Connexion

Checkers
GP: 10 | W: 4 | L: 5 | OTL: 1 | P: 9
GF: 28 | GA: 31 | PP%: 12.20% | PK%: 68.57%
DG: Mario Lemire | Morale : 50 | Moyenne d’équipe : 67
Prochain matchs #159 vs Rockets
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Centre de jeu
Marlies
8-2-0, 16pts
1
FINAL
3 Checkers
4-5-1, 9pts
Team Stats
W1StreakL1
5-0-0Home Record1-3-1
3-2-0Away Record3-2-0
8-2-0Last 10 Games4-5-1
3.40Buts par match 2.80
2.90Buts contre par match 3.10
29.03%Pourcentage en avantage numérique12.20%
74.51%Pourcentage en désavantage numérique68.57%
Checkers
4-5-1, 9pts
3
FINAL
5 Marlies
8-2-0, 16pts
Team Stats
L1StreakW1
1-3-1Home Record5-0-0
3-2-0Away Record3-2-0
4-5-1Last 10 Games8-2-0
2.80Buts par match 3.40
3.10Buts contre par match 2.90
12.20%Pourcentage en avantage numérique29.03%
68.57%Pourcentage en désavantage numérique74.51%
Checkers
4-5-1, 9pts
2022-08-02
Rockets
6-2-2, 14pts
Statistiques d’équipe
L1SéquenceW1
1-3-1Fiche domicile4-0-0
3-2-0Fiche visiteur2-2-2
4-5-110 derniers matchs6-2-2
2.80Buts par match 2.90
3.10Buts contre par match 3.00
12.20%Pourcentage en avantage numérique8.70%
68.57%Pourcentage en désavantage numérique76.92%
Griffins
5-2-1, 11pts
2022-08-04
Checkers
4-5-1, 9pts
Statistiques d’équipe
W1SéquenceL1
4-0-1Fiche domicile1-3-1
1-2-0Fiche visiteur3-2-0
5-2-110 derniers matchs4-5-1
3.75Buts par match 2.80
2.38Buts contre par match 3.10
32.26%Pourcentage en avantage numérique12.20%
89.29%Pourcentage en désavantage numérique68.57%
Checkers
4-5-1, 9pts
2022-08-05
Griffins
5-2-1, 11pts
Statistiques d’équipe
L1SéquenceW1
1-3-1Fiche domicile4-0-1
3-2-0Fiche visiteur1-2-0
4-5-110 derniers matchs5-2-1
2.80Buts par match 3.75
3.10Buts contre par match 2.38
12.20%Pourcentage en avantage numérique32.26%
68.57%Pourcentage en désavantage numérique89.29%
Meneurs d'équipe
Victoires
Mikhail Berdin
3
Pourcentage d’arrêts
Mikhail Berdin
0.926

Statistiques d’équipe
Buts pour
28
2.80 GFG
Tirs pour
378
37.80 Avg
Pourcentage en avantage numérique
12.2%
5 GF
Début de zone offensive
42.2%
Buts contre
31
3.10 GAA
Tirs contre
358
35.80 Avg
Pourcentage en désavantage numérique
68.6%
11 GA
Début de la zone défensive
40.8%
Information d’équipe

Directeur généralMario Lemire
EntraîneurSteve Hartley
DivisionATLANTIQUE
ConférenceEST
CapitaineScott Reedy
Assistant #1Connor Bunnaman
Assistant #2Thomas Hickey


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Information formation

Équipe Pro28
Équipe Mineure20
Limite contact 48 / 55
Espoirs17


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
1Scott Reedy (C)0X100.00683890678178846370626764656364050700234925,000$
2Greg McKegg0XXX100.00673693627377746173606272597172050690303975,000$
3Justin Kirkland0XX100.00674371648083876157626361626668050690262974,000$
4Dmitrij Jaskin0XX100.00863689638485686459625561667169050690293750,000$
5Jonah Gadjovich0X100.00877955618274736057636158626364050680231863,333$
6Mason Shaw0XX100.00703966636887855974625857636566050670234925,000$
7Connor Bunnaman (A)0XX100.00723893567976875778585963566466050670242750,000$
8Joona Koppanen0X100.00793681568869755963585761566466050670242750,000$
9Martin Pospisil0XXX100.00664558617682735960635861596365050670224810,000$
10Jacob Perreault (R)0X100.00563978667183796558625759646163050660202894,167$
11Cole Bardreau0XX100.00573693596881745866576258616972050650292700,000$
12Michael Eyssimont0XX100.00604175567087835762585960646668050650262750,000$
13Thomas Hickey (A)0X100.00733792637183726130665768507576050690332750,000$
14Jeremy Davies0X100.006139836168827762306758615066680506702521,778,000$
15Matt Donovan0X100.00693476597873855830635557487274050660322700,000$
16Oskari Laaksonen0X100.00633884607264915330645659456365050650232925,000$
17Bode Wilde0X100.00633986577977736130565359456164050640221910,883$
18Max Gildon0X100.00734087568269685530595356466365050640232925,000$
Rayé
1Anton Blidh0X100.008835766577757364576362706466670507102731,050,000$
2Zack Kassian0X100.009087716486798362596663566177720507103122,840,000$
3Daniel Carr0XX100.00673789667275776361656462667868050690304900,000$
4Sven Baertschi0X100.006036835870867259635859566071720506502942,017,000$
5Cedric Pare (R)0X100.00653993558469715661575854566365050640231750,000$
6Pavel Shen0XX100.00653986567465705861575559566362050630231925,000$
7Blade Jenkins0XX100.00673795557667735452535658576264050620222803,333$
8Michael Anderson (R)0X100.007671897771636749254141613944440506102311,775,000$
MOYENNE D’ÉQUIPE100.0070438261767777595460586057666705067
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
1Joseph Woll100.0074737287737274737274736471050750245800,000$
2Mikhail Berdin100.00737677737271737271737264710507402442,333,000$
Rayé
MOYENNE D’ÉQUIPE100.007475758073727473727473647105075
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Steve Hartley75757575757575USA3750$


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
1Greg McKeggCheckers (FLO)C/LW/RW10167-50011224811242.08%720620.6602214340000260034.78%2300000.6800000100
2Thomas HickeyCheckers (FLO)D10167-6602216236174.35%1223023.061231435000028100.00%000000.6100000000
3Jacob PerreaultCheckers (FLO)RW10347640272991910.34%212712.7100000000000055.56%900001.1000000002
4Mason ShawCheckers (FLO)C/LW102466402021247108.33%212812.8900000000010057.93%16400000.9300000100
5Jonah GadjovichCheckers (FLO)LW10156-3204318297173.45%418118.12011538000000035.00%2000000.6600000100
6Justin KirklandCheckers (FLO)C/LW10156-3007163511272.86%320720.800227380000260035.91%29800000.5800000010
7Dmitrij JaskinCheckers (FLO)LW/RW10426-56036112642215.38%420420.4710110340000241053.33%1500000.5900000001
8Oskari LaaksonenCheckers (FLO)D10325360910102830.00%1521621.61101537000023000.00%000000.4600000000
9Cole BardreauCheckers (FLO)C/RW1022450002122416.67%0545.4600000000000028.57%700001.4600000000
10Michael EyssimontCheckers (FLO)C/LW1022454033102520.00%2545.4400000000000050.00%200001.4700000001
11Martin PospisilCheckers (FLO)C/LW/RW10224-340993112216.45%118118.12101938000000038.46%1300000.4400000001
12Scott ReedyCheckers (FLO)C10314-50016233210249.38%420820.8310112340001282045.13%30800000.3800000010
13Connor BunnamanCheckers (FLO)C/LW1012362066245164.17%412712.7100000000000062.50%800000.4700000000
14Joona KoppanenCheckers (FLO)C1012352013452920.00%1595.9600000000150042.50%8000001.0100000010
15Bode WildeCheckers (FLO)D1012362011951320.00%814814.840000000000000.00%000000.4000000000
16Jeremy DaviesCheckers (FLO)D10022-6808514580.00%1222822.87011635000026000.00%000000.1700000000
17Matt DonovanCheckers (FLO)D1001138028815590.00%1221521.59000937000023000.00%000000.0900000000
18Max GildonCheckers (FLO)D1001161002256210.00%616016.1000000000013000.00%000000.1200000000
Statistiques d’équipe totales ou en moyenne180285179156802661953781032447.41%99294216.3558139136600022304043.93%94700000.5400000335
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
1Mikhail BerdinCheckers (FLO)83410.9262.7244220202710110.000073210
2Joseph WollCheckers (FLO)31100.8843.851560010860000.000037000
Statistiques d’équipe totales ou en moyenne114510.9163.0159920303570110.00001010210


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
Anton BlidhCheckers (FLO)LW271995-03-14No197 Lbs6 ft1NoNoNo3Pro & Farm1,050,000$1,050,000$525,000$0$0$No1,050,000$1,050,000$Lien
Blade JenkinsCheckers (FLO)C/LW222000-08-11No195 Lbs6 ft1NoNoNo2Pro & Farm803,333$803,333$803,333$0$0$No803,333$Lien
Bode WildeCheckers (FLO)D222000-01-24No192 Lbs6 ft2NoNoNo1Pro & Farm910,883$910,883$778,333$0$0$NoLien
Cedric PareCheckers (FLO)C231999-01-24Yes205 Lbs6 ft3NoNoNo1Pro & Farm750,000$750,000$700,000$0$0$No
Cole BardreauCheckers (FLO)C/RW291993-07-22No185 Lbs5 ft10NoNoNo2Pro & Farm700,000$700,000$600,000$0$0$No700,000$Lien
Connor BunnamanCheckers (FLO)C/LW241998-04-16No207 Lbs6 ft1NoNoNo2Pro & Farm750,000$750,000$700,000$0$0$No750,000$Lien
Daniel CarrCheckers (FLO)LW/RW301991-11-01No186 Lbs6 ft0NoNoNo4Pro & Farm900,000$900,000$900,000$0$0$No900,000$900,000$900,000$Lien
Dmitrij JaskinCheckers (FLO)LW/RW291993-03-23No216 Lbs6 ft2NoNoNo3Pro & Farm750,000$750,000$750,000$0$0$No750,000$750,000$Lien
Greg McKeggCheckers (FLO)C/LW/RW301992-06-17No195 Lbs6 ft0NoNoNo3Pro & Farm975,000$975,000$975,000$0$0$No975,000$975,000$Lien
Jacob PerreaultCheckers (FLO)RW202002-04-15Yes192 Lbs5 ft11NoNoNo2Pro & Farm894,167$894,167$600,000$0$0$No894,167$Lien
Jeremy DaviesCheckers (FLO)D251996-12-04No180 Lbs5 ft11NoNoNo2Pro & Farm1,778,000$1,778,000$750,000$0$0$No1,778,000$Lien
Jonah GadjovichCheckers (FLO)LW231998-10-12No209 Lbs6 ft2NoNoNo1Pro & Farm863,333$863,333$783,333$0$0$NoLien
Joona KoppanenCheckers (FLO)C241998-02-25No192 Lbs6 ft5NoNoNo2Pro & Farm750,000$750,000$700,000$0$0$No750,000$Lien
Joseph WollCheckers (FLO)G241998-07-12No203 Lbs6 ft4NoNoNo5Pro & Farm800,000$800,000$800,000$0$0$No925,000$925,000$925,000$925,000$Lien
Justin KirklandCheckers (FLO)C/LW261996-08-02No183 Lbs6 ft3NoNoNo2Pro & Farm974,000$974,000$650,000$0$0$No974,000$Lien
Martin PospisilCheckers (FLO)C/LW/RW221999-11-19No173 Lbs6 ft2NoNoNo4Pro & Farm810,000$810,000$796,668$0$0$No1,119,000$1,119,000$1,119,000$Lien
Mason ShawCheckers (FLO)C/LW231998-11-03No184 Lbs5 ft10NoNoNo4Pro & Farm925,000$925,000$792,500$0$0$No1,229,000$1,229,000$1,229,000$Lien
Matt DonovanCheckers (FLO)D321990-05-09No205 Lbs6 ft1NoNoNo2Pro & Farm700,000$700,000$600,000$0$0$No700,000$Lien
Max GildonCheckers (FLO)D231999-05-17No194 Lbs6 ft3NoNoNo2Pro & Farm925,000$925,000$925,000$0$0$No925,000$Lien
Michael AndersonCheckers (FLO)D231999-05-25Yes196 Lbs6 ft0NoNoNo1Pro & Farm1,775,000$1,775,000$925,001$0$0$NoLien
Michael EyssimontCheckers (FLO)C/LW261996-09-09No180 Lbs6 ft0NoNoNo2Pro & Farm750,000$750,000$700,000$0$0$No750,000$Lien
Mikhail BerdinCheckers (FLO)G241998-03-01No163 Lbs6 ft2NoNoNo4Pro & Farm2,333,000$2,333,000$650,000$0$0$No2,333,000$2,333,000$2,333,000$Lien
Oskari LaaksonenCheckers (FLO)D231999-07-02No172 Lbs6 ft1NoNoNo2Pro & Farm925,000$925,000$925,000$0$0$No925,000$Lien
Pavel ShenCheckers (FLO)C/RW231999-08-14No183 Lbs6 ft1NoNoNo1Pro & Farm925,000$925,000$809,169$0$0$NoLien
Scott ReedyCheckers (FLO)C231999-04-04No205 Lbs6 ft2NoNoNo4Pro & Farm925,000$925,000$925,000$0$0$No856,000$856,000$856,000$Lien
Sven BaertschiCheckers (FLO)LW291992-10-05No190 Lbs5 ft11NoNoNo4Pro & Farm2,017,000$2,017,000$525,000$0$0$No2,017,000$2,017,000$2,017,000$Lien
Thomas HickeyCheckers (FLO)D331989-02-08No185 Lbs6 ft0NoNoNo2Pro & Farm750,000$750,000$750,000$0$0$No750,000$Lien
Zack KassianCheckers (FLO)RW311991-01-24No211 Lbs6 ft3NoNoNo2Pro & Farm2,840,000$2,840,000$650,000$0$0$No2,840,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2825.46192 Lbs6 ft12.461,080,311$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dmitrij JaskinScott ReedyGreg McKegg32014
2Jonah GadjovichJustin KirklandMartin Pospisil30023
3Connor BunnamanMason ShawJacob Perreault28122
4Michael EyssimontJoona KoppanenCole Bardreau10041
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Thomas HickeyJeremy Davies34014
2Matt DonovanOskari Laaksonen34014
3Bode WildeMax Gildon28023
4Thomas HickeyJeremy Davies4131
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dmitrij JaskinScott ReedyGreg McKegg50014
2Jonah GadjovichJustin KirklandMartin Pospisil50014
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Thomas HickeyJeremy Davies50014
2Matt DonovanOskari Laaksonen50014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Scott ReedyDmitrij Jaskin50041
2Justin KirklandGreg McKegg50041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Thomas HickeyJeremy Davies50122
2Matt DonovanOskari Laaksonen50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Scott Reedy50041Thomas HickeyJeremy Davies50122
2Dmitrij Jaskin50041Matt DonovanOskari Laaksonen50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Scott ReedyDmitrij Jaskin50014
2Justin KirklandGreg McKegg50014
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Thomas HickeyJeremy Davies50122
2Matt DonovanOskari Laaksonen50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dmitrij JaskinScott ReedyGreg McKeggThomas HickeyJeremy Davies
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dmitrij JaskinScott ReedyGreg McKeggThomas HickeyJeremy Davies
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Mason Shaw, Connor Bunnaman, Joona KoppanenMason Shaw, Connor BunnamanJoona Koppanen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Bode Wilde, Max Gildon, Matt DonovanBode WildeMax Gildon, Matt Donovan
Tirs de pénalité
Scott Reedy, Dmitrij Jaskin, Justin Kirkland, Greg McKegg, Jonah Gadjovich
Gardien
#1 : Mikhail Berdin, #2 : Joseph Woll
Lignes d’attaque personnalisées en prolongation
Scott Reedy, Dmitrij Jaskin, Justin Kirkland, Greg McKegg, Jonah Gadjovich, Mason Shaw, Mason Shaw, Connor Bunnaman, Joona Koppanen, Martin Pospisil, Jacob Perreault
Lignes de défense personnalisées en prolongation
Thomas Hickey, Jeremy Davies, Matt Donovan, Oskari Laaksonen, Bode Wilde


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
1Americans211000006601010000003-31100000063320.500612180081010084123122133065218386116.67%40100.00%017040042.50%16938643.78%7716147.83%2311582407412864
2Binghamton Senateurs11000000422000000000001100000042221.0004812008101004412312213302610018700.00%000.00%017040042.50%16938643.78%7716147.83%2311582407412864
3Crunch20100100811-31000010045-11010000046-210.250814221081010074123122133061182066700.00%10730.00%017040042.50%16938643.78%7716147.83%2311582407412864
4Marlies21100000660110000003121010000035-220.50061016008101007712312213308316106413323.08%5260.00%017040042.50%16938643.78%7716147.83%2311582407412864
5Providence Bruins2110000045-11010000013-21100000032120.500471100810100721231221330842622486116.67%11281.82%017040042.50%16938643.78%7716147.83%2311582407412864
6Rockets1010000001-11010000001-10000000000000.000000008101002712312213303981032200.00%50100.00%017040042.50%16938643.78%7716147.83%2311582407412864
Total1045001002831-351300100813-5532000002018290.450285179108101003781231221330358997026641512.20%351168.57%017040042.50%16938643.78%7716147.83%2311582407412864
_Since Last GM Reset1045001002831-351300100813-5532000002018290.450285179108101003781231221330358997026641512.20%351168.57%017040042.50%16938643.78%7716147.83%2311582407412864
_Vs Conference1045001002831-351300100813-5532000002018290.450285179108101003781231221330358997026641512.20%351168.57%017040042.50%16938643.78%7716147.83%2311582407412864
_Vs Division1045001002831-351300100813-5532000002018290.450285179108101003781231221330358997026641512.20%351168.57%017040042.50%16938643.78%7716147.83%2311582407412864

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
109L1285179378358997026610
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
104501002831
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
5130100813
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
53200002018
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
41512.20%351168.57%0
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
1231221330810100
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
17040042.50%16938643.78%7716147.83%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2311582407412864


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 - 2022-07-179Checkers4Crunch6ALSommaire du match
2 - 2022-07-1820Crunch5Checkers4BLXSommaire du match
4 - 2022-07-2037Checkers6Americans3AWSommaire du match
6 - 2022-07-2252Americans3Checkers0BLSommaire du match
7 - 2022-07-2360Checkers4Binghamton Senateurs2AWSommaire du match
9 - 2022-07-2587Providence Bruins3Checkers1BLSommaire du match
11 - 2022-07-27104Rockets1Checkers0BLSommaire du match
12 - 2022-07-28117Checkers3Providence Bruins2AWSommaire du match
15 - 2022-07-31143Marlies1Checkers3BWSommaire du match
16 - 2022-08-01153Checkers3Marlies5ALSommaire du match
17 - 2022-08-02159Checkers-Rockets-
19 - 2022-08-04183Griffins-Checkers-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
20 - 2022-08-05195Checkers-Griffins-
22 - 2022-08-07215Binghamton Senateurs-Checkers-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
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$ 3,024,871$ 2,098,833$ 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$




Checkers 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

Checkers 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

Checkers 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

Checkers 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

Checkers 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