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Ontario
GP: 82 | W: 32 | L: 43 | OTL: 7 | P: 71
GF: 301 | GA: 344 | PP%: 22.05% | PK%: 73.31%
DG: Remi Brisson | Morale : 50 | Moyenne d’équipe : N/A
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Centre de jeu
Iowa
33-45-4, 70pts
2
FINAL
8 Ontario
32-43-7, 71pts
Team Stats
L4SéquenceW2
20-19-2Fiche domicile18-19-4
13-26-2Fiche domicile14-24-3
3-6-1Derniers 10 matchs6-3-1
3.39Buts par match 3.67
4.12Buts contre par match 4.20
17.01%Pourcentage en avantage numérique22.05%
75.24%Pourcentage en désavantage numérique73.31%
Springfield
45-35-2, 92pts
6
FINAL
7 Ontario
32-43-7, 71pts
Team Stats
W1SéquenceW2
20-20-1Fiche domicile18-19-4
25-15-1Fiche domicile14-24-3
5-4-1Derniers 10 matchs6-3-1
4.46Buts par match 3.67
4.16Buts contre par match 4.20
21.43%Pourcentage en avantage numérique22.05%
76.16%Pourcentage en désavantage numérique73.31%
Meneurs d'équipe
Buts
Axel Jonsson-Fjallby
31
Passes
Axel Jonsson-Fjallby
55
Points
Axel Jonsson-Fjallby
86
Plus/Moins
Nikolai Prokhorkin
6
Victoires
Antti Raanta
21
Pourcentage d’arrêts
Spencer Martin
0.913

Statistiques d’équipe
Buts pour
301
3.67 GFG
Tirs pour
3390
41.34 Avg
Pourcentage en avantage numérique
22.1%
73 GF
Début de zone offensive
40.7%
Buts contre
344
4.20 GAA
Tirs contre
3670
44.76 Avg
Pourcentage en désavantage numérique
73.3%%
87 GA
Début de la zone défensive
42.7%
Informations de l'équipe

Directeur généralRemi Brisson
EntraîneurTodd Reirden
DivisionPacifique
ConférenceConference ouest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,262
Billets de saison300


Informations de la formation

Équipe Pro18
Équipe Mineure20
Limite contact 38 / 50
Espoirs40


Historique d'équipe

Saison actuelle32-43-7 (71PTS)
Historique114-113-20 (0.462%)
Apparitions en séries éliminatoires 1
Historique en séries éliminatoires (W-L)8-6
Coupe Stanley0


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
1Ryan HartmanXX100.00693395898485937078687062845454565000271701,000$
2Jordan SchroederXX100.00663194737171807576717462786356425000311950,000$
3Nick ShoreX100.00673289768080936986686868765755435000292800,000$
4Sven AndrighettoXX100.007033918570829274707172618053425150002921,000,000$
5Nikolai ProkhorkinXXX100.00743090748976837384737265815649605000281900,000$
6Maxim MaminXX100.00753491778775757270697263755655565000272900,000$
7Laurent DauphinX100.006935938480808171777070737555555650002721,050,000$
8Axel Jonsson-Fjallby (R)X100.00753097748473997170697170754646625000242500,000$
9Denis Malgin (R)XXX100.00813097807774897370687470775049625000251500,000$
10Liam O'Brien (R)X100.00927065788675846670666866776060425000271600,000$
11Olli Juolevi (R)X100.00762793818580814451424587774341615000241900,000$
12Jordan OesterleX100.007130797475918854505552897557534850003021,000,000$
13Travis Dermott (R)X100.00762788838584885251504990784949645000251800,000$
14Dylan DeMeloX100.00743468777883865050535086755648515000292800,000$
15Jared CowenX100.007437686885888350504750834769655050003111,500,000$
16Ben HuttonX100.00633588818694946150585685725739485000293900,000$
17Jonathan Kovacevic (R)X100.00833081739084994950524792775050675000241500,000$
Rayé
MOYENNE D’ÉQUIPE100.0074348678828188636562627575555154500
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
1Antti Raanta99.0063858377728287828379727170395000332550,000$
Rayé
MOYENNE D’ÉQUIPE99.006385837772828782837972717039500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Todd Reirden73697477728281USA521500,000$


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
1Axel Jonsson-FjallbyOntario (LA )LW81315586-532099943067623110.13%18150818.6281422652510002895444.80%12500011.1401000734
2Ben HuttonOntario (LA )D76205171-4301037101218741409.17%165174722.99814221202480004194210%000000.8100101412
3Laurent DauphinOntario (LA )C58164864-625554132248521796.45%18126921.89417215719410141753150.59%193500001.0113001333
4Travis DermottOntario (LA )D82234063-54809370232791379.91%170175021.341312251132660112237110%000000.7200000221
5Maxim MaminOntario (LA )LW/RW7630295943610120702667818811.28%11122516.124913441350000157145.38%13000010.9601011344
6Nikolai ProkhorkinOntario (LA )C/LW/RW722731586400811012106518212.86%13143419.9279165523402241601252.82%88600110.8102000232
7Denis MalginOntario (LA )C/LW/RW522726530460123892496216810.84%14109921.14512175518300021062244.96%56500010.9625000281
8Jordan SchroederOntario (LA )C/RW62213152-1415549722076316010.14%12122019.688917502031011882052.26%31000010.8502010211
9Jonathan KovacevicOntario (LA )D79123951-284017691152731307.89%188183823.2731215772590000212110%000100.5500000210
10Jordan OesterleOntario (LA )D8213344733007688167411067.78%162156319.0771118741940004186100%000000.6000000322
11Sven AndrighettoOntario (LA )LW/RW82242044-851590101276771998.70%12125315.2913411320001142247.58%12400000.7011100201
12Nick ShoreOntario (LA )C82102636-1128051148202441164.95%14114914.020117390001130054.20%171400000.6300000102
13Ryan HartmanOntario (LA )LW/RW82131730-121003863204591526.37%395811.6911236000041052.11%7100000.6311000210
14Dylan DeMeloOntario (LA )D8241822-1958084507923495.06%106103212.5900001000013010%000000.4300000000
15Liam O'BrienOntario (LA )LW8113922-1074014058112408311.61%167108.770335260002580055.90%41500000.6200000002
16Jacob De La RoseLosAngelesC/LW2371320110023478335598.43%951022.2121316830002761051.42%74100000.7801000020
17Jared CowenOntario (LA )D7821113-28822071425923423.39%8087811.261121437011169000%000000.3000112001
18Olli JuoleviOntario (LA )D822810-1216027314214284.76%706387.78000000001610030.00%2000000.3100000000
19Zack SmithLosAngelesC/LW1315608018202813183.57%319114.76000140000330049.47%28500000.6311000001
20Radko GudasLosAngelesD71341140228181095.56%1016523.61101725000021000%000000.4800000000
21Juuso ValimakiLosAngelesD1011200003000%02020.280002300000000%000000.9900000000
Statistiques d’équipe totales ou en moyenne1333297515812-11973755147214763361100123768.84%10942216616.63731292027762435246311833291651.40%732100250.73618335353127
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
1Antti RaantaOntario (LA )47212330.9093.9628024018520300110.667124723323
2Spencer MartinLosAngeles31111530.9133.8418276011713500200.75083037231
Statistiques d’équipe totales ou en moyenne78323860.9113.9146301003023380031207760554


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Recrue Poids Taille Non-échange Disponible pour échange Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Lien
Antti RaantaOntario (LA )G331989-05-12 10:43:28No200 Lbs6 ft0NoNoNoNo2Pro & Farm550,000$3,216$0$0$No550,000$Lien
Axel Jonsson-FjallbyOntario (LA )LW241998-02-10 22:19:44Yes189 Lbs6 ft1NoNoNoNo2Pro & Farm500,000$2,924$0$0$No500,000$
Ben HuttonOntario (LA )D291993-04-20No188 Lbs6 ft2NoNoNoNo3Pro & Farm900,000$5,263$0$0$No900,000$900,000$Lien
Denis MalginOntario (LA )C/LW/RW251997-01-18 22:22:42Yes182 Lbs5 ft9NoNoNoNo1Pro & Farm500,000$2,924$0$0$No
Dylan DeMeloOntario (LA )D291993-05-01No198 Lbs6 ft1NoNoNoNo2Pro & Farm800,000$4,678$0$0$No800,000$Lien
Jared CowenOntario (LA )D311991-01-25No236 Lbs6 ft5NoNoNoNo1Pro & Farm1,500,000$8,772$0$0$NoLien
Jonathan KovacevicOntario (LA )D241997-07-12 03:47:26Yes208 Lbs6 ft4NoNoNoNo1Pro & Farm500,000$2,924$0$0$No
Jordan OesterleOntario (LA )D301992-06-25No186 Lbs6 ft0NoNoNoNo2Pro & Farm1,000,000$5,848$0$0$No1,000,000$Lien
Jordan SchroederOntario (LA )C/RW311990-09-29No189 Lbs5 ft9NoNoNoNo1Pro & Farm950,000$5,556$0$0$NoLien
Laurent DauphinOntario (LA )C271995-03-27 08:02:00No186 Lbs6 ft0NoNoNoNo2Pro & Farm1,050,000$6,140$0$0$No1,050,000$Lien
Liam O'BrienOntario (LA )LW271994-07-29 01:59:13Yes213 Lbs6 ft1NoNoNoNo1Pro & Farm600,000$3,509$0$0$No
Maxim MaminOntario (LA )LW/RW271995-01-13 07:46:56No206 Lbs6 ft2NoNoNoNo2Pro & Farm900,000$5,263$0$0$No900,000$Lien
Nick ShoreOntario (LA )C291992-09-26No207 Lbs6 ft1NoNoNoNo2Pro & Farm800,000$4,678$0$0$No800,000$Lien
Nikolai ProkhorkinOntario (LA )C/LW/RW281993-10-17No192 Lbs6 ft3NoNoNoNo1Pro & Farm900,000$5,263$0$0$NoLien
Olli JuoleviOntario (LA )D241998-05-05 05:28:55Yes182 Lbs6 ft2NoNoNoNo1Pro & Farm900,000$5,263$0$0$No
Ryan HartmanOntario (LA )LW/RW271994-09-20No188 Lbs6 ft0NoNoNoNo1Pro & Farm701,000$4,099$0$0$NoLien
Sven AndrighettoOntario (LA )LW/RW291993-03-21No195 Lbs5 ft10NoNoNoNo2Pro & Farm1,000,000$5,848$0$0$No1,000,000$Lien
Travis DermottOntario (LA )D251996-12-22 04:53:17Yes205 Lbs6 ft0NoNoNoNo1Pro & Farm800,000$4,678$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1827.72197 Lbs6 ft11.56825,056$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Denis MalginLaurent DauphinJordan Schroeder35122
2Axel Jonsson-FjallbyNikolai ProkhorkinMaxim Mamin33122
3Sven AndrighettoNick ShoreRyan Hartman30122
4Liam O'BrienLaurent DauphinJordan Schroeder2122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jonathan KovacevicBen Hutton35122
2Travis DermottJordan Oesterle30122
3Dylan DeMeloJared Cowen25122
4Olli JuoleviJonathan Kovacevic10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Denis MalginLaurent DauphinJordan Schroeder50122
2Axel Jonsson-FjallbyNikolai ProkhorkinMaxim Mamin50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jonathan KovacevicBen Hutton50122
2Travis DermottJordan Oesterle50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Laurent DauphinJordan Schroeder50122
2Denis MalginNikolai Prokhorkin50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jonathan KovacevicBen Hutton50122
2Travis DermottJordan Oesterle50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Laurent Dauphin50122Jonathan KovacevicBen Hutton50122
2Jordan Schroeder50122Travis DermottJordan Oesterle50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Laurent DauphinJordan Schroeder50122
2Denis MalginNikolai Prokhorkin50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jonathan KovacevicBen Hutton50122
2Travis DermottJordan Oesterle50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Denis MalginLaurent DauphinJordan SchroederJonathan KovacevicBen Hutton
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Denis MalginLaurent DauphinJordan SchroederJonathan KovacevicBen Hutton
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Sven Andrighetto, Ryan Hartman, Liam O'BrienSven Andrighetto, Ryan HartmanLiam O'Brien
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dylan DeMelo, Jared Cowen, Olli JuoleviDylan DeMeloJared Cowen, Olli Juolevi
Tirs de pénalité
Laurent Dauphin, Jordan Schroeder, Denis Malgin, Nikolai Prokhorkin, Axel Jonsson-Fjallby
Gardien
#1 : Antti Raanta, #2 :
Lignes d’attaque personnalisées en prolongation
Laurent Dauphin, Jordan Schroeder, Denis Malgin, Nikolai Prokhorkin, Axel Jonsson-Fjallby, Maxim Mamin, Maxim Mamin, Sven Andrighetto, Ryan Hartman, Liam O'Brien, Nick Shore
Lignes de défense personnalisées en prolongation
Jonathan Kovacevic, Ben Hutton, Travis Dermott, Jordan Oesterle, Dylan DeMelo


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
1Abbotsford622001102222030100110912-3321000001310370.58322335500127917972621102113711205126681559534514.71%25772.00%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
2Bakersfield615000002235-1330300000518-13312000001717020.167223557101279179727811021137112051298923211730930.00%16475.00%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
3Bridgeport20200000713-61010000046-21010000037-400.000711180012791797691102113711205111539143510440.00%6433.33%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
4Charlotte21100000511-6110000004311010000018-720.50051015001279179774110211371120511213222343133.33%11372.73%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
5Cleveland3210000015105110000007342110000087140.66715294400127917971021102113711205111544455610440.00%12191.67%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
6Coachella Valley412000011619-320100001911-22110000078-130.37516314700127917971531102113711205118756427020630.00%16381.25%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
7Eagles622001012524131100001911-2311001001613360.500254166001279179722411021137112051247716010226311.54%28967.86%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
8Grand Rapids21000001770110000004311000000134-130.7507132000127917979511021137112051702014398225.00%70100.00%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
9Hartford2110000078-11010000036-31100000042220.5007132000127917979211021137112051783110368225.00%5260.00%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
10Hershey2010001045-1100000102111010000024-220.5004590012791797671102113711205195152724600.00%10190.00%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
11Iowa42101000191272100100013672110000066060.75019335200127917971571102113711205116153366016425.00%16381.25%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
12Laval2020000048-41010000024-21010000024-200.00048120012791797861102113711205195252231600.00%10280.00%11695347048.85%1660363645.65%665141946.86%1911128819636341084534
13Lehigh Valley20200000210-81010000005-51010000025-300.0002350012791797581102113711205184292445700.00%11645.45%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
14Manitoba413000001320-72110000078-120200000612-620.2501325380012791797170110211371120511854734771417.14%16381.25%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
15Providence2020000037-41010000024-21010000013-200.00033600127917976611021137112051102262842500.00%13469.23%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
16Rochester3210000015962110000011651100000043140.66715274200127917971351102113711205111629336612541.67%13284.62%11695347048.85%1660363645.65%665141946.86%1911128819636341084534
17Rockford42100100161602110000067-121000100109150.62516284400127917971831102113711205115742337314321.43%11372.73%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
18San Diego624000001824-632100000880303000001016-640.333182947001279179725811021137112051271736412223521.74%30776.67%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
19San Jose623001002428-4320001001614230300000814-650.417244468001279179726611021137112051287985111429724.14%23769.57%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
20Springfield413000001622-621100000912-320200000710-320.25016294500127917971741102113711205122259347815746.67%17852.94%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
21Syracuse413000001518-320200000911-22110000067-120.2501525400012791797153110211371120511545529581317.69%11372.73%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
22Texas43100000191272110000098122000000104660.75019345300127917971691102113711205116668288416425.00%14471.43%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
23Wilkes-Barre/Scranton21000010743100000103211100000042241.000710170012791797991102113711205178261241600.00%5180.00%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
Total82284301433301344-4341141901232151169-1841142400201150175-25710.43330151982010127917973390110211371120513670111174914993317322.05%3268773.31%21695347048.85%1660363645.65%665141946.86%1911128819636341084534
_Since Last GM Reset82284301433301344-4341141901232151169-1841142400201150175-25710.43330151982010127917973390110211371120513670111174914993317322.05%3268773.31%21695347048.85%1660363645.65%665141946.86%1911128819636341084534
_Vs Conference54192801411209233-2427101201211100115-152791600200109118-9470.435209356565101279179722941102113711205124147394569802304921.30%2075871.98%01695347048.85%1660363645.65%665141946.86%1911128819636341084534
_Vs Division2891600311102128-261456002114763-1614410001005565-10240.429102172274101279179712171102113711205113094002445181363223.53%1102874.55%01695347048.85%1660363645.65%665141946.86%1911128819636341084534

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8271W2301519820339036701111749149910
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8228431433301344
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4114191232151169
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4114240201150175
Derniers 10 matchs
WLOTWOTL SOWSOL
630001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3317322.05%3268773.31%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
1102113711205112791797
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
1695347048.85%1660363645.65%665141946.86%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1911128819636341084534


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
16Ontario4Abbotsford2AWSommaire du match
317Abbotsford4Ontario3BLXSommaire du match
529Ontario4Eagles5ALXSommaire du match
636Eagles4Ontario2BLSommaire du match
1059Bakersfield4Ontario2BLSommaire du match
1272Ontario4San Diego5ALSommaire du match
1482San Jose5Ontario4BLXSommaire du match
1697Ontario3San Diego5ALSommaire du match
17104San Diego2Ontario4BWSommaire du match
19115Ontario3San Jose4ALSommaire du match
22131Bakersfield9Ontario2BLSommaire du match
23140Ontario7Cleveland4AWSommaire du match
25151Rockford3Ontario1BLSommaire du match
27165Ontario3Bakersfield5ALSommaire du match
29175Texas3Ontario6BWSommaire du match
31190Abbotsford3Ontario4BWXXSommaire du match
33200Ontario4Texas3AWSommaire du match
34210Ontario6Rockford7ALXSommaire du match
37224Cleveland3Ontario7BWSommaire du match
39237Ontario1Cleveland3ALSommaire du match
40245Providence4Ontario2BLSommaire du match
42258Ontario6Texas1AWSommaire du match
44272Texas5Ontario3BLSommaire du match
48290Manitoba6Ontario3BLSommaire du match
50302Ontario2Lehigh Valley5ALSommaire du match
52314Grand Rapids3Ontario4BWSommaire du match
54326Ontario4Manitoba6ALSommaire du match
56337Ontario2Hershey4ALSommaire du match
58346Ontario2Coachella Valley4ALSommaire du match
59355San Diego4Ontario1BLSommaire du match
61370Bakersfield5Ontario1BLSommaire du match
65388Abbotsford5Ontario2BLSommaire du match
67404Ontario3San Diego6ALSommaire du match
69411San Jose5Ontario6BWSommaire du match
71424Ontario5Abbotsford3AWSommaire du match
73437San Jose4Ontario6BWSommaire du match
74448Ontario1Charlotte8ALSommaire du match
76460Laval4Ontario2BLSommaire du match
78470Ontario4Abbotsford5ALSommaire du match
80486Hershey1Ontario2BWXXSommaire du match
82497Ontario7Bakersfield8ALSommaire du match
83507Syracuse6Ontario5BLSommaire du match
86519Ontario3Bridgeport7ALSommaire du match
88532Bridgeport6Ontario4BLSommaire du match
90545Ontario2Iowa5ALSommaire du match
91553Coachella Valley4Ontario3BLSommaire du match
94566Ontario4Hartford2AWSommaire du match
96579Ontario2Laval4ALSommaire du match
97585Manitoba2Ontario4BWSommaire du match
100600Ontario4Wilkes-Barre/Scranton2AWSommaire du match
101608Ontario3San Jose4ALSommaire du match
103616Wilkes-Barre/Scranton2Ontario3BWXXSommaire du match
105633Syracuse5Ontario4BLSommaire du match
107648Ontario1Providence3ALSommaire du match
109659Hartford6Ontario3BLSommaire du match
111673Ontario9Eagles4AWSommaire du match
112681San Diego2Ontario3BWSommaire du match
115693Ontario4Iowa1AWSommaire du match
117704Ontario2Syracuse4ALSommaire du match
118711Rockford4Ontario5BWSommaire du match
120728Rochester2Ontario9BWSommaire du match
123744Ontario4Syracuse3AWSommaire du match
124746Ontario2Manitoba6ALSommaire du match
126758Eagles3Ontario2BLXXSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
128770Ontario3Springfield5ALSommaire du match
131780Charlotte3Ontario4BWSommaire du match
134793Ontario3Eagles4ALSommaire du match
135802Ontario5Coachella Valley4AWSommaire du match
137811Coachella Valley7Ontario6BLXXSommaire du match
140827Rochester4Ontario2BLSommaire du match
142837Ontario4Rochester3AWSommaire du match
144848Ontario2San Jose6ALSommaire du match
146860Eagles4Ontario5BWSommaire du match
147868Ontario4Rockford2AWSommaire du match
149881Ontario7Bakersfield4AWSommaire du match
150887Lehigh Valley5Ontario0BLSommaire du match
154906Springfield6Ontario2BLSommaire du match
155914Ontario4Springfield5ALSommaire du match
157928Iowa4Ontario5BWXSommaire du match
159939Ontario3Grand Rapids4ALXXSommaire du match
163959Iowa2Ontario8BWSommaire du match
168974Springfield6Ontario7BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance62,07730,670
Assistance PCT75.70%74.80%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2262 - 75.40% 132,496$5,432,335$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,051,808$ 1,485,100$ 1,485,100$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,685$ 1,554,728$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 11,609$ 11,609$




Ontario 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
1Joel Kiviranta24614616831455156416317120712.10%27495520.14415596254000029652.90%71.27612
2Sami Niku24258206264108801272815869.90%475542722.432752793220557660%00.9700
3Brendan Lemieux242117126243104420831249106710.97%41435618.00233962208101114655.16%31.1202
4Derick Brassard246102134236436113637984712.04%43469819.10283866179000118652.91%11.0000
5Carl Grundstrom16268104172748823816463210.76%22319919.75162844154000412243.58%01.0800

Ontario 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
1Al Montoya82621640.9322.9949428224636180000.91724
2Mike Condon90522870.9103.79527110133337140320.7789
3Pheonix Copley54351350.9152.8132304115117770000.69213
4Michael Hutchinson2416800.9293.0914370074103600000

Ontario 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
Saison régulière
2082452106244329238914126702132178106724119140411215113219116329581910021281009112288593592299357270977788013703807820.53%3695784.55%31809319856.57%1732310655.76%739132155.94%1995135819006301076538
21824922035303912861054125100231019514352412412012201961435311539169110821114312911374027124914321314443719108697215563368625.60%3997281.95%42112389654.21%1962379351.73%785147953.08%1957131419126311088541
21824922035303912861054125100231019514352412412012201961435311539169110821114312911374027124914321314443719108697215563368625.60%3997281.95%42112389654.21%1962379351.73%785147953.08%1957131419126311088541
Total Saison régulière246941130121188911947-36123495007575459462-3123456305613452485-3324791115642475323712732472798223184324632781709976298321094409103922121.27%91722975.03%651921025750.62%48811022947.72%2041418848.73%586940005788188532341608
Séries éliminatoires
20221480000077601712930000043301310550000034304287713521201302023478725824525232705222225434891617.98%1051684.76%245486252.67%43983352.70%19735655.34%543371530168291147
Total Séries éliminatoires1486000004446-28620000027234624000001723-6164476120001511171471175140155146811312123768913.24%56689.29%229856852.46%26654448.90%10723345.92%33923132210317887

Ontario 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
1Nikita Kucherov22111021628286915.94%242719.41145900003158.33%00.9800
2Nick Bjugstad2291019526358510.59%342319.251341100000053.83%00.9000
3Sami Niku2221618442513238.70%2951623.47167130110100%00.7000
4Nicolas Roy22611173263546847.14%544520.251342900001052.22%00.7600
5Brendan Lemieux22313162307723704.29%840818.582241600000157.69%00.7800

Ontario 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
1Pheonix Copley139310.9162.51788003339501000
2Mike Condon105400.9132.81576012731000000