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Toronto
GP: 82 | W: 38 | L: 37 | OTL: 7 | P: 83
GF: 259 | GA: 262 | PP%: 18.95% | PK%: 83.18%
DG: Richard Gadbois | Morale : 50 | Moyenne d’équipe : N/A
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Centre de jeu
Texas
52-27-3, 107pts
2
FINAL
1 Toronto
38-37-7, 83pts
Team Stats
L1StreakW1
30-9-2Home Record21-15-5
22-18-1Away Record17-22-2
5-5-0Last 10 Games2-7-1
3.35Buts par match 3.16
2.71Buts contre par match 3.20
15.54%Pourcentage en avantage numérique18.95%
86.51%Pourcentage en désavantage numérique83.18%
Iowa
33-42-7, 73pts
2
FINAL
6 Toronto
38-37-7, 83pts
Team Stats
L1StreakW1
18-20-3Home Record21-15-5
15-22-4Away Record17-22-2
5-4-1Last 10 Games2-7-1
2.73Buts par match 3.16
3.61Buts contre par match 3.20
17.45%Pourcentage en avantage numérique18.95%
81.48%Pourcentage en désavantage numérique83.18%
Meneurs d'équipe
Buts
Jimmy Vesey
25
Passes
Luca Sbisa
54
Points
Luca Sbisa
73
Plus/Moins
Nikita Tryamkin
16
Victoires
Michal Neuvirth
17
Pourcentage d’arrêts
Jake Oettinger
0.925

Statistiques d’équipe
Buts pour
259
3.16 GFG
Tirs pour
2609
31.82 Avg
Pourcentage en avantage numérique
19.0%
65 GF
Début de zone offensive
41.0%
Buts contre
262
3.20 GAA
Tirs contre
2755
33.60 Avg
Pourcentage en désavantage numérique
83.2%%
55 GA
Début de la zone défensive
41.4%
Informations de l'équipe

Directeur généralRichard Gadbois
EntraîneurMarty Raymond
DivisionNord
ConférenceConference est
Capitaine
Assistant #1Nick Bonino
Assistant #2Valtteri Filppula


Informations de l’aréna

Capacité3,000
Assistance2,276
Billets de saison300


Informations de la formation

Équipe Pro20
Équipe Mineure18
Limite contact 38 / 50
Espoirs12


Historique d'équipe

Saison actuelle38-37-7 (83PTS)
Historique76-74-12 (0.469%)
Apparitions en séries éliminatoires 0
Historique en séries éliminatoires (W-L)-
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
1Nikolai ZherdevXX100.006833936175679067846368608397951750003521,240,000$
2Oscar MollerXX100.00662899757785806770696972758475255000323500,000$
3Rocco GrimaldiXX100.00731996766778816970667263825654545000281750,000$
4Valtteri Filppula (A)XXX100.00612391667580907280706863848783150003721,350,000$
5Jimmy VeseyXX100.00743175768782957370727265805545565000281675,000$
6David DesharnaisXX100.005725977166819271867271648876703450003421,200,000$
7Nick Bonino (A)XX100.00573692587578836885686467796490305000332850,000$
8Kyle OkposoX100.007034937378888773706573598562533750003321,203,000$
9Linus OmarkXX100.00602395617167847250646864757859265000342650,000$
10Luca SbisaX100.00684172808181955815852866270534150003121,000,000$
11Nikita TryamkinX100.00763565799382995455555287804939555000262900,000$
12Brent SeabrookX100.006432885581769756315648887592902350003631,180,000$
13Mark BorowieckiX100.00815543609174874850484987626360345000312800,000$
14Casey NelsonX100.00743482768182835150504487715555515000283500,000$
15Mark PysykX100.006234957580888658505261847858575950002931,000,500$
Rayé
1Jim O'BrienXX100.00652292607870896573626468755858285000322951,000$
2Joe ColborneXXX100.00743981718681867098727061836161515000311999,999$
3Juuso RiikolaX100.00772985808782804851494483775349605000272650,000$
MOYENNE D’ÉQUIPE100.0068328570797988636262627377686438500
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
1David Rittich100.0071878891839596939393935959575000283500,000$
2Michal Neuvirth100.0065818287789397989882857978435000333500,000$
Rayé
MOYENNE D’ÉQUIPE100.006884858981949796968889696950500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Marty Raymond72726974868769CAN592550,000$


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
1Luca SbisaToronto (TOR)D82195473792101091241584911012.03%121188322.97101323762910222244410.00%000100.7800002342
2Valtteri FilppulaToronto (TOR)C/LW/RW82223961-19300541192015415510.95%6165820.23613195428521331414051.71%120100000.7400000340
3Jimmy VeseyToronto (TOR)LW/RW76253661836014998252752149.92%14166621.92514195227100052232050.40%25000000.7300000532
4Nikita TryamkinToronto (TOR)D6793948168401237211732797.69%118156623.3861016712460111208210.00%000000.6100000114
5Mikhail GrigorenkoTorontoC/LW72232447-928037842115014010.90%11111115.435510261290112386253.62%84300000.8500000324
6Mark PysykToronto (TOR)D82133447-142202981161651088.07%115167120.3861117702320111218200.00%000000.5600000003
7David DesharnaisToronto (TOR)C/LW6315314682018148164571249.15%9147923.48312153622512362433154.55%139700100.6200000042
8Kyle OkposoToronto (TOR)RW82202040-2150010473230541788.70%3148218.086814462720001110047.06%13600000.5400000012
9Joe ColborneToronto (TOR)C/LW/RW63132235-150109689174391187.47%10129520.57111124022921371371060.23%87000000.5400101132
10Mike RichardsTorontoC/LW2815203514295886890205416.67%965223.3236927970000962055.44%96500011.0700010232
11Brent SeabrookToronto (TOR)D80102131-74405977100446910.00%146180322.545510602800110254110.00%000100.3400000131
12Rocco GrimaldiToronto (TOR)LW/RW82151530-213209371189391467.94%5103212.591127610000190040.91%8800000.5800000411
13Juuso RiikolaToronto (TOR)D68720272200434038163218.42%5693113.7000004011176100.00%000000.5800000102
14Nick BoninoToronto (TOR)C/LW8271724-2115321008132818.64%489810.960001120111330155.53%95800000.5300001111
15Mark BorowieckiToronto (TOR)D8281422-2116735175398220479.76%120128315.6542628109011186000.00%000000.3400025000
16Nikolai ZherdevToronto (TOR)LW/RW8291221036083289839659.18%698712.04000060001513253.21%10900000.4300000111
17Linus OmarkToronto (TOR)LW/RW79111021-6100253891277812.09%36798.602134250000214136.76%6800000.6200000013
18Oscar MollerToronto (TOR)LW/RW2281220-240224077215710.39%343919.9815613741012312148.48%9900000.9100000212
19Jim O'BrienToronto (TOR)C/RW81527560203231153216.13%23774.6600000000060050.75%26600000.3700000101
20Casey NelsonToronto (TOR)D22156-7201017134117.69%2232714.870001310118000.00%000000.3700000010
21John MooreTorontoD6044-200142180.00%89716.300111400001000.00%000000.8200000000
Statistiques d’équipe totales ou en moyenne1383255451706-727556513701442256075319069.96%7912332616.8764118182613286671320352155371154.04%725000310.6100139293435
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
1Michal NeuvirthToronto (TOR)35171430.9053.2120160210811410010.00%0358522
2David RittichToronto (TOR)27101410.9083.16153620818850100.00%02451301
3Jake OettingerToronto53200.9252.4030021121590000.00%054201
Statistiques d’équipe totales ou en moyenne67303040.9083.133852432012185011064631024


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 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 10Link
Brent SeabrookToronto (TOR)D361985-04-20No234 Lbs6 ft3NoNoNoNo3Pro & Farm1,180,000$0$0$No1,180,000$1,180,000$
Casey NelsonToronto (TOR)D281992-07-18No189 Lbs6 ft1NoNoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
David DesharnaisToronto (TOR)C/LW341986-09-14No177 Lbs5 ft7NoNoNoNo2Pro & Farm1,200,000$0$0$No1,200,000$Lien
David RittichToronto (TOR)G281992-08-08 05:28:46No208 Lbs6 ft3NoNoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Jim O'BrienToronto (TOR)C/RW321989-01-29No207 Lbs6 ft2NoNoNoNo2Pro & Farm951,000$0$0$No951,000$Lien
Jimmy VeseyToronto (TOR)LW/RW281993-05-26No210 Lbs6 ft3NoNoNoNo1Pro & Farm675,000$0$0$NoLien
Joe ColborneToronto (TOR)C/LW/RW311990-01-30No218 Lbs6 ft5NoNoNoNo1Pro & Farm999,999$0$0$NoLien
Juuso RiikolaToronto (TOR)D271993-11-09No192 Lbs6 ft0NoNoNoNo2Pro & Farm650,000$0$0$No650,000$Lien
Kyle OkposoToronto (TOR)RW331988-04-16No223 Lbs6 ft0NoNoNoNo2Pro & Farm1,203,000$0$0$No1,203,000$Lien
Linus OmarkToronto (TOR)LW/RW341987-02-05No191 Lbs5 ft10NoNoNoNo2Pro & Farm650,000$0$0$No650,000$Lien
Luca SbisaToronto (TOR)D311990-01-01No218 Lbs6 ft2NoNoNoNo2Pro & Farm1,000,000$0$0$No1,000,000$Lien
Mark BorowieckiToronto (TOR)D311989-07-12No209 Lbs6 ft2NoNoNoNo2Pro & Farm800,000$0$0$No800,000$Lien
Mark PysykToronto (TOR)D291992-01-11No206 Lbs6 ft1NoNoNoNo3Pro & Farm1,000,500$0$0$No1,000,500$1,000,500$Lien
Michal NeuvirthToronto (TOR)G331988-01-21 14:34:09No230 Lbs6 ft1NoNoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Nick BoninoToronto (TOR)C/LW331988-04-20No200 Lbs6 ft1NoNoNoNo2Pro & Farm850,000$0$0$No850,000$Lien
Nikita TryamkinToronto (TOR)D261994-08-30No267 Lbs6 ft7NoNoNoNo2Pro & Farm900,000$0$0$No900,000$Lien
Nikolai ZherdevToronto (TOR)LW/RW351985-11-05No211 Lbs6 ft2NoNoNoNo2Pro & Farm1,240,000$0$0$No1,240,000$
Oscar MollerToronto (TOR)LW/RW321989-01-22No195 Lbs5 ft11NoNoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Rocco GrimaldiToronto (TOR)LW/RW281993-02-08No183 Lbs5 ft6NoNoNoNo1Pro & Farm750,000$0$0$NoLien
Valtteri FilppulaToronto (TOR)C/LW/RW371984-03-20No189 Lbs6 ft0NoNoNoNo2Pro & Farm1,350,000$0$0$No1,350,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2031.30208 Lbs6 ft12.15869,975$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jimmy VeseyDavid DesharnaisValtteri Filppula40122
2Oscar MollerNick BoninoKyle Okposo30122
3Rocco GrimaldiLinus OmarkNikolai Zherdev20122
4Linus OmarkDavid DesharnaisJimmy Vesey10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brent SeabrookNikita Tryamkin40122
2Luca SbisaMark Pysyk30122
3Casey NelsonMark Borowiecki20122
4Brent SeabrookNikita Tryamkin10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jimmy VeseyDavid DesharnaisValtteri Filppula60122
2Oscar MollerNick BoninoKyle Okposo40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brent SeabrookNikita Tryamkin60122
2Luca SbisaMark Pysyk40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1David DesharnaisJimmy Vesey60122
2Valtteri FilppulaOscar Moller40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brent SeabrookNikita Tryamkin60122
2Luca SbisaMark Pysyk40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1David Desharnais60122Brent SeabrookNikita Tryamkin60122
2Jimmy Vesey40122Luca SbisaMark Pysyk40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1David DesharnaisJimmy Vesey60122
2Valtteri FilppulaOscar Moller40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brent SeabrookNikita Tryamkin60122
2Luca SbisaMark Pysyk40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jimmy VeseyDavid DesharnaisValtteri FilppulaBrent SeabrookNikita Tryamkin
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jimmy VeseyDavid DesharnaisValtteri FilppulaBrent SeabrookNikita Tryamkin
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Rocco Grimaldi, Nikolai Zherdev, Kyle OkposoRocco Grimaldi, Nikolai ZherdevKyle Okposo
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Casey Nelson, Mark Borowiecki, Luca SbisaCasey NelsonMark Borowiecki, Luca Sbisa
Tirs de pénalité
David Desharnais, Jimmy Vesey, Valtteri Filppula, Oscar Moller, Kyle Okposo
Gardien
#1 : Michal Neuvirth, #2 : David Rittich


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
1Abbotsford210010001156100010004311100000072541.0001120310088867966683388887117551514375120.00%5180.00%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
2Bakersfield2020000048-41010000023-11010000025-300.00047110088867964083388887117671824358225.00%12283.33%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
3Charlotte412001001014-4210001007522020000039-630.3751017270188867961228338888711715653396314428.57%17194.12%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
4Cleveland624000001720-332100000108230300000712-540.3331734510088867961778338888711719063427624833.33%21290.48%11646308953.29%1637311552.55%729132155.19%1952131419226271069539
5Grand Rapids103502000343225220100019163513010001516-1100.5003458920088867963038338888711731411511517250918.00%49785.71%21646308953.29%1637311552.55%729132155.19%1952131419226271069539
6Hartford4400000015114220000008622200000075281.000152843008886796127833888871171333230701417.14%15286.67%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
7Hershey4210100013112220000007252010100069-360.7501324370088867961368338888711713237416520420.00%120100.00%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
8Iowa220000001349110000006241100000072541.0001324370088867961008338888711746982816531.25%20100.00%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
9Laval651000002215732100000871330000001486100.83322406201888679621383388887117183526611426519.23%21385.71%11646308953.29%1637311552.55%729132155.19%1952131419226271069539
10Lehigh Valley42100100161422200000011652010010058-350.6251628440088867961558338888711714838356925520.00%15380.00%11646308953.29%1637311552.55%729132155.19%1952131419226271069539
11Manitoba21100000111011010000034-11100000086220.50011213200888679682833888871177114132810330.00%4325.00%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
12Milwaukee21100000752110000006241010000013-220.500711180088867965483388887117601510471119.09%3233.33%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
13Ontario21100000770110000005321010000024-220.50071219008886796648338888711764211333700.00%4250.00%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
14Providence605010001322-93030000059-430201000813-520.16713253800888679618583388887117216524210424312.50%21480.95%11646308953.29%1637311552.55%729132155.19%1952131419226271069539
15Rochester623001001820-232100000105530200100815-750.4171833511188867962058338888711718854469228621.43%22386.36%11646308953.29%1637311552.55%729132155.19%1952131419226271069539
16Rockford2020000037-41010000013-21010000024-200.000358008886796428338888711776292440400.00%12375.00%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
17San Diego210001008621000010045-11100000041330.750815230088867967383388887117701916407114.29%8275.00%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
18San Jose20200000311-81010000006-61010000035-200.00034700888679657833888871171042532334125.00%15566.67%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
19Springfield2020000029-71010000013-21010000016-500.000235008886796618338888711770211834500.00%70100.00%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
20Texas2010010036-31000010012-11010000024-210.2503690088867965583388887117661426316116.67%13376.92%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
21Tucson210001004311000010012-11100000031230.7504711008886796478338888711773263732600.00%16193.75%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
22Utica413000001113-22020000047-32110000076120.250112132108886796948338888711715244388011218.18%18383.33%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
23Wilkes-Barre/Scranton420011001495210001007612100100073470.8751424380188867961518338888711712150326918316.67%15380.00%01646308953.29%1637311552.55%729132155.19%1952131419226271069539
Total82323706700259262-3411915025001301151541132204200129147-18830.506259467726248886796260983388887117275581676113923436518.95%3275583.18%71646308953.29%1637311552.55%729132155.19%1952131419226271069539
_Since Last GM Reset82323706700259262-3411915025001301151541132204200129147-18830.506259467726248886796260983388887117275581676113923436518.95%3275583.18%71646308953.29%1637311552.55%729132155.19%1952131419226271069539
_Vs Conference58242505400183181229161001200967719298150420087104-17620.53418333251524888679618688338888711719335905269742545019.69%2263186.28%71646308953.29%1637311552.55%729132155.19%1952131419226271069539
_Vs Division3212180310097103-61688010004942716410021004861-13310.4849717327013888679610288338888711710573263085451422719.01%1301886.15%51646308953.29%1637311552.55%729132155.19%1952131419226271069539

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8283W125946772626092755816761139224
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8232376700259262
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4119152500130115
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4113224200129147
Derniers 10 matchs
WLOTWOTL SOWSOL
270100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3436518.95%3275583.18%7
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
833888871178886796
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
1646308953.29%1637311552.55%729132155.19%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1952131419226271069539


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 - 2022-11-256Grand Rapids3Toronto2BLSommaire du match
4 - 2022-11-2616Toronto4Grand Rapids3AWXSommaire du match
6 - 2022-11-2728Grand Rapids4Toronto6BWSommaire du match
8 - 2022-11-2837Toronto2Grand Rapids3ALSommaire du match
10 - 2022-11-2953Toronto0Providence3ALSommaire du match
13 - 2022-12-0166Rochester0Toronto4BWSommaire du match
16 - 2022-12-0282Grand Rapids3Toronto4BWXSommaire du match
19 - 2022-12-0498Toronto5Grand Rapids2AWSommaire du match
21 - 2022-12-05107Toronto2Rochester3ALXSommaire du match
22 - 2022-12-05115Cleveland3Toronto4BWSommaire du match
24 - 2022-12-06127Toronto7Laval4AWSommaire du match
26 - 2022-12-07140Laval2Toronto3BWSommaire du match
29 - 2022-12-09155Providence2Toronto1BLSommaire du match
32 - 2022-12-10167Toronto4Cleveland6ALSommaire du match
33 - 2022-12-11176Toronto2Hershey6ALSommaire du match
35 - 2022-12-12184Wilkes-Barre/Scranton3Toronto5BWSommaire du match
38 - 2022-12-13200San Diego5Toronto4BLXSommaire du match
40 - 2022-12-14215Toronto3San Jose5ALSommaire du match
42 - 2022-12-15222Toronto7Abbotsford2AWSommaire du match
44 - 2022-12-16231Lehigh Valley3Toronto5BWSommaire du match
47 - 2022-12-18250Rockford3Toronto1BLSommaire du match
49 - 2022-12-19260Toronto1Charlotte3ALSommaire du match
50 - 2022-12-19270Toronto3Utica4ALSommaire du match
53 - 2022-12-21280Wilkes-Barre/Scranton3Toronto2BLXSommaire du match
55 - 2022-12-22295Toronto2Rochester6ALSommaire du match
56 - 2022-12-22303Tucson2Toronto1BLXSommaire du match
58 - 2022-12-23318Toronto4Rochester6ALSommaire du match
61 - 2022-12-25327Grand Rapids2Toronto5BWSommaire du match
63 - 2022-12-26341Toronto4Hershey3AWXSommaire du match
64 - 2022-12-26348Toronto4San Diego1AWSommaire du match
66 - 2022-12-27355Abbotsford3Toronto4BWXSommaire du match
69 - 2022-12-29372Hartford2Toronto3BWSommaire du match
74 - 2022-12-31394Springfield3Toronto1BLSommaire du match
76 - 2023-01-01405Toronto1Cleveland3ALSommaire du match
79 - 2023-01-03418San Jose6Toronto0BLSommaire du match
81 - 2023-01-04431Toronto3Hartford2AWSommaire du match
82 - 2023-01-04440Toronto3Wilkes-Barre/Scranton0AWSommaire du match
84 - 2023-01-05446Hartford4Toronto5BWSommaire du match
87 - 2023-01-07462Toronto4Laval2AWSommaire du match
89 - 2023-01-08471Lehigh Valley3Toronto6BWSommaire du match
93 - 2023-01-10491Cleveland1Toronto3BWSommaire du match
95 - 2023-01-11501Toronto1Springfield6ALSommaire du match
97 - 2023-01-12515Bakersfield3Toronto2BLSommaire du match
99 - 2023-01-13525Toronto2Charlotte6ALSommaire du match
100 - 2023-01-13534Toronto3Laval2AWSommaire du match
102 - 2023-01-14542Charlotte0Toronto3BWSommaire du match
106 - 2023-01-16563Toronto4Utica2AWSommaire du match
107 - 2023-01-17567Charlotte5Toronto4BLXSommaire du match
110 - 2023-01-18577Toronto3Tucson1AWSommaire du match
112 - 2023-01-19589Hershey1Toronto5BWSommaire du match
114 - 2023-01-20599Toronto1Milwaukee3ALSommaire du match
117 - 2023-01-22612Ontario3Toronto5BWSommaire du match
122 - 2023-01-24632Grand Rapids4Toronto2BLSommaire du match
124 - 2023-01-25644Toronto8Manitoba6AWSommaire du match
126 - 2023-01-26656Rochester3Toronto5BWSommaire du match
128 - 2023-01-27668Toronto2Bakersfield5ALSommaire du match
130 - 2023-01-28679Toronto4Wilkes-Barre/Scranton3AWXSommaire du match
132 - 2023-01-29684Toronto2Lehigh Valley4ALSommaire du match
133 - 2023-01-30691Manitoba4Toronto3BLSommaire du match
137 - 2023-02-01711Utica3Toronto1BLSommaire du match
139 - 2023-02-02721Toronto4Hartford3AWSommaire du match
141 - 2023-02-03734Laval5Toronto3BLSommaire du match
145 - 2023-02-05750Toronto3Lehigh Valley4ALXSommaire du match
146 - 2023-02-05759Hershey1Toronto2BWSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
148 - 2023-02-06773Toronto3Providence6ALSommaire du match
150 - 2023-02-07782Milwaukee2Toronto6BWSommaire du match
155 - 2023-02-10802Toronto2Ontario4ALSommaire du match
156 - 2023-02-10809Utica4Toronto3BLSommaire du match
158 - 2023-02-11818Toronto7Iowa2AWSommaire du match
160 - 2023-02-12829Toronto2Texas4ALSommaire du match
162 - 2023-02-13836Laval0Toronto2BWSommaire du match
165 - 2023-02-15853Rochester2Toronto1BLSommaire du match
167 - 2023-02-16869Toronto5Providence4AWXSommaire du match
169 - 2023-02-17875Cleveland4Toronto3BLSommaire du match
172 - 2023-02-18886Toronto2Rockford4ALSommaire du match
174 - 2023-02-19897Toronto3Grand Rapids4ALSommaire du match
176 - 2023-02-20908Providence3Toronto1BLSommaire du match
177 - 2023-02-21911Toronto2Cleveland3ALSommaire du match
183 - 2023-02-24929Providence4Toronto3BLSommaire du match
188 - 2023-02-26953Toronto1Grand Rapids4ALSommaire du match
190 - 2023-02-27960Texas2Toronto1BLXSommaire du match
196 - 2023-03-02982Iowa2Toronto6BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance62,26331,038
Assistance PCT75.93%75.70%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2276 - 75.85% 133,166$5,459,793$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,399,610$ 1,739,950$ 1,739,950$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,788$ 1,849,582$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 11,565$ 0$




Toronto 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
1Mark Arcobello1645274126-141611018846811.11%20293917.9310263612002202253.3300.8622
2Jake Evans1163484118-18722463384747.17%24253021.8210283813006664253.1400.9306
3Michael Chaput1644868116-14408428043411.06%20274216.728182674000188254.7320.8524
4MacKenzie Entwistle1644468112-361163342125028.76%28282317.2216143014400008044.4400.7902
5Melker Karlsson1424258100-22241661905667.42%24294920.77122032146202124250.2400.68410

Toronto 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
1Samuel Montembeault92324880.8983.55534716231630920260.50024
2Pavel Francouz70303240.8973.54393816223222600040.66718

Toronto 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
2082254503234249317-6841132600011117161-4441121903223132156-24682494416905272100719276492394186358288183882114993526117.33%3306779.70%51641310752.82%1539322347.75%690137550.18%1889127320076421070523
2082254503234249317-6841132600011117161-4441121903223132156-24682494416905272100719276492394186358288183882114993526117.33%3306779.70%51641310752.82%1539322347.75%690137550.18%1889127320076421070523
Total Saison régulière16464740121400518524-68238300410002602303082264408400258294-3616651893414524817617215812521816661776174234551016321522278468613018.95%65411083.18%143292617853.29%3274623052.55%1458264255.19%390526283844125421391079
Séries éliminatoires
Total Séries éliminatoires00000000000000.00%0.00%0.00%0.00%0.00%000000

Toronto 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

Toronto 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