beholdershellpepitosKingspatriots

 

 


Leftovers

GP: 5 | W: 1 | L: 4 | OTL: 0 | P: 2
GF: 18 | GA: 27 | PP%: 11.54% | PK%: 67.57%
DG: Francois Bedard | Morale : 50 | Moyenne d'Équipe : 75
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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
1Devante Smith-Pelly0XX100.00853866437758747451838369706061050830
2Brian Gibbons (R)0X100.00453366393366687048847779685445017790
3Scott Laughton0XX100.00825053455450777078808165705050050780
4Peter Holland0X100.00554259437258776581808156785446050780
5Cory Conacher0XXX100.00563739363445937737808458715753018770
6Matt Beleskey0X100.00855349437556646246778350666567050770
7Oscar Lindberg0XX100.00813468446552786672798260615847050770
8Tanner Kero0X100.00553479474460846579817769644642050770
9Josh Jooris0X100.00663864486449736473798165714636050760
10Matt Martin0XX100.00995743519137806442807849666072050760
11Ryan Reaves0X100.00975940479035806244787753526673050750
12Boo Nieves (R)0X100.00672966537446736278816872633732050730
13John Gilmour (R)0X100.00532866455362788130767164643932050780
14Rob O'Gara0X100.00673769547956707630776970644943050780
15Steven Kampfer0X100.00803954535859687730756971605242050770
16Adam Clendening0X100.00453654485557887630767058634943050760
17Matt Bartkowski0X100.00824058536651837830767052585243050760
18Jamie McBain0X100.00321678584760836931726555565948050730
Rayé
1Josh Leivo0X100.00373763417251686238787956634537050730
2Jordan Szwarz (R)0X100.00544659596452855954727459655354050730
3Brad Malone0XX100.00885346678135925846697461595348050710
4Michael Sgarbossa0X100.00624268594851815977717253645145050710
5Vinni Lettieri0X100.00673480514755786037747953643935050710
6Lias Andersson (R)0X100.00642881635355785847707362654142050710
7Steven Fogarty (R)0X100.00733169707356775631677356654142050700
8Stephen Gionta0XX100.00843672653551775853706958566355050700
9Marek Hrivik0X100.00723384656444555847707552645443050690
10Zach Sanford0X100.00514063587349595940707847683530050690
11Nicklas Jensen0X100.00493367617741655631677350725447050670
12Taylor Fedun0X100.00373359516850417430756965635045050730
MOYENNE D'ÉQUIPE100.0066386352635275664876756064514704874
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
1Marek Mazanec100.0080916478808183848480716264050830
2Brandon Halverson (R)100.0080825681808188848468712141050790
Rayé
MOYENNE D'ÉQUIPE100.008087608080818684847471425305081
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
David Quinn70707070707070CAN455450,000$


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'ÉquipePOS GP 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
1Cory ConacherLeftovers (MOB)C/LW/RW5821076038188644.44%37715.54112425000001130.56%3600022.5700000200
2Devante Smith-PellyLeftovers (MOB)LW/RW5268700114187911.11%37114.26101216000010066.67%610002.2400000010
3Peter HollandLeftovers (MOB)C51569202751520.00%05410.9500001000000060.00%5001002.1900000000
4Scott LaughtonLeftovers (MOB)C/LW5415-320871871322.22%17214.57112725000000050.00%223001.3700000000
5Matt BeleskeyLeftovers (MOB)LW5224-110038125816.67%39218.43011020001330057.14%772000.8700000000
6Oscar LindbergLeftovers (MOB)C/RW5044-4609417330.00%49819.750226290000130045.33%7560000.8100000000
7John GilmourLeftovers (MOB)D5033-220495410.00%79719.4100002200000000.00%003000.6200000000
8Rob O'GaraLeftovers (MOB)D50334005145350.00%1111222.47000318000016000.00%002000.5300000001
9Josh JoorisLeftovers (MOB)C5022-2000105450.00%25711.4900000000030055.36%5621000.7000000000
10Matt BartkowskiLeftovers (MOB)D5112-2004731033.33%1010220.5800001000041000.00%011000.3900000000
11Brian GibbonsLeftovers (MOB)LW5011-44051114970.00%67214.59011216000070050.00%201000.2700000000
12Matt MartinLeftovers (MOB)LW/RW5011-1120674380.00%15310.65000000000000100.00%200000.3800000000
13Ryan ReavesLeftovers (MOB)RW5011-336101003030.00%2479.4400000000000050.00%201000.4200101000
14Tanner KeroLeftovers (MOB)C5011-30071617090.00%1110120.20000090004400056.67%9042000.2000000000
15Adam ClendeningLeftovers (MOB)D5000-240246230.00%29519.0200032200000000.00%000000.0000000000
16Steven KampferLeftovers (MOB)D5000-260564420.00%57314.7500011000115000.00%001000.0000000000
Stats d'équipe Total ou en Moyenne80183351-2901084122154618711.69%71128016.013692819200061711151.83%3282318020.8000101211
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
1Marek MazanecLeftovers (MOB)51310.8745.60268202519894000.000050010
2Brandon HalversonLeftovers (MOB)10000.9002.86420022010000.000005000
Stats d'équipe Total ou en Moyenne61310.8765.213112027218104000.000055010


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Adam ClendeningLeftovers (MOB)D251992-10-26No196 Lbs183 CMNoNoNo1Avec RestrictionPro & Farm600,000$0$0$NoLien / Lien NHL
Boo NievesLeftovers (MOB)C241994-01-23Yes212 Lbs191 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien
Brad MaloneLeftovers (MOB)C/LW291989-05-20No213 Lbs185 CMNoNoNo2Sans RestrictionPro & Farm780,000$0$0$NoLien / Lien NHL
Brandon HalversonLeftovers (MOB)G221996-03-29Yes209 Lbs193 CMNoNoNo2Contrat d'EntréePro & Farm894,167$0$0$NoLien
Brian GibbonsLeftovers (MOB)LW301988-02-26Yes175 Lbs173 CMNoNoNo2Sans RestrictionPro & Farm650,000$0$0$NoLien
Cory ConacherLeftovers (MOB)C/LW/RW281989-12-14No180 Lbs173 CMNoNoNo1Avec RestrictionPro & Farm575,000$0$0$NoLien
Devante Smith-PellyLeftovers (MOB)LW/RW261992-06-14No223 Lbs183 CMNoNoNo2Avec RestrictionPro & Farm1,300,000$0$0$NoLien / Lien NHL
Jamie McBainLeftovers (MOB)D301988-02-25No180 Lbs185 CMNoNoNo2Sans RestrictionPro & Farm780,000$0$0$NoLien / Lien NHL
John GilmourLeftovers (MOB)D251993-05-17Yes195 Lbs183 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien
Jordan SzwarzLeftovers (MOB)RW271991-05-14Yes200 Lbs180 CMNoNoNo2Avec RestrictionPro & Farm650,000$0$0$NoLien
Josh JoorisLeftovers (MOB)C281990-07-14No197 Lbs185 CMNoNoNo1Avec RestrictionPro & Farm600,000$0$0$NoLien / Lien NHL
Josh LeivoLeftovers (MOB)LW251993-05-26No210 Lbs188 CMNoNoNo2Avec RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Lias AnderssonLeftovers (MOB)C191998-10-13Yes204 Lbs183 CMNoNoNo2Contrat d'EntréePro & Farm1,775,000$0$0$NoLien
Marek HrivikLeftovers (MOB)RW271991-08-28No197 Lbs188 CMNoNoNo2Avec RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Marek MazanecLeftovers (MOB)G271991-07-18No187 Lbs193 CMNoNoNo2Avec RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Matt BartkowskiLeftovers (MOB)D301988-06-04No196 Lbs185 CMNoNoNo2Sans RestrictionPro & Farm735,000$0$0$NoLien / Lien NHL
Matt BeleskeyLeftovers (MOB)LW301988-06-07No203 Lbs183 CMNoNoNo1Sans RestrictionPro & Farm782,496$0$0$NoLien / Lien NHL
Matt MartinLeftovers (MOB)LW/RW291989-05-08No220 Lbs191 CMNoNoNo2Sans RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Michael SgarbossaLeftovers (MOB)C261992-07-25No186 Lbs183 CMNoNoNo1Avec RestrictionPro & Farm600,000$0$0$NoLien / Lien NHL
Nicklas JensenLeftovers (MOB)RW251993-03-06No216 Lbs191 CMNoNoNo2Avec RestrictionPro & Farm949,300$0$0$NoLien / Lien NHL
Oscar LindbergLeftovers (MOB)C/RW261991-10-29No202 Lbs185 CMNoNoNo1Avec RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Peter HollandLeftovers (MOB)C271991-01-14No205 Lbs188 CMNoNoNo2Avec RestrictionPro & Farm675,000$0$0$NoLien / Lien NHL
Rob O'GaraLeftovers (MOB)D251993-07-06No215 Lbs193 CMNoNoNo1Avec RestrictionPro & Farm450,001$0$0$NoLien
Ryan ReavesLeftovers (MOB)RW311987-01-20No225 Lbs185 CMNoNoNo2Sans RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Scott LaughtonLeftovers (MOB)C/LW241994-05-30No190 Lbs185 CMNoNoNo2Avec RestrictionPro & Farm962,500$0$0$NoLien / Lien NHL
Stephen GiontaLeftovers (MOB)C/RW341983-10-09No177 Lbs170 CMNoNoNo2Sans RestrictionPro & Farm1,224,000$0$0$NoLien / Lien NHL
Steven FogartyLeftovers (MOB)C251993-04-19Yes209 Lbs191 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Steven KampferLeftovers (MOB)D291988-09-24No195 Lbs180 CMNoNoNo2Sans RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Tanner KeroLeftovers (MOB)C261992-07-24No185 Lbs183 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien / Lien NHL
Taylor FedunLeftovers (MOB)D301988-06-04No201 Lbs185 CMNoNoNo2Sans RestrictionPro & Farm780,000$0$0$NoLien / Lien NHL
Vinni LettieriLeftovers (MOB)C231995-02-06No195 Lbs180 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien
Zach SanfordLeftovers (MOB)LW231994-11-09No207 Lbs193 CMNoNoNo1Avec RestrictionPro & Farm925,000$0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3226.72200 Lbs185 CM1.75797,265$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Devante Smith-PellyPeter HollandCory Conacher26014
2Brian GibbonsTanner Kero25113
3Scott LaughtonOscar LindbergRyan Reaves25113
4Matt BeleskeyJosh JoorisMatt Martin24131
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Adam ClendeningJohn Gilmour38122
2Rob O'Gara37122
3Matt BartkowskiSteven Kampfer25122
4Rob O'Gara0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Scott LaughtonCory ConacherOscar Lindberg60113
2Brian GibbonsOscar LindbergDevante Smith-Pelly40113
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Adam ClendeningJohn Gilmour60122
2Rob O'Gara40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Tanner KeroMatt Beleskey60122
2Oscar Lindberg40131
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt Bartkowski60122
2Rob O'GaraSteven Kampfer40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Peter Holland60122Matt BartkowskiJohn Gilmour60122
2Oscar Lindberg40122Rob O'Gara40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Peter HollandMatt Beleskey60122
2Oscar LindbergScott Laughton40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1John Gilmour60212
2Rob O'GaraSteven Kampfer40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Devante Smith-PellyCory ConacherOscar LindbergAdam ClendeningJohn Gilmour
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt BeleskeyPeter HollandOscar LindbergJohn Gilmour
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Tanner Kero, Josh Jooris, Devante Smith-PellyTanner Kero, Matt BeleskeyTanner Kero
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Matt Bartkowski, Steven Kampfer, Rob O'GaraMatt BartkowskiMatt Bartkowski, Steven Kampfer
Tirs de Pénalité
Brian Gibbons, Oscar Lindberg, Cory Conacher, Tanner Kero, Josh Jooris
Gardien
#1 : Marek Mazanec, #2 : Brandon Halverson


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
1Jardiniers514000001827-9211000001210230300000617-1120.200183452009630154674339521871948426311.54%371267.57%04510742.06%8314955.70%447757.14%10361132457435
Total514000001827-9211000001210230300000617-1120.200183452009630154674339521871948426311.54%371267.57%04510742.06%8314955.70%447757.14%10361132457435
_Since Last GM Reset514000001827-9211000001210230300000617-1120.200183452009630154674339521871948426311.54%371267.57%04510742.06%8314955.70%447757.14%10361132457435
_Vs Conference514000001827-9211000001210230300000617-1120.200183452009630154674339521871948426311.54%371267.57%04510742.06%8314955.70%447757.14%10361132457435

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
52L118345215421871948400
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
51400001827
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
21100001210
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3030000617
Derniers 10 Matchs
WLOTWOTL SOWSOL
130100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
26311.54%371267.57%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
67433959630
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
4510742.06%8314955.70%447757.14%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
10361132457435


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 - 2019-04-037Leftovers2Jardiniers8LSommaire du Match
2 - 2019-04-0415Leftovers2Jardiniers4LSommaire du Match
3 - 2019-04-0523Jardiniers2Leftovers5WSommaire du Match
4 - 2019-04-0631Jardiniers8Leftovers7LXSommaire du Match
5 - 2019-04-0739Leftovers2Jardiniers5LSommaire du Match



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$ 2,551,247$ 2,006,580$ 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$ 3 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
20168446220732444219225042297021122548616842171505212188106829244277412160413813416111260683388985451221481993918532756222.55%3235682.66%141033165662.38%987159162.04%783121764.34%2097138617146651277661
2017842439073653042455942161405313169104654282502052135141-648304530834231121017818256282685183191231275771418812814415.66%3486780.75%141029172959.51%997159862.39%701112562.31%2049133717766711298660
201784165205506136447-311429220440377232-155427300110359215-156321362423782432485111180555558263558248593351614742824214.89%2624084.73%7698136651.10%820158051.90%526117244.88%170298520017211391691
201882244803421473374994115200222026117388419280120121220111484738241297222001451238302911659109402529221056130115222716122.51%54914573.59%251112178462.33%1211197461.35%880141562.19%1895123318526531204603
Total Saison Régulière334110161022151016135512589716769630131048761595166167419809568594663-6922013552370372561348242841348100023379323232602259933356534706730110920918.85%148230879.22%603872653559.25%4015674359.54%2890492958.63%774449427344271151712616
Séries
2016954000001918153200000101004220000098110193251009361293113701064247941141932328.70%43783.72%212118665.05%13519369.95%7510273.53%2451711776712565
201640400000322-192020000037-420200000015-15033600030077292123416958146410220.00%7442.86%0166425.00%2510424.04%94918.37%6739128325725
2017514000001119-82110000076130300000413-92111829004250191654776317473569311327.27%29968.97%17710573.33%8212864.06%446765.67%12484111376734
2018514000001827-9211000001210230300000617-112183452009630154674339521871948426311.54%371267.57%04510742.06%8314955.70%447757.14%10361132457435
Total Séries23716000005186-351156000003233-112210000001953-3414518713800221414171527418124416808296278434701014.29%1163272.41%325946256.06%32557456.62%17229558.31%541356551182325160