773Blackhawks1Red Wings6BWSommaire du match
156 - 2023-03-22787Red Wings2Flyers1AWSommaire du match
158 - 2023-03-24797Oilers4Red Wings2BLSommaire du match
160 - 2023-03-26808Red Wings3Devils2AWXSommaire du match
162 - 2023-03-28824Sabres3Red Wings2BLSommaire du match
168 - 2023-04-03845Flyers3Red Wings2BLSommaire du match
170 - 2023-04-05858Red Wings4Senateurs5ALSommaire du match
172 - 2023-04-07868Avalanche1Red Wings3BWSommaire du match
173 - 2023-04-08874Red Wings4Sabres3AWSommaire du match
174 - 2023-04-09881Red Wings3Senateurs4ALSommaire du match
178 - 2023-04-13894Canadiens3Red Wings5BWR5Sommaire du match
182 - 2023-04-17915Blackhawks3Red Wings5BWSommaire du match
183 - 2023-04-18920Red Wings3Rangers1AWSommaire du match
186 - 2023-04-21933Red Wings2Sabres3ALXSommaire du match
188 - 2023-04-23941Capitals4Red Wings3BLSommaire du match
189 - 2023-04-24942Red Wings6Islanders2AWSommaire du match
193 - 2023-04-28962Canadiens1Red Wings5BWR5Sommaire du match
194 - 2023-04-29967Red Wings1Islanders2ALXSommaire du match
195 - 2023-04-30969Red Wings4Penguins3AWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4525
Assistance65,60033,954
Assistance PCT80.00%82.81%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2428 - 80.94% 125,150$5,131,145$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
4,854,670$ 3,306,500$ 1,916,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
16,616$ 3,362,271$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 24,153$ 24,153$




Red Wings Leaders statistiques (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

Red Wings 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

Red Wings 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

Red Wings Leaders statistiques (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

Red Wings 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