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Marlies
GP: 82 | W: 42 | L: 32 | OTL: 8 | P: 92
GF: 285 | GA: 272 | PP%: 19.83% | PK%: 79.86%
DG: Patrick Pellegrino | Morale : 50 | Moyenne d’équipe : 56
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Centre de jeu
Marlies
42-32-8, 92pts
5
FINAL
0 Thunder
39-39-4, 82pts
Team Stats
SOL1StreakL2
23-15-3Home Record20-18-3
19-17-5Away Record19-21-1
5-4-1Last 10 Games3-7-0
3.48Buts par match 3.20
3.32Buts contre par match 3.21
19.83%Pourcentage en avantage numérique21.91%
79.86%Pourcentage en désavantage numérique84.25%
Marlies
42-32-8, 92pts
3
FINAL
4 Wolf Pack
49-27-6, 104pts
Team Stats
SOL1StreakW2
23-15-3Home Record28-12-1
19-17-5Away Record21-15-5
5-4-1Last 10 Games7-3-0
3.48Buts par match 3.66
3.32Buts contre par match 3.29
19.83%Pourcentage en avantage numérique14.81%
79.86%Pourcentage en désavantage numérique84.15%
Meneurs d'équipe
Buts
Jan Jenik
30
Passes
Austin Strand
39
Points
Jan Jenik
63
Plus/Moins
Brett Leason
17
Victoires
Daniil Tarasov
35
Pourcentage d’arrêts
Josef Korenar
0.972

Statistiques d’équipe
Buts pour
285
3.48 GFG
Tirs pour
3050
37.20 Avg
Pourcentage en avantage numérique
19.8%
46 GF
Début de zone offensive
42.2%
Buts contre
272
3.32 GAA
Tirs contre
2851
34.77 Avg
Pourcentage en désavantage numérique
79.9%%
57 GA
Début de la zone défensive
37.7%
Informations de l'équipe

Directeur généralPatrick Pellegrino
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité6,000
Assistance3,814
Billets de saison600


Informations de la formation

Équipe Pro23
Équipe Mineure22
Limite contact 45 / 50
Espoirs10


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
1Jan Jenik (R)XX100.00849176746457736543586865254545050610213795,000$
2Brett LeasonX100.00634296707752765936585867254747050590221842,500$
3Riley Damiani (R)X100.00676278666272756278606060574444050590213803,333$
4Cole Schwindt (R)X100.00756990616966686150566264594444050580203870,000$
5Tim GettingerX100.00844699668355655746505565254444050570231770,000$
6Tyler Madden (R)X100.00675791665755546176586060574444050560213925,000$
7Ryan Suzuki (R)X100.00706583776553535670505860554444050560203894,167$
8Justin AlmeidaX100.00756798596155505875495866524444050550223809,166$
9Shane Bowers (R)X100.00767089667054555265445662534444050540222925,002$
10Kody Clark (R)X100.00737176607158605150475160484444050530213808,333$
11Samuel Helenius (R)X100.00817985667936354556384663444444050500184828,333$
12Kevin Bahl (R)X100.00814683688868786025534878254646050650213795,000$
13Simon BenoitX100.00977087727464755625474773255050050640234950,000$
14Austin StrandX100.00734499638067636325594776254545050620242750,000$
15Jalen ChatfieldX100.00854585686965645625544768255454050610252750,000$
16Darren RaddyshX100.00767481677466705325464365415353050600252750,000$
17Lucas JohansenX100.00746790696759615425474662444444050570231750,000$
18Xavier Bernard (R)X100.00817790697740394525353963374444050540213650,000$
Rayé
1Karl Henriksson (R)X100.00423599666058803950333838405454050460204870,000$
2Albin Eriksson (R)X100.00505098607750703453293244355050050450213825,000$
MOYENNE D’ÉQUIPE100.0074618967715863544649516340464605057
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
1Olle Eriksson Ek (R)100.0045405077454650524949304444050500222900,000$
2Josef Korenar100.0044496170414350524546304545050490231600,000$
Rayé
1Zachary Emond (R)100.0043405073424250514546304444050480211600,000$
MOYENNE D’ÉQUIPE100.004443547343445052464730444405049
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Jan JenikMarlies (Tor)LW/RW813033638129252361603601132698.33%18168420.80671360174000102035140.28%35500000.75010311521
2Brett LeasonMarlies (Tor)RW812137581716021140275712137.64%19154519.08310134017901111034139.74%23400100.7535000034
3Ryan SuzukiMarlies (Tor)C8119355413120691531816713110.50%14114314.121341073000002154.93%144000000.9400000234
4Kevin BahlMarlies (Tor)D791835533520125112124528414.52%105154219.53347251000000111210.00%000100.6900000223
5Cole SchwindtMarlies (Tor)RW812726535360130892677422510.11%16142817.63314281541013712445.09%27500000.7400000344
6Austin StrandMarlies (Tor)D81123951512039122145541118.28%132182122.4851116631890001223100.00%000000.5600000012
7Riley DamianiMarlies (Tor)C8116345045410104150241751846.64%13167120.64310134018701171841158.71%178500000.6016002233
8Tim GettingerMarlies (Tor)LW8122244614380158862187213510.09%16150018.52538401870000724150.00%11200000.6100000431
9Tyler MaddenMarlies (Tor)C81133346310060174207811516.28%14121715.030113190000423257.09%132600000.7625000142
10Simon BenoitMarlies (Tor)D81103343-698102277512939957.75%122187223.123912521860001196100.00%000000.4600110112
11Jalen ChatfieldMarlies (Tor)D8183139126001958212034806.67%97174221.52279481850114204120.00%000000.4500000115
12Lucas JohansenMarlies (Tor)D818303816355976466184012.12%84135116.69145941000096210.00%000000.5600100221
13Justin AlmeidaMarlies (Tor)C81191736916049561493511212.75%1286710.711014170002273353.09%16200000.8313000052
14David GustafssonTorontoC3791827613534859728869.28%367218.181345420001670155.77%57200000.8001100211
15Kody ClarkMarlies (Tor)RW811013232235834076235013.16%88019.90000115000012133.96%5300000.5700100202
16Darren RaddyshMarlies (Tor)D40318211025556265521395.45%5782420.611451975000281000.00%000000.5100001000
17Xavier BernardMarlies (Tor)D5756118581077231751829.41%3765211.4500005000029000.00%000000.3400002000
18Shane BowersMarlies (Tor)C40448-1208122782014.81%32295.731233180000360045.07%7100100.7000000000
19Samuel HeleniusMarlies (Tor)C60033-31151016104100.00%01512.53011110000000055.13%15600000.3900100000
20Albin ErikssonMarlies (Tor)LW25011100643220.00%034813.93000030000270050.00%2200000.0600000000
21Karl HenrikssonMarlies (Tor)C2510100003100100.00%0391.59000001011290037.21%4300000.5000000000
Statistiques d’équipe totales ou en moyenne14162554707251267008017841672276887620559.21%7702311116.3239801194511865235331810332054.19%660600300.63730826273537
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
1Daniil TarasovToronto68352660.9053.2139832221322510420.65223684731
2Olle Eriksson EkMarlies (Tor)186620.9053.2285661464860100.62581368110
3Josef KorenarMarlies (Tor)20000.9720.8174001360000.00%009000
Statistiques d’équipe totales ou en moyenne88413280.9063.184914832602773052318181841


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 moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Albin ErikssonMarlies (Tor)LW212000-07-20Yes205 Lbs6 ft4NoNoNo3Pro & Farm825,000$0$0$No825,000$825,000$Lien
Austin StrandMarlies (Tor)D241997-02-16No216 Lbs6 ft3YesNoYes2Pro & Farm750,000$0$0$No750,000$Lien
Brett LeasonMarlies (Tor)RW221999-04-30No201 Lbs6 ft4NoNoNo1Pro & Farm842,500$0$0$NoLien
Cole SchwindtMarlies (Tor)RW202001-04-25Yes183 Lbs6 ft2NoNoNo3Pro & Farm870,000$0$0$No870,000$870,000$Lien
Darren RaddyshMarlies (Tor)D251996-02-28No200 Lbs6 ft1YesNoYes2Pro & Farm750,000$0$0$No750,000$Lien
Jalen ChatfieldMarlies (Tor)D251996-05-15No188 Lbs6 ft1YesNoYes2Pro & Farm750,000$0$0$No750,000$Lien
Jan JenikMarlies (Tor)LW/RW212000-09-15Yes161 Lbs6 ft1NoNoNo3Pro & Farm795,000$0$0$No795,000$795,000$Lien
Josef KorenarMarlies (Tor)G231998-01-31No185 Lbs6 ft1YesNoNo1Pro & Farm600,000$0$0$NoLien
Justin AlmeidaMarlies (Tor)C221999-02-06No165 Lbs5 ft11NoNoNo3Pro & Farm809,166$0$0$No809,166$809,166$Lien
Karl HenrikssonMarlies (Tor)C202001-02-05Yes174 Lbs5 ft9NoNoNo4Pro & Farm870,000$0$0$No870,000$870,000$870,000$Lien
Kevin BahlMarlies (Tor)D212000-06-27Yes230 Lbs6 ft6NoNoNo3Pro & Farm795,000$0$0$No795,000$795,000$Lien
Kody ClarkMarlies (Tor)RW211999-10-13Yes185 Lbs6 ft3NoNoNo3Pro & Farm808,333$0$0$No808,333$808,333$Lien
Lucas JohansenMarlies (Tor)D231997-11-16No176 Lbs6 ft2NoNoNo1Pro & Farm750,000$0$0$NoLien
Olle Eriksson EkMarlies (Tor)G221999-06-22Yes189 Lbs6 ft3YesNoNo2Pro & Farm900,000$0$0$No900,000$Lien
Riley DamianiMarlies (Tor)C212000-03-20Yes170 Lbs5 ft10NoNoNo3Pro & Farm803,333$0$0$No803,333$803,333$Lien
Ryan SuzukiMarlies (Tor)C202001-05-28Yes176 Lbs6 ft0NoNoNo3Pro & Farm894,167$0$0$No894,167$894,167$Lien
Samuel HeleniusMarlies (Tor)C182002-11-26Yes201 Lbs6 ft6NoNoNo4Pro & Farm828,333$0$0$No828,333$828,333$828,333$Lien
Shane BowersMarlies (Tor)C221999-07-30Yes186 Lbs6 ft2NoNoNo2Pro & Farm925,002$0$0$No925,002$Lien
Simon BenoitMarlies (Tor)D231998-09-19No191 Lbs6 ft3YesNoNo4Pro & Farm950,000$0$0$No950,000$950,000$950,000$Lien
Tim GettingerMarlies (Tor)LW231998-04-13No218 Lbs6 ft6NoNoNo1Pro & Farm770,000$0$0$NoLien
Tyler MaddenMarlies (Tor)C211999-11-09Yes152 Lbs5 ft11NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien
Xavier BernardMarlies (Tor)D212000-01-06Yes205 Lbs6 ft3NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Zachary EmondMarlies (Tor)G212000-06-20Yes181 Lbs6 ft3YesNoNo1Pro & Farm600,000$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2321.74189 Lbs6 ft22.48802,645$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jan JenikRiley DamianiBrett Leason40122
2Tim GettingerRyan SuzukiCole Schwindt30122
3Justin AlmeidaTyler MaddenKody Clark20122
4Jan JenikJustin AlmeidaRiley Damiani10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Simon BenoitAustin Strand40122
2Jalen ChatfieldDarren Raddysh30122
3Lucas JohansenKevin Bahl20122
4Simon BenoitAustin Strand10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jan JenikRiley DamianiBrett Leason60122
2Tim GettingerRyan SuzukiCole Schwindt40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Simon BenoitAustin Strand60122
2Jalen ChatfieldDarren Raddysh40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jan JenikRiley Damiani60122
2Brett LeasonCole Schwindt40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Simon BenoitAustin Strand60122
2Jalen ChatfieldDarren Raddysh40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jan Jenik60122Simon BenoitAustin Strand60122
2Riley Damiani40122Jalen ChatfieldDarren Raddysh40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jan JenikRiley Damiani60122
2Brett LeasonCole Schwindt40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Simon BenoitAustin Strand60122
2Jalen ChatfieldDarren Raddysh40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jan JenikRiley DamianiBrett LeasonSimon BenoitAustin Strand
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jan JenikRiley DamianiBrett LeasonSimon BenoitAustin Strand
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Shane Bowers, Samuel Helenius, Riley DamianiShane Bowers, Samuel HeleniusJan Jenik
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Lucas Johansen, Simon Benoit, Jalen ChatfieldLucas JohansenAustin Strand, Jalen Chatfield
Tirs de pénalité
Jan Jenik, Riley Damiani, Brett Leason, Cole Schwindt, Tim Gettinger
Gardien
#1 : Olle Eriksson Ek, #2 : Josef Korenar


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
1Admirals220000001266110000006421100000062441.0001221330099998110759999431068737013296011327.27%6183.33%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
2Baby Hawks211000008711010000045-11100000042220.50081220009999811077999943106873561643511200.00%7271.43%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
3Bears31100010121202100001010821010000024-240.667122234009999811011899994310687310337235716212.50%9277.78%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
4Bruins42200000812-42110000067-12110000025-340.500813210199998110124999943106873134353010010110.00%140100.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
5Cabaret Lady Mary Ann44000000271116220000001156220000001661081.000275178009999811027699994310687312029188812325.00%9366.67%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
6Caroline321000001192110000006332110000056-140.6671121320099998110989999431068738741247810330.00%10550.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
7Chiefs21001000954110000005231000100043141.0009142300999981108099994310687364211628500.00%7185.71%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
8Chill210001006511000010034-11100000031230.75061117009999811083999943106873872618386116.67%9277.78%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
9Comets20200000214-121010000028-61010000006-600.00024600999981104699994310687382271257300.00%6350.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
10Cougars422000001818020200000610-422000000128440.500183250009999811012199994310687314742308216850.00%6350.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
11Crunch312000001012-22110000067-11010000045-120.33310182800999981101439999431068731021928709222.22%9188.89%11631294355.42%1348262851.29%775140055.36%2054141218376001088560
12Heat22000000844110000003121100000053241.0008152300999981105999994310687357171427400.00%7271.43%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
13Jayhawks21000001770110000004311000000134-130.75071219009999811071999943106873731422403133.33%11463.64%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
14Las Vegas21100000862110000005231010000034-120.50081422009999811082999943106873751513379222.22%30100.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
15Manchots3210000013671010000013-222000000123940.6671323360099998110809999431068731204146446116.67%10280.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
16Minnesota21100000990110000004311010000056-120.5009182700999981108999994310687362211857200.00%8362.50%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
17Monarchs21100000660110000004131010000025-320.50061117009999811073999943106873571010365240.00%4175.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
18Monsters302000101113-2201000108801010000035-220.33311182910999981101009999431068731204530777114.29%15380.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
19Monsters2110000057-2110000003121010000026-420.5005101500999981106999994310687366916347114.29%8275.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
20Oceanics210000016511000000123-11100000042230.75061218009999811057999943106873722319548112.50%7185.71%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
21Oil Kings2000000257-21000000134-11000000123-120.5005914009999811082999943106873641320552150.00%90100.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
22Phantoms32100000151052200000011471010000046-240.66715284300999981101119999431068731002722598337.50%11190.91%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
23Rocket4110110013112211000006422000110077050.62513263900999981101539999431068731734128101400.00%12283.33%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
24Seattle20200000410-61010000024-21010000026-400.000471100999981106199994310687372271841300.00%9277.78%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
25Senators422000001315-22200000085320200000510-540.5001322350099998110165999943106873153443211212216.67%16381.25%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
26Sharks2010001089-11010000035-21000001054120.50081220009999811091999943106873741210572150.00%5180.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
27Sound Tigers31200000911-2211000007701010000024-220.3339152400999981101069999431068731053126528337.50%12375.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
28Spiders3120000047-31010000013-22110000034-120.33347111099998110839999431068731032521725120.00%80100.00%11631294355.42%1348262851.29%775140055.36%2054141218376001088560
29Stars2020000027-51010000015-41010000012-100.000246009999811049999943106873692634357114.29%17288.24%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
30Thunder321000008261010000012-12200000070740.6678162402999981101139999431068738117186610110.00%70100.00%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
31Wolf Pack3000001289-1100000103212000000257-240.66781220009999811011599994310687310331267010110.00%12283.33%01631294355.42%1348262851.29%775140055.36%2054141218376001088560
Total82363202246285272134120150013214513312411617021141401391920.56128551079523999981103050999943106873285179571418352324619.83%2835779.86%21631294355.42%1348262851.29%775140055.36%2054141218376001088560
_Since Last GM Reset82363202246285272134120150013214513312411617021141401391920.56128551079523999981103050999943106873285179571418352324619.83%2835779.86%21631294355.42%1348262851.29%775140055.36%2054141218376001088560
_Vs Conference42181600143139128112197001317466821990001265623480.5711392433822399998110149499994310687314824173609541242419.35%1452284.83%11631294355.42%1348262851.29%775140055.36%2054141218376001088560
_Vs Division26540011197811613220010144404133200010534112140.2699717827503999981101095999943106873910227184619731723.29%731283.56%11631294355.42%1348262851.29%775140055.36%2054141218376001088560

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8292SOL128551079530502851795714183523
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8236322246285272
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4120150132145133
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4116172114140139
Derniers 10 matchs
WLOTWOTL SOWSOL
540001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2324619.83%2835779.86%2
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
99994310687399998110
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
1631294355.42%1348262851.29%775140055.36%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2054141218376001088560


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
6 - 2022-10-127Marlies5Rocket4AWXSommaire du match
7 - 2022-10-1315Bears3Marlies4BWSommaire du match
9 - 2022-10-1530Senators2Marlies4BWSommaire du match
11 - 2022-10-1740Jayhawks3Marlies4BWSommaire du match
14 - 2022-10-2061Stars5Marlies1BLSommaire du match
16 - 2022-10-2278Marlies4Oceanics2AWSommaire du match
18 - 2022-10-2496Marlies3Las Vegas4ALSommaire du match
21 - 2022-10-27119Marlies5Sharks4AWXXSommaire du match
23 - 2022-10-29130Marlies2Monarchs5ALSommaire du match
24 - 2022-10-30142Marlies6Admirals2AWSommaire du match
27 - 2022-11-02159Phantoms2Marlies5BWSommaire du match
30 - 2022-11-05180Bruins3Marlies5BWSommaire du match
31 - 2022-11-06191Marlies5Caroline3AWSommaire du match
33 - 2022-11-08201Las Vegas2Marlies5BWSommaire du match
36 - 2022-11-11221Manchots3Marlies1BLSommaire du match
37 - 2022-11-12230Comets8Marlies2BLSommaire du match
40 - 2022-11-15251Marlies5Manchots2AWSommaire du match
42 - 2022-11-17264Spiders3Marlies1BLSommaire du match
44 - 2022-11-19277Crunch4Marlies2BLSommaire du match
46 - 2022-11-21295Sound Tigers4Marlies5BWSommaire du match
48 - 2022-11-23309Marlies0Spiders3ALSommaire du match
50 - 2022-11-25321Marlies5Minnesota6ALSommaire du match
51 - 2022-11-26335Marlies7Manchots1AWSommaire du match
53 - 2022-11-28348Marlies6Cougars5AWSommaire du match
55 - 2022-11-30363Sharks5Marlies3BLSommaire du match
58 - 2022-12-03385Marlies2Thunder0AWSommaire du match
61 - 2022-12-06409Marlies1Stars2ALSommaire du match
63 - 2022-12-08420Monarchs1Marlies4BWSommaire du match
65 - 2022-12-10438Heat1Marlies3BWSommaire du match
68 - 2022-12-13454Admirals4Marlies6BWSommaire du match
70 - 2022-12-15476Marlies2Wolf Pack3ALXXSommaire du match
72 - 2022-12-17491Marlies2Bears4ALSommaire du match
75 - 2022-12-20513Thunder2Marlies1BLSommaire du match
77 - 2022-12-22525Phantoms2Marlies6BWSommaire du match
82 - 2022-12-27553Marlies4Chiefs3AWXSommaire du match
84 - 2022-12-29572Marlies3Jayhawks4ALXXSommaire du match
86 - 2022-12-31582Marlies2Monsters6ALSommaire du match
89 - 2023-01-03602Chiefs2Marlies5BWSommaire du match
91 - 2023-01-05615Seattle4Marlies2BLSommaire du match
93 - 2023-01-07630Cougars7Marlies4BLSommaire du match
94 - 2023-01-08643Marlies4Phantoms6ALSommaire du match
97 - 2023-01-11658Chill4Marlies3BLXSommaire du match
98 - 2023-01-12666Marlies6Cougars3AWSommaire du match
100 - 2023-01-14683Marlies2Bruins0AWSommaire du match
103 - 2023-01-17706Cabaret Lady Mary Ann3Marlies7BWSommaire du match
105 - 2023-01-19723Oceanics3Marlies2BLXXSommaire du match
107 - 2023-01-21737Marlies2Rocket3ALXSommaire du match
109 - 2023-01-23752Sound Tigers3Marlies2BLSommaire du match
111 - 2023-01-25767Wolf Pack2Marlies3BWXXSommaire du match
113 - 2023-01-27782Senators3Marlies4BWSommaire du match
115 - 2023-01-29800Bears5Marlies6BWXXSommaire du match
118 - 2023-02-01806Bruins4Marlies1BLSommaire du match
127 - 2023-02-10829Marlies3Monsters5ALSommaire du match
128 - 2023-02-11840Monsters4Marlies3BLSommaire du match
132 - 2023-02-15864Baby Hawks5Marlies4BLSommaire du match
135 - 2023-02-18888Rocket1Marlies4BWSommaire du match
136 - 2023-02-19899Marlies4Baby Hawks2AWSommaire du match
138 - 2023-02-21912Marlies4Crunch5ALSommaire du match
141 - 2023-02-24931Minnesota3Marlies4BWSommaire du match
143 - 2023-02-26952Marlies2Seattle6ALSommaire du match
146 - 2023-03-01969Marlies2Oil Kings3ALXXSommaire du match
147 - 2023-03-02979Marlies5Heat3AWSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-04994Marlies0Comets6ALSommaire du match
152 - 2023-03-071015Marlies3Spiders1AWSommaire du match
156 - 2023-03-111043Oil Kings4Marlies3BLXXSommaire du match
158 - 2023-03-131061Crunch3Marlies4BWSommaire du match
160 - 2023-03-151077Monsters1Marlies3BWSommaire du match
162 - 2023-03-171092Caroline3Marlies6BWSommaire du match
163 - 2023-03-181102Marlies3Senators5ALSommaire du match
166 - 2023-03-211127Marlies2Sound Tigers4ALSommaire du match
168 - 2023-03-231140Marlies8Cabaret Lady Mary Ann3AWSommaire du match
170 - 2023-03-251161Marlies0Caroline3ALSommaire du match
171 - 2023-03-261167Marlies3Chill1AWSommaire du match
174 - 2023-03-291186Cabaret Lady Mary Ann2Marlies4BWSommaire du match
177 - 2023-04-011210Marlies2Senators5ALSommaire du match
178 - 2023-04-021223Cougars3Marlies2BLSommaire du match
180 - 2023-04-041230Monsters4Marlies5BWXXSommaire du match
182 - 2023-04-061246Marlies0Bruins5ALSommaire du match
184 - 2023-04-081263Rocket3Marlies2BLSommaire du match
186 - 2023-04-101279Marlies8Cabaret Lady Mary Ann3AWSommaire du match
187 - 2023-04-111289Marlies5Thunder0AWSommaire du match
189 - 2023-04-131304Marlies3Wolf Pack4ALXXSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité40002000
Prix des billets5020
Assistance102,24554,130
Assistance PCT62.34%66.01%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 3814 - 63.57% 151,094$6,194,850$6000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,228,140$ 1,846,083$ 1,846,083$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,716$ 2,228,140$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 9,716$ 0$




Marlies 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

Marlies 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

Marlies 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

Marlies 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

Marlies 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