beholdershellpepitosKingspatriots

 

 


Leftovers

GP: 34 | W: 10 | L: 19 | OTL: 5 | P: 25
GF: 229 | GA: 164 | PP%: 21.77% | PK%: 73.81%
DG: Francois Bedard | Morale : 50 | Moyenne d'Équipe : 75
Prochain matchs #360 vs Barracuda
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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
2Jesper Fast0X100.00812172405068707348857974605443050810
3Scott Laughton0XX100.00825053455450777078808165705050050780
4Peter Holland0X100.00554259437258776581808156785446050780
5Matt Beleskey0X100.00855349437556646246778350666567050770
6Oscar Lindberg0XX100.00813468446552786672798260615847050770
7Tanner Kero0X100.00553479474460846579817769644642050770
8Josh Jooris0X100.00663864486449736473798165714636050760
9Matt Martin0XX100.00995743519137806442807849666072050760
10Ryan Reaves0X100.00975940479035806244787753526673050750
11Josh Leivo0X100.00373763417251686238787956634537050730
12Boo Nieves (R)0X100.00672966537446736278816872633732050730
13Jordan Szwarz (R)0X100.00544659596452855954727459655354050730
14Lias Andersson (R)0X100.00642881635355785847707362654142050710
15Tony DeAngelo (R)0X100.00524461433660808633847452734443050800
16John Gilmour (R)0X100.00532866455362788130767164643932050780
17Rob O'Gara0X100.00673769547956707630776970644943050780
18Steven Kampfer0X100.00803954535859687730756971605242050770
19Adam Clendening0X100.00453654485557887630767058634943050760
20Matt Bartkowski0X100.00824058536651837830767052585243050760
Rayé
1Brad Malone0XX100.00885346678135925846697461595348050710
2Michael Sgarbossa0X100.00624268594851815977717253645145050710
3Vinni Lettieri0X100.00673480514755786037747953643935050710
4Steven Fogarty (R)0X100.00733169707356775631677356654142050700
5Stephen Gionta0XX100.00843672653551775853706958566355050700
6Marek Hrivik0X100.00723384656444555847707552645443050690
7Zach Sanford0X100.00514063587349595940707847683530050690
8Nicklas Jensen0X100.00493367617741655631677350725447050670
9Jamie McBain0X100.00321678584760836931726555565948050730
10Taylor Fedun0X100.00373359516850417430756965635045050730
MOYENNE D'ÉQUIPE100.0067386452645275664876755964514605075
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
1Devante Smith-PellyLeftovers (MOB)LW/RW34333265211407926127398225.98%750614.88461023891011133150.00%30406032.5700000405
2Scott LaughtonLeftovers (MOB)C/LW28214364203208525140467515.00%853519.1381321261030002353168.57%353411012.3901000241
3Oscar LindbergLeftovers (MOB)C/RW34213859121205828127437316.54%1359117.4041721381571343640150.88%114376031.9912000111
4Peter HollandLeftovers (MOB)C3417355222300262385334020.00%1253815.846814281121012120061.76%557164021.9312000031
5Jesper FastLeftovers (MOB)RW341634502480303177325620.78%2037911.1600000000000030.00%101013022.6300000010
6Matt BeleskeyLeftovers (MOB)LW34271845233357421115335323.48%2070320.6962830110538192053045.65%46306031.2811001311
7Josh JoorisLeftovers (MOB)C3424194331140433898215724.49%2139311.5700000000001058.23%316255032.1900000220
8Tanner KeroLeftovers (MOB)C341327401320194384266115.48%3148214.180117410112480162.13%3671312011.6601000110
9Jordan SzwarzLeftovers (MOB)RW3411273833180402764303217.19%745013.24000001123611062.50%16278021.6900000011
10Boo NievesLeftovers (MOB)C31629353080197447203612.77%3153117.140000317881950062.40%6011112011.3200000000
11Tony DeAngeloLeftovers (MOB)D349253428480281265182313.85%2372121.213252412400003110.00%0713000.9401000000
12Matt MartinLeftovers (MOB)LW/RW34142034146820581070195120.00%234710.2200000000010031.82%22201021.9600121001
13Josh LeivoLeftovers (MOB)LW3491726301409860203015.00%1247213.912241389000000125.00%20155011.1000000001
14Ryan ReavesLeftovers (MOB)RW341213252010135361560243120.00%73389.9600000000000043.75%16142021.4800034000
15John GilmourLeftovers (MOB)D344182228120214340221710.00%5170320.681348123011111000.00%0123010.6301000001
16Rob O'GaraLeftovers (MOB)D34216183412033536014293.33%4473521.6311215770113106000.00%0633000.4901000000
17Lias AnderssonLeftovers (MOB)C284121678025235111267.84%436212.952351060000000047.41%135180000.8800000010
18Steven KampferLeftovers (MOB)D343121536375365621122114.29%4755816.41000001122138000.00%0323000.5401001001
19Adam ClendeningLeftovers (MOB)D343111429380164120101715.00%6478122.970112771122181000.00%0616000.3600000000
20Matt BartkowskiLeftovers (MOB)D3447113334048161811822.22%4162418.37000012243203000.00%0411000.3500000000
Stats d'équipe Total ou en Moyenne66525345370648854365783613142948481817.70%4651075716.18375996224117614213551128312658.86%22853372100271.31311157131514
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)34101950.8664.611980211521138610200.5717340011
2Brandon HalversonLeftovers (MOB)40000.7718.158100114825000.0000034000
Stats d'équipe Total ou en Moyenne38101950.8634.752061211631186635200.57173434011


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
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
Jesper FastLeftovers (MOB)RW261991-12-02No191 Lbs183 CMNoNoNo3Avec RestrictionPro & Farm1,850,000$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
Tony DeAngeloLeftovers (MOB)D221995-10-24Yes181 Lbs180 CMNoNoNo1Contrat d'EntréePro & Farm1,263,333$0$0$NoLien
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
3226.41201 Lbs185 CM1.78856,275$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Devante Smith-PellyPeter HollandJesper Fast26014
2Matt MartinTanner KeroOscar Lindberg25113
3Matt BeleskeyBoo NievesRyan Reaves25113
4Josh LeivoJosh JoorisJordan Szwarz24131
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tony DeAngeloJohn Gilmour38122
2Rob O'GaraAdam Clendening37122
3Matt BartkowskiSteven Kampfer25122
4Rob O'GaraTony DeAngelo0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt BeleskeyPeter HollandOscar Lindberg60113
2Josh LeivoOscar LindbergDevante Smith-Pelly40113
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tony DeAngeloJohn Gilmour60122
2Rob O'GaraAdam Clendening40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Boo NievesMatt Beleskey60122
2Oscar LindbergJordan Szwarz40131
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Adam ClendeningMatt Bartkowski60122
2Rob O'GaraSteven Kampfer40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Peter Holland60122Matt BartkowskiJohn Gilmour60122
2Oscar Lindberg40122Rob O'GaraAdam Clendening40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Peter HollandMatt Beleskey60122
2Oscar LindbergJosh Leivo40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tony DeAngeloJohn Gilmour60212
2Rob O'GaraAdam Clendening40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Devante Smith-PellyPeter HollandOscar LindbergTony DeAngeloJohn Gilmour
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt BeleskeyPeter HollandOscar LindbergTony DeAngeloJohn Gilmour
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Tanner Kero, Josh Jooris, Devante Smith-PellyTanner Kero, Boo NievesTanner Kero
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Matt Bartkowski, Steven Kampfer, Rob O'GaraMatt BartkowskiMatt Bartkowski, Steven Kampfer
Tirs de Pénalité
Peter Holland, Oscar Lindberg, Matt Beleskey, 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
1Barbarians20200000610-40000000000020200000610-400.0006121800100685946545939837215721622445120.00%11281.82%142473857.45%45580056.88%39064160.84%773497776277511258
2Barracuda11000000211110000002110000000000021.00023500100685944145939837215177820100.00%6183.33%042473857.45%45580056.88%39064160.84%773497776277511258
3Benchwarmers1010000014-31010000014-30000000000000.0001230010068594274593983721527111627400.00%8450.00%042473857.45%45580056.88%39064160.84%773497776277511258
4Caribou1010000046-21010000046-20000000000000.000471100100685943945939837215342616223133.33%8362.50%142473857.45%45580056.88%39064160.84%773497776277511258
5Giants514000001837-1921100000712-5303000001125-1420.20018314900100685941784593983721520171717827725.93%28775.00%042473857.45%45580056.88%39064160.84%773497776277511258
6Hooligans302010001518-3302010001518-30000000000020.33315274200100685941214593983721512339525411327.27%22863.64%142473857.45%45580056.88%39064160.84%773497776277511258
7Jardiniers411001011215-32010010058-32100000177040.50012203200100685941374593983721513353608418211.11%21385.71%042473857.45%45580056.88%39064160.84%773497776277511258
8Pirates41000300191811000010056-1310002001412250.6251931500010068594147459398372151595760919444.44%30583.33%042473857.45%45580056.88%39064160.84%773497776277511258
9Remparts3300000012131183300000012131180000000000061.00012121533601100685941274593983721563343661000.00%18288.89%1042473857.45%45580056.88%39064160.84%773497776277511258
10Requins20200000613-720200000613-70000000000000.0006121800100685947245939837215692737468225.00%16662.50%042473857.45%45580056.88%39064160.84%773497776277511258
11Royaux21100000981000000000002110000098120.50091322001006859471459398372156426243812325.00%12375.00%142473857.45%45580056.88%39064160.84%773497776277511258
12St Johns2010001079-2100000104311010000036-320.500791600100685947245939837215863124268112.50%7271.43%042473857.45%45580056.88%39064160.84%773497776277511258
Total348190141122916465185901210173789516310002015686-30250.368229398627011006859412384593983721511864535076731242721.77%2105573.81%1442473857.45%45580056.88%39064160.84%773497776277511258
14Werewolves30300000719-121010000034-120200000415-1100.0007132000100685941124593983721511341696014214.29%17758.82%042473857.45%45580056.88%39064160.84%773497776277511258
15Zombie1010000023-1000000000001010000023-100.00023500100685942945939837215251412224125.00%6266.67%042473857.45%45580056.88%39064160.84%773497776277511258
_Since Last GM Reset348190141122916465185901210173789516310002015686-30250.368229398627011006859412384593983721511864535076731242721.77%2105573.81%1442473857.45%45580056.88%39064160.84%773497776277511258
_Vs Conference2461101411199117821547012101646797924002013550-15210.438199347546011006859488145939837215861323356467851922.35%1503775.33%1142473857.45%45580056.88%39064160.84%773497776277511258
_Vs Division114701010150491016430101013016114504000002033-13120.545150262412011006859441745939837215345138139197401025.00%641379.69%1142473857.45%45580056.88%39064160.84%773497776277511258

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
3425L22293986271238118645350767301
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
348191411229164
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
1859121017378
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1631002015686
Derniers 10 Matchs
WLOTWOTL SOWSOL
550000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1242721.77%2105573.81%14
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
4593983721510068594
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
42473857.45%45580056.88%39064160.84%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
773497776277511258


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
2 - 2018-10-024Leftovers6Pirates7LXSommaire du Match
3 - 2018-10-0316Pirates6Leftovers5LXSommaire du Match
6 - 2018-10-0627Hooligans6Leftovers4LSommaire du Match
10 - 2018-10-1044Remparts1Leftovers39WSommaire du Match
11 - 2018-10-1152Leftovers3St Johns6LSommaire du Match
14 - 2018-10-1463Hooligans7Leftovers5LSommaire du Match
15 - 2018-10-1573Leftovers4Jardiniers3WSommaire du Match
16 - 2018-10-1676Leftovers3Giants10LSommaire du Match
19 - 2018-10-1991Caribou6Leftovers4LSommaire du Match
21 - 2018-10-21104Jardiniers6Leftovers5LXSommaire du Match
23 - 2018-10-23114Leftovers2Werewolves8LSommaire du Match
24 - 2018-10-24121Leftovers4Giants6LSommaire du Match
25 - 2018-10-25130St Johns3Leftovers4WXXSommaire du Match
28 - 2018-10-28141Leftovers6Royaux3WSommaire du Match
30 - 2018-10-30150Barracuda1Leftovers2WSommaire du Match
32 - 2018-11-01162Leftovers3Pirates4LXSommaire du Match
33 - 2018-11-02171Requins7Leftovers1LSommaire du Match
35 - 2018-11-04184Jardiniers2Leftovers0LSommaire du Match
37 - 2018-11-06188Leftovers4Barbarians5LSommaire du Match
40 - 2018-11-09201Werewolves4Leftovers3LSommaire du Match
42 - 2018-11-11210Leftovers2Barbarians5LSommaire du Match
44 - 2018-11-13222Giants8Leftovers2LSommaire du Match
46 - 2018-11-15229Leftovers4Giants9LSommaire du Match
48 - 2018-11-17241Leftovers3Jardiniers4LXXSommaire du Match
50 - 2018-11-19247Remparts0Leftovers39WSommaire du Match
52 - 2018-11-21261Hooligans5Leftovers6WXSommaire du Match
53 - 2018-11-22272Leftovers2Werewolves7LSommaire du Match
55 - 2018-11-24281Remparts2Leftovers43WSommaire du Match
58 - 2018-11-27292Leftovers2Zombie3LSommaire du Match
59 - 2018-11-28302Requins6Leftovers5LSommaire du Match
61 - 2018-11-30312Leftovers5Pirates1WSommaire du Match
63 - 2018-12-02322Giants4Leftovers5WSommaire du Match
67 - 2018-12-06340Benchwarmers4Leftovers1LSommaire du Match
69 - 2018-12-08350Leftovers3Royaux5LSommaire du Match
71 - 2018-12-10360Leftovers-Barracuda-
72 - 2018-12-11364Leftovers-Caribou-
73 - 2018-12-12370Hybrides-Leftovers-
76 - 2018-12-15386St Johns-Leftovers-
78 - 2018-12-17394Leftovers-St Johns-
80 - 2018-12-19405Chevalier-Leftovers-
83 - 2018-12-22417Leftovers-Hybrides-
85 - 2018-12-24426Chevalier-Leftovers-
87 - 2018-12-26437Leftovers-Hooligans-
88 - 2018-12-27446Evil Saints-Leftovers-
91 - 2018-12-30459Leftovers-St Johns-
92 - 2018-12-31466Hybrides-Leftovers-
94 - 2019-01-02479Leftovers-Chevalier-
95 - 2019-01-03485Benchwarmers-Leftovers-
98 - 2019-01-06498Leftovers-Chevalier-
99 - 2019-01-07505Diabotins-Leftovers-
101 - 2019-01-09519Leftovers-Evil Saints-
102 - 2019-01-10526Werewolves-Leftovers-
104 - 2019-01-12537Leftovers-Benchwarmers-
106 - 2019-01-14547Diabotins-Leftovers-
109 - 2019-01-17561Casse-Tete-Leftovers-
110 - 2019-01-18567Leftovers-Diabotins-
111 - 2019-01-19575Leftovers-Barracuda-
113 - 2019-01-21585Casse-Tete-Leftovers-
116 - 2019-01-24598Leftovers-Zombie-
118 - 2019-01-26607Zombie-Leftovers-
120 - 2019-01-28621Royaux-Leftovers-
122 - 2019-01-30631Leftovers-Benchwarmers-
124 - 2019-02-01642Royaux-Leftovers-
125 - 2019-02-02646Leftovers-Evil Saints-
128 - 2019-02-05663Leftovers-Caribou-
129 - 2019-02-06665Zombie-Leftovers-
133 - 2019-02-10683Pirates-Leftovers-
135 - 2019-02-12701Caribou-Leftovers-
136 - 2019-02-13703Leftovers-Hooligans-
137 - 2019-02-14709Leftovers-Hybrides-
141 - 2019-02-18721Evil Saints-Leftovers-
143 - 2019-02-20730Leftovers-Remparts-
145 - 2019-02-22742Pirates-Leftovers-
146 - 2019-02-23749Leftovers-Remparts-
148 - 2019-02-25755Leftovers-Diabotins-
150 - 2019-02-27765Barracuda-Leftovers-
152 - 2019-03-01774Leftovers-Casse-Tete-
154 - 2019-03-03783Barbarians-Leftovers-
156 - 2019-03-05795Leftovers-Requins-
159 - 2019-03-08804Barbarians-Leftovers-
160 - 2019-03-09810Leftovers-Casse-Tete-
161 - 2019-03-10818Leftovers-Requins-



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
23 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,089,912$ 2,740,080$ 2,184,830$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
16,914$ 1,089,912$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 92 16,914$ 1,556,088$




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
2018348190141122916465185901210173789516310002015686-3025229398627011006859412384593983721511864535076731242721.77%2105573.81%1442473857.45%45580056.88%39064160.84%773497776277511258
Total Saison Régulière2869413202015916111110486314459520121038673500173142358008568438548-110197111119443055412382351349448211267327202692215819729622676588196217518.19%114321880.93%493184548958.01%3259556958.52%2400415557.76%662342076268233544782271
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
Total Séries18612000003359-26945000002023-3927000001336-2312335386001381115612071382051159022518435044715.91%792074.68%321435560.28%24242556.94%12821858.72%437294418136251125