GRAND RAPIDS Griffins
GP: 1 | W: 0 | L: 1
GF: 2 | GA: 3 | PP%: 0.00% | PK%: 100.00%
DG: Justin Guitard | Morale : 99 | Moyenne d'Équipe : 67
Prochain matchs #12 vs BINGHAMTON Devils
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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
1Kenny Agostino0XX100.007246856475807863596562666375685799690285750,000$
2Michael Rasmussen0X100.007848876398757164736162656361628699690216900,000$
3Greg McKegg0X100.007343876473728063776162666375685699680282750,000$
4Michael Chaput0X100.006545886380757362766061656275735299680283800,000$
5Justin Kirkland0XX100.006254846180879160565954586167646699670245850,000$
6Ryan MacInnis0XXX100.006446896186757362686159636167647299670243850,000$
7Trevor Moore0X100.006339876667757265716264636669654299670256900,000$
8Kristian Vesalainen0X100.006545906285757663566159646261638299670212900,000$
9Keegan Kolesar0X100.006749886186777360575958625865636699660235900,000$
10Ryan Poehling0X100.007142896381747262765958645961648299660211750,000$
11Nicholas Merkley (R)0X100.005842896069777362576159586265637899640233750,000$
12Chase Pearson (R)0X100.006243885778818255505356585765635699640233750,000$
13Nate Schnarr (R)0X100.006249845879807657635853565961636699640213750,000$
14Timothy Gettinger (R)0X100.006935686696515266506060506050505699610223750,000$
15Mark Barberio0X100.0062387965777571643063596753786854996803021,450,000$
16Evan Bouchard (R)0X100.006452836681858764306355594861638699680203750,000$
17Christian Folin0X100.007846856087756958305957645377695199670295800,000$
18Yannick Weber0X100.007139856472737862306356615280734199670313750,000$
19Guillaume Brisebois0X100.005943895975777258305756605265636699640235900,000$
20Cody Goloubef0X100.006739835675776454305252644679715999630304750,000$
Rayé
MOYENNE D'ÉQUIPE100.00674485628076746153605862586865649966
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 SP
1Malcolm Subban100.00798280837877797877797873776999710
2Garret Sparks100.00757371847473757473757473775899680
3J-F Berube100.00718987737069717069717077835199670
Rayé
1Christopher Gibson100.00756765827473757473757475816099670
MOYENNE D'ÉQUIPE100.0075787681747375747375747580609968
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Steve Yzerman62626262696960CAN562300,000$


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
1Greg McKeggGRAND RAPIDS Griffins (DET)C110114021101100.00%01616.4800000000010061.90%2100001.2100000000
2Yannick WeberGRAND RAPIDS Griffins (DET)D1011020202110.00%12222.730001100004000.00%000000.8800000000
3Michael ChaputGRAND RAPIDS Griffins (DET)C1011000023000.00%01919.3800000000010062.96%2700001.0300000000
4Ryan MacInnisGRAND RAPIDS Griffins (DET)C/LW/RW1011000012120.00%12323.1800000000000050.00%800000.8600000000
5Trevor MooreGRAND RAPIDS Griffins (DET)LW1011000012140.00%01717.65000000000000100.00%100001.1300000000
6Keegan KolesarGRAND RAPIDS Griffins (DET)RW11010000222050.00%01717.650000000000000.00%000001.1300000000
7Kenny AgostinoGRAND RAPIDS Griffins (DET)LW/RW1000-100317030.00%01717.48000210000000100.00%100000.0000000000
8Christian FolinGRAND RAPIDS Griffins (DET)D1000000110100.00%12222.830000100004000.00%000000.0000000000
9Cody GoloubefGRAND RAPIDS Griffins (DET)D1000000110010.00%01818.450000000000000.00%000000.0000000000
10Mark BarberioGRAND RAPIDS Griffins (DET)D1000-140000000.00%12525.070000000002000.00%000000.0000000000
11Justin KirklandGRAND RAPIDS Griffins (DET)C/LW1000100110010.00%11818.25000000000300100.00%100000.0000000000
12Guillaume BriseboisGRAND RAPIDS Griffins (DET)D1000000011020.00%22222.920000000003000.00%000000.0000000000
13Nicholas MerkleyGRAND RAPIDS Griffins (DET)RW1000-100101000.00%088.920000000000000.00%100000.0000000000
14Evan BouchardGRAND RAPIDS Griffins (DET)D1000-120111000.00%22828.000000000004000.00%000000.0000000000
15Kristian VesalainenGRAND RAPIDS Griffins (DET)LW1000-100002010.00%088.920000000000000.00%000000.0000000000
16Michael RasmussenGRAND RAPIDS Griffins (DET)C1000-100337110.00%02525.0300011000060054.29%3500000.0000000000
Stats d'équipe Total ou en Moyenne16246-41201516317176.45%931219.56000480000330058.95%9500000.3800000000
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
1Garret SparksGRAND RAPIDS Griffins (DET)10010.9142.5770003350000.000010000
Stats d'équipe Total ou en Moyenne10010.9142.5770003350000.000010000


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 MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Chase PearsonGRAND RAPIDS Griffins (DET)C238/23/1997Yes86 Kg188 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Christian FolinGRAND RAPIDS Griffins (DET)D292/9/1991No93 Kg193 CMNoNoNo5Pro & Farm800,000$685,714$800,000$685,714$0$0$No800,000$800,000$800,000$800,000$Lien
Christopher GibsonGRAND RAPIDS Griffins (DET)G2712/27/1992No94 Kg188 CMNoNoNo6Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$750,000$750,000$Lien
Cody GoloubefGRAND RAPIDS Griffins (DET)D3011/30/1989No86 Kg185 CMNoNoNo4Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$Lien
Evan BouchardGRAND RAPIDS Griffins (DET)D2010/20/1999Yes88 Kg191 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Garret SparksGRAND RAPIDS Griffins (DET)G276/28/1993No91 Kg191 CMNoNoNo5Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$750,000$Lien
Greg McKeggGRAND RAPIDS Griffins (DET)C286/17/1992No87 Kg183 CMNoNoNo2Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$Lien
Guillaume BriseboisGRAND RAPIDS Griffins (DET)D237/21/1997No80 Kg188 CMNoNoNo5Pro & Farm900,000$771,429$900,000$771,429$0$0$No900,000$900,000$900,000$900,000$Lien
J-F BerubeGRAND RAPIDS Griffins (DET)G297/13/1991No80 Kg185 CMNoNoNo6Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$750,000$750,000$Lien
Justin KirklandGRAND RAPIDS Griffins (DET)C/LW248/2/1996No83 Kg191 CMNoNoNo5Pro & Farm850,000$728,571$850,000$728,571$0$0$No850,000$850,000$850,000$850,000$Lien
Keegan KolesarGRAND RAPIDS Griffins (DET)RW234/8/1997No103 Kg188 CMNoNoNo5Pro & Farm900,000$771,429$900,000$771,429$0$0$No900,000$900,000$900,000$900,000$Lien
Kenny AgostinoGRAND RAPIDS Griffins (DET)LW/RW284/30/1992No93 Kg183 CMNoNoNo5Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$750,000$Lien
Kristian VesalainenGRAND RAPIDS Griffins (DET)LW216/1/1999No94 Kg191 CMNoNoNo2Pro & Farm900,000$771,429$750,000$642,857$0$0$No900,000$Lien
Malcolm SubbanGRAND RAPIDS Griffins (DET)G2612/21/1993No98 Kg188 CMNoNoNo2Pro & Farm900,000$771,429$900,000$771,429$0$0$No900,000$Lien
Mark BarberioGRAND RAPIDS Griffins (DET)D303/23/1990No91 Kg185 CMNoNoNo2Pro & Farm1,450,000$1,242,857$1,450,000$1,242,857$0$0$No1,450,000$Lien
Michael ChaputGRAND RAPIDS Griffins (DET)C284/9/1992No90 Kg188 CMNoNoNo3Pro & Farm800,000$685,714$800,000$685,714$0$0$No800,000$800,000$Lien
Michael RasmussenGRAND RAPIDS Griffins (DET)C214/17/1999No104 Kg198 CMNoNoNo6Pro & Farm900,000$771,429$750,000$642,857$0$0$No900,000$900,000$900,000$900,000$900,000$Lien
Nate SchnarrGRAND RAPIDS Griffins (DET)C212/25/1999Yes82 Kg191 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Nicholas MerkleyGRAND RAPIDS Griffins (DET)RW235/23/1997Yes88 Kg178 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Ryan MacInnisGRAND RAPIDS Griffins (DET)C/LW/RW242/14/1996No87 Kg193 CMNoNoNo3Pro & Farm850,000$728,571$850,000$728,571$0$0$No850,000$850,000$Lien
Ryan PoehlingGRAND RAPIDS Griffins (DET)C211/3/1999No93 Kg188 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Timothy GettingerGRAND RAPIDS Griffins (DET)LW224/14/1998Yes100 Kg198 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$Lien
Trevor MooreGRAND RAPIDS Griffins (DET)LW253/21/1995No84 Kg178 CMNoNoNo6Pro & Farm900,000$771,429$750,000$642,857$0$0$No900,000$900,000$900,000$900,000$900,000$Lien
Yannick WeberGRAND RAPIDS Griffins (DET)D319/23/1988No91 Kg180 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2425.1790 Kg188 CM3.79829,167$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael RasmussenKenny Agostino31122
2Justin KirklandGreg McKeggRyan MacInnis26122
3Trevor MooreMichael ChaputKeegan Kolesar23122
4Kristian VesalainenRyan MacInnisNicholas Merkley20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark BarberioEvan Bouchard31122
2Christian FolinYannick Weber26122
3Guillaume BriseboisCody Goloubef23122
4Mark BarberioEvan Bouchard20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael RasmussenKenny Agostino55122
2Justin KirklandGreg McKeggRyan MacInnis45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark BarberioEvan Bouchard55122
2Christian FolinYannick Weber45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Michael Rasmussen55122
2Greg McKeggJustin Kirkland45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark BarberioEvan Bouchard55122
2Christian FolinYannick Weber45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Michael Rasmussen55122Mark BarberioEvan Bouchard55122
2Greg McKegg45122Christian FolinYannick Weber45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Michael Rasmussen55122
2Greg McKeggJustin Kirkland45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark BarberioEvan Bouchard55122
2Christian FolinYannick Weber45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael RasmussenKenny AgostinoMark BarberioEvan Bouchard
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael RasmussenKenny AgostinoMark BarberioEvan Bouchard
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Chaput, Ryan MacInnis, Justin KirklandMichael Chaput, Ryan MacInnisMichael Chaput
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Yannick Weber, Guillaume Brisebois, Cody GoloubefYannick WeberYannick Weber, Guillaume Brisebois
Tirs de Pénalité
, Kenny Agostino, Michael Rasmussen, Greg McKegg, Michael Chaput
Gardien
#1 : Garret Sparks, #2 :
Lignes d'Attaque Perso. en Prol.
, Kenny Agostino, Michael Rasmussen, Greg McKegg, Michael Chaput, Ryan MacInnis, Ryan MacInnis, Justin Kirkland, Trevor Moore, Kristian Vesalainen, Keegan Kolesar
Lignes de Défense Perso. en Prol.
Mark Barberio, Evan Bouchard, Christian Folin, Yannick Weber, Guillaume Brisebois


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
LigueDomicileVisiteur
# 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 Devils1010000023-1000000000001010000023-100.00024600002031651373591215100.00%50100.00%0253865.79%224252.38%91947.37%2718297147
Total1010000023-1000000000001010000023-100.00024600002031651373591215100.00%50100.00%0253865.79%224252.38%91947.37%2718297147
_Since Last GM Reset1010000023-1000000000001010000023-100.00024600002031651373591215100.00%50100.00%0253865.79%224252.38%91947.37%2718297147
_Vs Conference1010000023-1000000000001010000023-100.00024600002031651373591215100.00%50100.00%0253865.79%224252.38%91947.37%2718297147
_Vs Division1010000023-1000000000001010000023-100.00024600002031651373591215100.00%50100.00%0253865.79%224252.38%91947.37%2718297147

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
10OTL124631359121500
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
101000023
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
101000023
Derniers 10 Matchs
WLOTWOTL SOWSOL
000100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
100.00%50100.00%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
651370020
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
253865.79%224252.38%91947.37%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2718297147


Derniers Match 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 - 2021-05-154GRAND RAPIDS Griffins2BINGHAMTON Devils3LXSommaire du Match
3 - 2021-05-1712GRAND RAPIDS Griffins-BINGHAMTON Devils-
5 - 2021-05-1920BINGHAMTON Devils-GRAND RAPIDS Griffins-
7 - 2021-05-2128BINGHAMTON Devils-GRAND RAPIDS Griffins-
9 - 2021-05-2336GRAND RAPIDS Griffins-BINGHAMTON Devils-
11 - 2021-05-2544BINGHAMTON Devils-GRAND RAPIDS Griffins-
13 - 2021-05-2752GRAND RAPIDS Griffins-BINGHAMTON Devils-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets3515
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
40 0 - 0.00%0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 1,990,000$ 1,945,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 12 0$ 0$




LigueDomicileVisiteur
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