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Marlies

GP: 5 | W: 5 | L: 0 | OTL: 0 | P: 10
GF: 31 | GA: 10 | PP%: 60.00% | PK%: 100.00%
DG: | Morale : 50 | Moyenne d'Équipe : 61
Prochain matchs #68 vs Rocket
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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 SP
1Michael Dal ColleXX100.00754289638475776453616062656764050640
2Alexander TrueX100.00664789648980776259616063626563050630
3Anders BjorkXX100.00624088647274756260656163626764050630
4Austin WagnerX100.00874981637472836153606456636566050630
5Chris StewartXX100.00794880628961635952605861568273050630
6Mackenzie MacEachernX100.00824378617880716254556357627168050630
7Andy AndreoffX100.00645383627879776156596058627774050630
8Mitchell StephensX100.00594589617277736376606062646563050620
9Nathan BastianX100.00725385618781745954586062596563050620
10Michael McLeodX100.00644985627882766377615864596362050620
11Oliver WahlstromXX100.00654688648374726253585961566062050620
12Beck MalenstynX100.00644888598381795652575861566362050610
13Andy WelinskiX100.00654388627884756130605963527367050630
14Cameron GaunceX100.00614884627680736130655860537868050630
15Libor HajekX100.00644587638182796230605966526364050630
16Nate ProsserX100.00634688608174715830575659538474050620
17Rasmus SandinX100.00573989677177696630635864556063050620
Rayé
1Austin PoganskiX100.00624288607778805954605861596764050610
2Lance BoumaXXX100.00685778588286885752545659557867050610
3Remi ElieX100.00644386618072695853575960626965050610
4Clark BishopX100.00624883607774725860575759606764050600
5Hudson ElynuikX100.00705185558875775360525456536563050590
6Marian StudenicX100.00533989587082835954555756596362050590
7Nate SchnarrX100.00624984587980765763585356596163050590
8Tanner KaspickX100.00614788557484825659535457556362050590
9Blake SpeersX100.00534587566985845561535452566563050580
10David PopeX100.00624388557875775351505456537166050580
11Urho VaakanainenX100.00634287617479725930605865536263050610
12Dylan BlujusX100.00654983558278775430535356457166050590
13Hunter DrewX100.00634977577974735530545356456362050580
14Teemu KivihalmeX100.00524287585585845730565352456965050580
15Vili SaarijarviX100.00533987575883845630545155456562050570
MOYENNE D'ÉQUIPE100.0064468660777876594958575956686505061
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
1Joey Daccord100.0077636180767577767577766771050660
2Stuart Skinner100.0074737188737274737274736367050650
Rayé
MOYENNE D'ÉQUIPE100.007668668475747675747675656905066
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Nathan BastianMarlies (TOR)RW5105151420121569146014.49%58717.5111223000000166.67%600023.4300000300
2Andy AndreoffMarlies (TOR)C559141400151043165111.63%48817.7611243000012172.27%11900003.1500000031
3Anders BjorkMarlies (TOR)LW/RW53584001065216365.77%48817.7901113000231066.67%600001.8000000001
4Mitchell StephensMarlies (TOR)C5707300121647143914.89%57515.1200000000001079.22%7700011.8500000100
5Mackenzie MacEachernMarlies (TOR)LW533600018113718368.11%28617.3510112000000057.14%700001.3800000002
6Rasmus SandinMarlies (TOR)D5145420186137117.69%59018.120001000013000.00%000001.1000000000
7Chris StewartMarlies (TOR)LW/RW1022100011000.00%11717.3200001000030060.00%500002.3100000000
8Michael Dal ColleMarlies (TOR)LW/RW11121001253320.00%02525.1200001000061056.52%2300001.5900000000
9Alexander TrueMarlies (TOR)C11011001163016.67%02222.1200011000260063.64%2200000.9000000000
10Andy WelinskiMarlies (TOR)D1011300212110.00%72525.350000100016000.00%000000.7900000000
11Beck MalenstynMarlies (TOR)LW1000000000000.00%000.250000000000000.00%000000.0000000000
12Austin WagnerMarlies (TOR)LW1000-200341150.00%11515.67000000000000100.00%200000.0000000000
13Nate ProsserMarlies (TOR)D1000-360010010.00%01515.380000000001000.00%000000.0000000000
14Cameron GaunceMarlies (TOR)D1000320110100.00%32323.420000100004000.00%000000.0000000000
15Libor HajekMarlies (TOR)D1000100261020.00%02121.330000000004000.00%000000.0000000000
16Michael McLeodMarlies (TOR)C1000000000000.00%000.480000000000000.00%000000.0000000000
17Oliver WahlstromMarlies (TOR)C/RW1000-200011040.00%01414.7300000000000050.00%1200000.0000000000
Stats d'équipe Total ou en Moyenne413130614212095822789424911.15%3769917.0633610200006405270.61%27900031.7400000434
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
1Stuart SkinnerMarlies (TOR)44000.9471.752400071330200.000041010
2Joey DaccordMarlies (TOR)11000.9193.0060003370000.000010000
Stats d'équipe Total ou en Moyenne55000.9412.0030000101700200.000051010


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 Cap 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
Alexander TrueMarlies (TOR)C221997-07-17No200 Lbs6 ft5NoNoNo2Pro & Farm800,000$0$0$No800,000$Lien / Lien NHL
Anders BjorkMarlies (TOR)LW/RW231996-08-05No190 Lbs6 ft0NoNoNo1Pro & Farm1,066,667$0$0$NoLien / Lien NHL
Andy AndreoffMarlies (TOR)C281991-05-17No203 Lbs6 ft1NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien / Lien NHL
Andy WelinskiMarlies (TOR)D261993-04-27No201 Lbs6 ft1NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Austin PoganskiMarlies (TOR)RW231996-02-16No198 Lbs6 ft1NoNoNo1Pro & Farm762,500$0$0$NoLien / Lien NHL
Austin WagnerMarlies (TOR)LW221997-06-23No185 Lbs6 ft1NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Beck MalenstynMarlies (TOR)LW211998-02-04No200 Lbs6 ft3NoNoNo2Pro & Farm773,333$0$0$No773,333$Lien / Lien NHL
Blake SpeersMarlies (TOR)C221997-01-02No185 Lbs5 ft11NoNoNo1Pro & Farm935,833$0$0$NoLien / Lien NHL
Cameron GaunceMarlies (TOR)D291990-03-19No194 Lbs6 ft1NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Chris StewartMarlies (TOR)LW/RW311987-10-30No242 Lbs6 ft2NoNoNo1Pro & Farm753,757$0$0$NoLien
Clark BishopMarlies (TOR)C231996-03-29No199 Lbs6 ft1NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
David PopeMarlies (TOR)LW251994-09-27No187 Lbs6 ft2NoNoNo1Pro & Farm1,437,500$0$0$NoLien / Lien NHL
Dylan BlujusMarlies (TOR)D251994-01-22No191 Lbs6 ft3NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Hudson ElynuikMarlies (TOR)C211997-10-12No194 Lbs6 ft5NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Hunter DrewMarlies (TOR)D201998-10-21No191 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien
Joey DaccordMarlies (TOR)G231996-08-19No197 Lbs6 ft2NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Lance BoumaMarlies (TOR)C/LW/RW291990-03-25No208 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien
Libor HajekMarlies (TOR)D211998-02-04No203 Lbs6 ft2NoNoNo2Pro & Farm894,166$0$0$No894,166$Lien / Lien NHL
Mackenzie MacEachernMarlies (TOR)LW251994-03-09No190 Lbs6 ft2NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Marian StudenicMarlies (TOR)RW201998-10-28No164 Lbs6 ft1NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Michael Dal ColleMarlies (TOR)LW/RW231996-06-20No204 Lbs6 ft3NoNoNo2Pro & Farm700,000$0$0$No700,000$Lien / Lien NHL
Michael McLeodMarlies (TOR)C211998-02-03No188 Lbs6 ft2NoNoNo2Pro & Farm1,363,333$0$0$No1,363,333$Lien / Lien NHL
Mitchell StephensMarlies (TOR)C221997-02-05No193 Lbs5 ft11NoNoNo1Pro & Farm919,166$0$0$NoLien / Lien NHL
Nate ProsserMarlies (TOR)D331986-05-07No201 Lbs6 ft2NoNoNo2Pro & Farm700,000$0$0$No700,000$Lien / Lien NHL
Nate SchnarrMarlies (TOR)C201999-02-25No180 Lbs6 ft3NoNoNo3Pro & Farm894,167$0$0$No894,167$894,167$Lien
Nathan BastianMarlies (TOR)RW211997-12-06No205 Lbs6 ft4NoNoNo2Pro & Farm905,000$0$0$No905,000$Lien / Lien NHL
Oliver WahlstromMarlies (TOR)C/RW192000-06-13No211 Lbs6 ft2NoNoNo3Pro & Farm1,462,500$0$0$No1,462,500$1,462,500$Lien
Rasmus SandinMarlies (TOR)D192000-03-07No183 Lbs5 ft11NoNoNo3Pro & Farm894,167$0$0$No894,167$894,167$Lien / Lien NHL
Remi ElieMarlies (TOR)LW241995-04-16No215 Lbs6 ft1NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Stuart SkinnerMarlies (TOR)G201998-11-01No206 Lbs6 ft4NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Tanner KaspickMarlies (TOR)C211998-01-28No200 Lbs6 ft0NoNoNo2Pro & Farm822,222$0$0$No822,222$Lien / Lien NHL
Teemu KivihalmeMarlies (TOR)D241995-06-17No161 Lbs5 ft1NoNoNo1Pro & Farm925,000$0$0$NoLien
Urho VaakanainenMarlies (TOR)D201999-01-01No185 Lbs6 ft1NoNoNo3Pro & Farm1,302,500$0$0$No1,302,500$1,302,500$Lien / Lien NHL
Vili SaarijarviMarlies (TOR)D221997-05-15No182 Lbs5 ft1NoNoNo1Pro & Farm930,000$0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3423.18195 Lbs6 ft11.56879,171$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael Dal ColleAlexander TrueChris Stewart30122
2Anders BjorkAndy AndreoffNathan Bastian30122
3Austin WagnerOliver WahlstromMackenzie MacEachern25122
4Mackenzie MacEachernMitchell StephensMichael Dal Colle15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Cameron GaunceAndy Welinski30122
2Libor HajekRasmus Sandin30122
3Nate ProsserMitchell Stephens25122
4Cameron GaunceAndy Welinski15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael Dal ColleAlexander TrueChris Stewart60122
2Anders BjorkAndy AndreoffNathan Bastian40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Cameron GaunceAndy Welinski60122
2Libor HajekRasmus Sandin40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Michael Dal ColleAlexander True60122
2Chris StewartAnders Bjork40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Cameron GaunceAndy Welinski60122
2Libor HajekRasmus Sandin40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Michael Dal Colle60122Cameron GaunceAndy Welinski60122
2Alexander True40122Libor HajekRasmus Sandin40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Michael Dal ColleAlexander True60122
2Chris StewartAnders Bjork40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Cameron GaunceAndy Welinski60122
2Libor HajekRasmus Sandin40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael Dal ColleAlexander TrueChris StewartCameron GaunceAndy Welinski
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael Dal ColleAlexander TrueChris StewartCameron GaunceAndy Welinski
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael McLeod, Beck Malenstyn, Austin WagnerMichael McLeod, Beck MalenstynAustin Wagner
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nate Prosser, Libor Hajek, Rasmus SandinNate ProsserLibor Hajek, Rasmus Sandin
Tirs de Pénalité
Michael Dal Colle, Alexander True, Chris Stewart, Anders Bjork, Austin Wagner
Gardien
#1 : Joey Daccord, #2 : Stuart Skinner


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
1Americans220000001358110000007341100000062441.0001320330014107012393124154091232663266.67%10100.00%014321466.82%9714865.54%508558.82%15912485255531
2Rocket11000000431000000000001100000043121.0004711001410703793124154037141221100.00%50100.00%014321466.82%9714865.54%508558.82%15912485255531
3Senators2200000014212110000008171100000061541.00014213500141070211931241540421305711100.00%000.00%014321466.82%9714865.54%508558.82%15912485255531
Total5500000031102122000000154113300000016610101.0003148790014107037193124154017050141445360.00%60100.00%014321466.82%9714865.54%508558.82%15912485255531
_Since Last GM Reset5500000031102122000000154113300000016610101.0003148790014107037193124154017050141445360.00%60100.00%014321466.82%9714865.54%508558.82%15912485255531
_Vs Conference5500000031102122000000154113300000016610101.0003148790014107037193124154017050141445360.00%60100.00%014321466.82%9714865.54%508558.82%15912485255531
_Vs Division5500000031102122000000154113300000016610101.0003148790014107037193124154017050141445360.00%60100.00%014321466.82%9714865.54%508558.82%15912485255531

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
510W5314879371170501414400
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
55000003110
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2200000154
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3300000166
Derniers 10 Matchs
WLOTWOTL SOWSOL
500000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
5360.00%60100.00%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
931241540141070
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
14321466.82%9714865.54%508558.82%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
15912485255531


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
3 - 2020-04-0710Senators1Marlies8WSommaire du Match
4 - 2020-04-0824Marlies6Senators1WSommaire du Match
6 - 2020-04-1034Americans3Marlies7WSommaire du Match
7 - 2020-04-1142Marlies6Americans2WSommaire du Match
9 - 2020-04-1358Marlies4Rocket3WSommaire du Match
11 - 2020-04-1568Rocket-Marlies-
13 - 2020-04-1785Marlies-Griffins-
14 - 2020-04-1893Griffins-Marlies-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
39 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 2,989,182$ 1,750,368$ 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$ 6 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
Saison Régulière
282224905222247346-9941112303202125181-5641112602020122165-43442474406870289826982310774742774343354964104115822745620.44%4109676.59%21023241142.43%1069287337.21%539134740.01%1724115522126111016480
382116501122177424-247415320002291206-115416330110086218-132221773174940067575032458756890795274421129391116212843913.73%36710471.66%1834237535.12%1100325433.80%466133734.85%13709052640607933386
482126101035167428-261416290102388194-106416320001279234-1552416730947610605746922887537767306041601244106915224805812.08%41412270.53%1967244339.58%1094319134.28%527132739.71%13668732631654964400
582224901244243345-10241152001212134160-264172900032109185-764424338362611867874102929908981100871328091943519332084320.67%2015373.63%31371276549.58%1244270745.95%676140348.18%184713292151559970459
68234400023330427430412117000211611253641132300212143149-6683045018055614181796364011471213126636331497344120972184219.27%1724176.16%11554315049.33%1405321143.76%621134346.24%196514262007559979478
7823434022822932732041161801051147140741181601231146133136829352081321119867814348411551187110782312388350021572184018.35%2214778.73%11828318157.47%1639309852.91%737136953.83%2039145919255601014510
88250250104240223716541261101021200104964124140002120213369100402736113813184124897404813371320136845261975647420481884423.40%1904078.95%12052336960.91%1470270354.38%838138860.37%227616881690514987524
88250250104240223716541261101021200104964124140002120213369100402736113813184124897404813371320136845261975647420481884423.40%1904078.95%12052336960.91%1470270354.38%838138860.37%227616881690514987524
Total Saison Régulière6562353480129302222352564-329328126161084161311461214-6832810918704514910891350-26147022353942617711169306895746425205816784298416400268907788534515008205836617.78%216554374.92%11116812306350.65%104912374044.19%52421090248.08%148661052816951458378543764
Séries
6404000001022-1220200000613-72020000049-5010152500532012634494302046326701417.14%13469.23%04213231.82%8117546.29%326648.48%7449117314721
7116500000393635320000023185633000001618-21239661050011141314361381501351342712570275361027.78%31777.42%023145051.33%20642248.82%9619349.74%2621812838414971
8624000002326-33210000012120303000001114-342341640097702057260721230704411617529.41%21957.14%010921650.46%8021637.04%6111254.46%13189156417335
Total Séries21813000007284-121055000004143-21138000003141-10167212219400252422176724425925014861258140461671623.88%652069.23%038279847.87%36781345.14%18937150.94%467320558156270128