Connexion

Americans
GP: 11 | W: 4 | L: 6 | OTL: 1 | P: 9
GF: 33 | GA: 37 | PP%: 15.79% | PK%: 77.50%
DG: Yannick Caron | Morale : 50 | Moyenne d’équipe : 68
Prochain matchs #185 vs Crunch
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Centre de jeu
Americans
4-6-1, 9pts
1
FINAL
4 Binghamton Senateurs
4-6-0, 8pts
Team Stats
W1StreakL1
3-1-1Home Record3-2-0
1-5-0Away Record1-4-0
4-5-1Last 10 Games4-6-0
3.00Buts par match 2.70
3.36Buts contre par match 3.30
15.79%Pourcentage en avantage numérique16.28%
77.50%Pourcentage en désavantage numérique78.95%
Binghamton Senateurs
4-6-0, 8pts
2
FINAL
6 Americans
4-6-1, 9pts
Team Stats
L1StreakW1
3-2-0Home Record3-1-1
1-4-0Away Record1-5-0
4-6-0Last 10 Games4-5-1
2.70Buts par match 3.00
3.30Buts contre par match 3.36
16.28%Pourcentage en avantage numérique15.79%
78.95%Pourcentage en désavantage numérique77.50%
Crunch
5-3-1, 11pts
2022-08-04
Americans
4-6-1, 9pts
Statistiques d’équipe
W1SéquenceW1
4-1-0Fiche domicile3-1-1
1-2-1Fiche visiteur1-5-0
5-3-110 derniers matchs4-5-1
3.67Buts par match 3.00
3.11Buts contre par match 3.36
39.47%Pourcentage en avantage numérique15.79%
87.10%Pourcentage en désavantage numérique77.50%
Griffins
5-2-1, 11pts
2022-08-06
Americans
4-6-1, 9pts
Statistiques d’équipe
W1SéquenceW1
4-0-1Fiche domicile3-1-1
1-2-0Fiche visiteur1-5-0
5-2-110 derniers matchs4-5-1
3.75Buts par match 3.00
2.38Buts contre par match 3.36
32.26%Pourcentage en avantage numérique15.79%
89.29%Pourcentage en désavantage numérique77.50%
Americans
4-6-1, 9pts
2022-08-07
Rockets
6-2-2, 14pts
Statistiques d’équipe
W1SéquenceW1
3-1-1Fiche domicile4-0-0
1-5-0Fiche visiteur2-2-2
4-5-110 derniers matchs6-2-2
3.00Buts par match 2.90
3.36Buts contre par match 3.00
15.79%Pourcentage en avantage numérique8.70%
77.50%Pourcentage en désavantage numérique76.92%
Meneurs d'équipe
Victoires
Louis Domingue
4
Pourcentage d’arrêts
Louis Domingue
0.919

Statistiques d’équipe
Buts pour
33
3.00 GFG
Tirs pour
399
36.27 Avg
Pourcentage en avantage numérique
15.8%
6 GF
Début de zone offensive
39.9%
Buts contre
37
3.36 GAA
Tirs contre
424
38.55 Avg
Pourcentage en désavantage numérique
77.5%
9 GA
Début de la zone défensive
43.7%
Information d’équipe

Directeur généralYannick Caron
EntraîneurChantal Machabée
DivisionATLANTIQUE
ConférenceEST
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Information formation

Équipe Pro27
Équipe Mineure21
Limite contact 48 / 55
Espoirs25


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur #C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Marcus Sorensen0XX100.006639866967778468566764706877690507103031,000,000$
2Michael Amadio0X100.00593993668180826477636762656769050700262795,000$
3Benoit-Olivier Groulx0X100.00693981658079836480636168626469050700222910,833$
4Hayden Hodgson0X100.00743461648281776558666759646668050700262800,000$
5Byron Froese0X100.00703987607887776378616268647176050700312817,000$
6Sam Steel0X100.005934936870828667836664596864650506902441,093,750$
7Anders Bjork0X100.00583593667481866355616467626766050690263700,000$
8Kasper Bjorkqvist0X100.00683881657773826255616257636567050680253900,000$
9Matthew Peca0X100.00663594646779846371675960626971050680291700,000$
10Sean Malone0X100.00633470667478716575646359656769050680272912,000$
11Mackenzie MacEachern0X100.00734184577977865863596057616870050670282750,000$
12Mitchell Stephens0X100.006234886371777260836456685764650506702521,061,000$
13Cody Franson0X100.00837086559478875630645763457577050700351750,000$
14Will Butcher0X100.005534846871887766307559615368670506902721,952,000$
15Dillon Heatherington0X100.00814182598977785630585764496769050680272775,000$
16Casey Fitzgerald0X100.007235686170848561306457625165670506802533,125,000$
17Vincent Desharnais0X100.00867773569572935430595362466668050680262800,000$
18Tommy Cross0X100.00744372588478865730605661487378050680331750,000$
Rayé
1Semyon Der-Arguchintsev0X100.00563689646877796470625957646265050660222766,677$
2Matej Pekar0X100.00655362517473765256535455516264050610222913,333$
3Luke Witkowski0X100.006334875882717857305655594872740506503221,029,000$
4Ashton Sautner0X100.00673975597667695830575456456870050640281700,000$
5Jeremy Groleau0X100.00733975538264725130535256456365050620222898,000$
MOYENNE D’ÉQUIPE100.0068418162787780615362596157676905068
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
1Louis Domingue100.00737577857271737271737272840507603011,650,000$
2Michael Houser100.0075717276747375747375747084050760302800,000$
Rayé
1Callum Booth100.0069646583686769686769686573050710252928,000$
2Jeremy Brodeur100.0066646571656466656466656775050680251875,000$
MOYENNE D’ÉQUIPE100.007169707970697170697170697905073
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Chantal Machabée75757575757575CAN5850$


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
1Marcus SorensenAmericans (BUF)LW/RW1186143208195363315.09%222420.4531420341011330035.80%8100011.2400000100
2Will ButcherAmericans (BUF)D11281002068238128.70%2326724.312131734000035000.00%000000.7500000001
3Benoit-Olivier GroulxAmericans (BUF)C1136922018303111339.68%522320.340337340000320053.78%33100000.8000000100
4Hayden HodgsonAmericans (BUF)RW11448310024734152611.76%119117.401011034000000036.84%1900000.8400000000
5Cody FransonAmericans (BUF)D11246-1603111133815.38%1926223.85022534000031100.00%000000.4600000010
6Vincent DesharnaisAmericans (BUF)D1115606020883912.50%2020318.47000534011030000.00%000000.5900000000
7Sam SteelAmericans (BUF)C11235-24015303810305.26%219317.600111335000002048.36%27500000.5200000001
8Casey FitzgeraldAmericans (BUF)D110550801998240.00%1619217.540000100008000.00%000000.5200000000
9Anders BjorkAmericans (BUF)LW11145-2004144218372.38%819317.570111135000000060.00%1000000.5200000010
10Kasper BjorkqvistAmericans (BUF)RW11224-2120219314226.45%219317.55000835000000020.00%1500000.4100000011
11Mitchell StephensAmericans (BUF)C113141004141841516.67%512911.7900000000040053.33%1500000.6200000010
12Dillon HeatheringtonAmericans (BUF)D11123010022642525.00%1118616.980000100001100.00%000000.3200000000
13Mackenzie MacEachernAmericans (BUF)LW1112318021419885.26%212511.4100000000000044.44%900000.4800000001
14Byron FroeseAmericans (BUF)C11123-20071117665.88%111410.44000000110350061.11%1800000.5200000000
15Michael AmadioAmericans (BUF)C11022100718324250.00%416014.55000000000330046.43%16800000.2500000000
16Tommy CrossAmericans (BUF)D111120401361051410.00%1820618.75000634000133000.00%000000.1900000001
17Sean MaloneAmericans (BUF)C11101-320111592911.11%0797.2200000000000055.34%10300000.2500000000
18Matthew PecaAmericans (BUF)C11000-300179350.00%0807.3300000000000040.00%500000.0000000000
Statistiques d’équipe totales ou en moyenne198335790-47602522263991143018.27%139322916.31691510235212322784049.19%104900010.5600000245
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
1Louis DomingueAmericans (BUF)114510.9193.1562841334090000.0000101210
2Michael HouserAmericans (BUF)10100.7337.7431004150000.0000110000
Statistiques d’équipe totales ou en moyenne124610.9133.3666041374240000.00001111210


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 restantSalaire moyenPlafond 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
Anders BjorkAmericans (BUF)LW261996-08-05No197 Lbs6 ft0NoNoNo3Pro & Farm700,000$700,000$0$0$No700,000$700,000$Lien
Ashton SautnerAmericans (BUF)D281994-05-27No195 Lbs6 ft1NoNoNo1Pro & Farm700,000$700,000$700,000$0$0$NoLien
Benoit-Olivier GroulxAmericans (BUF)C222000-02-06No200 Lbs6 ft2NoNoNo2Pro & Farm910,833$910,833$910,833$0$0$No910,833$Lien
Byron FroeseAmericans (BUF)C311991-03-12No202 Lbs6 ft1NoNoNo2Pro & Farm817,000$817,000$0$0$No817,000$Lien
Callum BoothAmericans (BUF)G251997-05-21No184 Lbs6 ft4NoNoNo2Pro & Farm928,000$928,000$750,000$0$0$No928,000$Lien
Casey FitzgeraldAmericans (BUF)D251997-02-25No188 Lbs5 ft11NoNoNo3Pro & Farm3,125,000$3,125,000$650,000$0$0$No3,125,000$3,125,000$Lien
Cody FransonAmericans (BUF)D351987-08-08No224 Lbs6 ft5NoNoNo1Pro & Farm750,000$750,000$750,000$0$0$NoLien
Dillon HeatheringtonAmericans (BUF)D271995-05-09No215 Lbs6 ft4NoNoNo2Pro & Farm775,000$775,000$775,000$0$0$No775,000$Lien
Hayden HodgsonAmericans (BUF)RW261996-03-02No208 Lbs6 ft2NoNoNo2Pro & Farm800,000$800,000$750,000$0$0$No800,000$Lien
Jeremy BrodeurAmericans (BUF)G251996-10-29No185 Lbs6 ft0NoNoNo1Pro & Farm875,000$875,000$875,000$0$0$NoLien
Jeremy GroleauAmericans (BUF)D221999-10-25No193 Lbs6 ft3NoNoNo2Pro & Farm898,000$898,000$743,335$0$0$No898,000$Lien
Kasper BjorkqvistAmericans (BUF)RW251997-07-10No198 Lbs6 ft1NoNoNo3Pro & Farm900,000$900,000$900,000$0$0$No900,000$900,000$Lien
Louis DomingueAmericans (BUF)G301992-03-06No208 Lbs6 ft3NoNoNo1Pro & Farm1,650,000$1,650,000$650,000$0$0$NoLien
Luke WitkowskiAmericans (BUF)D321990-04-14No210 Lbs6 ft2NoNoNo2Pro & Farm1,029,000$1,029,000$650,000$0$0$No1,029,000$Lien
Mackenzie MacEachernAmericans (BUF)LW281994-03-09No193 Lbs6 ft2NoNoNo2Pro & Farm750,000$750,000$750,000$0$0$No750,000$Lien
Marcus SorensenAmericans (BUF)LW/RW301992-04-07No175 Lbs5 ft11NoNoNo3Pro & Farm1,000,000$1,000,000$1,000,000$0$0$No1,000,000$1,000,000$Lien
Matej PekarAmericans (BUF)LW222000-02-10No185 Lbs6 ft1NoNoNo2Pro & Farm913,333$913,333$913,333$0$0$No913,333$Lien
Matthew PecaAmericans (BUF)C291993-04-27No181 Lbs5 ft10NoNoNo1Pro & Farm700,000$700,000$700,000$0$0$NoLien
Michael AmadioAmericans (BUF)C261996-05-13No205 Lbs6 ft2NoNoNo2Pro & Farm795,000$795,000$650,000$0$0$No700,000$Lien
Michael HouserAmericans (BUF)G301992-09-13No185 Lbs6 ft1NoNoNo2Pro & Farm800,000$800,000$800,000$0$0$No800,000$Lien
Mitchell StephensAmericans (BUF)C251997-02-05No190 Lbs5 ft11NoNoNo2Pro & Farm1,061,000$1,061,000$650,000$0$0$No1,061,000$Lien
Sam SteelAmericans (BUF)C241998-02-03No184 Lbs5 ft11NoNoNo4Pro & Farm1,093,750$1,093,750$650,000$0$0$No1,093,750$1,093,750$1,093,750$Lien
Sean MaloneAmericans (BUF)C271995-04-30No197 Lbs6 ft0NoNoNo2Pro & Farm912,000$912,000$650,000$0$0$No750,000$Lien
Semyon Der-ArguchintsevAmericans (BUF)C222000-09-15No160 Lbs5 ft11NoNoNo2Pro & Farm766,677$766,677$700,000$0$0$No766,677$Lien
Tommy CrossAmericans (BUF)D331989-09-12No205 Lbs6 ft3NoNoNo1Pro & Farm750,000$750,000$750,000$0$0$NoLien
Vincent DesharnaisAmericans (BUF)D261996-05-29No215 Lbs6 ft6NoNoNo2Pro & Farm800,000$800,000$800,000$0$0$No800,000$Lien
Will ButcherAmericans (BUF)D271995-01-06No190 Lbs5 ft10NoNoNo2Pro & Farm1,952,000$1,952,000$525,000$0$0$No1,952,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2726.96195 Lbs6 ft12.001,005,615$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Marcus SorensenBenoit-Olivier GroulxHayden Hodgson30023
2Anders BjorkSam SteelKasper Bjorkqvist30023
3Mackenzie MacEachernMichael AmadioMitchell Stephens24122
4Matthew PecaSean MaloneByron Froese16122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Cody FransonWill Butcher32122
2Casey FitzgeraldDillon Heatherington30122
3Tommy CrossVincent Desharnais22122
4Cody FransonWill Butcher16122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Marcus SorensenBenoit-Olivier GroulxHayden Hodgson50122
2Anders BjorkSam SteelKasper Bjorkqvist50122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Cody FransonWill Butcher50122
2Tommy CrossVincent Desharnais50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Marcus SorensenByron Froese50122
2Benoit-Olivier GroulxMichael Amadio50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Cody FransonWill Butcher50122
2Tommy CrossVincent Desharnais50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Marcus Sorensen50122Cody FransonWill Butcher50122
2Byron Froese50122Tommy CrossVincent Desharnais50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Marcus SorensenByron Froese50122
2Benoit-Olivier GroulxMichael Amadio50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Cody FransonWill Butcher50122
2Tommy CrossVincent Desharnais50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Marcus SorensenByron FroeseHayden HodgsonCody FransonWill Butcher
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Marcus SorensenByron FroeseHayden HodgsonCody FransonWill Butcher
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Matthew Peca, Sean Malone, Mitchell StephensMatthew Peca, Sean MaloneMitchell Stephens
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dillon Heatherington, Casey Fitzgerald, Tommy CrossDillon HeatheringtonCasey Fitzgerald, Tommy Cross
Tirs de pénalité
Marcus Sorensen, Byron Froese, Benoit-Olivier Groulx, Michael Amadio, Hayden Hodgson
Gardien
#1 : Louis Domingue, #2 : Michael Houser
Lignes d’attaque personnalisées en prolongation
Marcus Sorensen, Byron Froese, Benoit-Olivier Groulx, Michael Amadio, Hayden Hodgson, Anders Bjork, Anders Bjork, Sam Steel, Matthew Peca, Kasper Bjorkqvist, Sean Malone
Lignes de défense personnalisées en prolongation
Cody Franson, Will Butcher, Tommy Cross, Vincent Desharnais, Dillon Heatherington


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
1Binghamton Senateurs21100000761110000006241010000014-320.50071118001210110781461231300843014557228.57%7185.71%020641849.28%22645849.34%8417248.84%2581782628113970
2Checkers211000006601010000036-31100000030320.5006111701121011065146123130084301246400.00%6183.33%120641849.28%22645849.34%8417248.84%2581782628113970
3Crunch1010000025-3000000000001010000025-300.000246001210110351461231300482214214125.00%7357.14%020641849.28%22645849.34%8417248.84%2581782628113970
4Griffins1010000014-3000000000001010000014-300.0001230012101103514612313002619618400.00%3233.33%020641849.28%22645849.34%8417248.84%2581782628113970
5Marlies2010010059-41000010023-11010000036-310.2505914001210110721461231300691416428225.00%8275.00%020641849.28%22645849.34%8417248.84%2581782628113970
6Providence Bruins21100000660110000003211010000034-120.50061117001210110741461231300771910478112.50%50100.00%020641849.28%22645849.34%8417248.84%2581782628113970
7Rockets11000000615110000006150000000000021.0006915001210110401461231300365823300.00%40100.00%020641849.28%22645849.34%8417248.84%2581782628113970
Total1146001003337-45310010020146615000001323-1090.40933579001121011039914612313004241398025238615.79%40977.50%120641849.28%22645849.34%8417248.84%2581782628113970
_Since Last GM Reset1146001003337-45310010020146615000001323-1090.40933579001121011039914612313004241398025238615.79%40977.50%120641849.28%22645849.34%8417248.84%2581782628113970
_Vs Conference1146001003337-45310010020146615000001323-1090.40933579001121011039914612313004241398025238615.79%40977.50%120641849.28%22645849.34%8417248.84%2581782628113970
_Vs Division1146001003337-45310010020146615000001323-1090.40933579001121011039914612313004241398025238615.79%40977.50%120641849.28%22645849.34%8417248.84%2581782628113970

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
119W13357903994241398025201
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
114601003337
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
53101002014
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
61500001323
Derniers 10 matchs
WLOTWOTL SOWSOL
450100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
38615.79%40977.50%1
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
14612313001210110
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
20641849.28%22645849.34%8417248.84%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2581782628113970


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 - 2022-07-175Americans3Providence Bruins4ALSommaire du match
2 - 2022-07-1822Rockets1Americans6BWSommaire du match
4 - 2022-07-2037Checkers6Americans3BLSommaire du match
6 - 2022-07-2252Americans3Checkers0AWSommaire du match
7 - 2022-07-2365Americans1Griffins4ALSommaire du match
9 - 2022-07-2584Americans2Crunch5ALSommaire du match
10 - 2022-07-2694Providence Bruins2Americans3BWSommaire du match
11 - 2022-07-27107Americans3Marlies6ALSommaire du match
13 - 2022-07-29128Marlies3Americans2BLXSommaire du match
14 - 2022-07-30140Americans1Binghamton Senateurs4ALSommaire du match
16 - 2022-08-01156Binghamton Senateurs2Americans6BWSommaire du match
19 - 2022-08-04185Crunch-Americans-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
21 - 2022-08-06206Griffins-Americans-
22 - 2022-08-07223Americans-Rockets-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets2414
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,715,159$ 1,864,249$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 8 0$ 0$




Americans 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

Americans 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

Americans Statistiques de l'Équipe de Carrière


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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

Americans 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

Americans 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