3L

GP: 5 | W: 1 | L: 4
GF: 11 | GA: 15 | PP%: 35.29% | PK%: 62.50%
DG: William Soucy | Morale : 50 | Moyenne d'Équipe : 62
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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
1Boo NievesX100.00563594837163485053485370525766036650
2Connor BrickleyX100.00663893826362395049465364526370050640
3Peter HollandX100.00523494836858364850445360556668047620
4Josh Currie (R)X100.00583395874959254849435264516368050610
5Drew ShoreX100.00493195837055254546405060506666045600
6Freddie HamiltonX100.00513295846254264646405059506365049590
7Samuel Henley (R)X100.00453095827350254540405055506062050580
8Ronalds KeninsX100.00473195826251264541415055506665050580
9Carter AshtonX100.00453095817350254541405055506665050580
10Sheldon Rempal (R)X100.00453395874656254548405060505460050570
11Justin ShuggX100.00453095845550254540405055506665050570
12Zack Mitchell (R)X100.00453095836350254540405055506062050570
13Matt GrzelcykX100.00633679874474796049625876565771039720
14Alex BiegaX100.00823291835565505650575367527581048690
15Paul PostmaX100.00503295856359384949495158507270050630
16Bryan AllenX100.00453395817750254552455055509982050620
17Ryan SproulX100.00473295846963274948495255516064050620
Rayé
1Christian Thomas (R)X100.00453095854850254540405055506363050560
2Sergey Tolchinsky (R)X100.00453095864450254540405055505459050560
3Fedor TyutinX100.00563394807057404851495160509081047650
MOYENNE D'ÉQUIPE100.0052329484615633484645516051666804861
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
1Mackenzie Blackwood (R)100.0078368482718081787465684556051720
2Steve Mason100.0071368479667071707069637769044680
Rayé
1Scott Wedgewood (R)100.0060257074616060606065556153050580
2Dylan Ferguson (R)100.0060256672636060606065553741050570
MOYENNE D'ÉQUIPE100.006731767765686867666660555504964
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Geoff Ward70737879707268CAN5641,000,000$


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
1Ronalds Kenins3L (WAS)LW542620028147328.57%29519.193143110000100066.67%323001.2500000101
2Alex Biega3L (WAS)D5123-460101112638.33%713627.37112214000018000.00%047000.4400000001
3Connor Brickley3L (WAS)LW5123-360142013687.69%39418.91011180000110062.50%831000.6300000010
4Matt Grzelcyk3L (WAS)D4123-412089171075.88%410426.05112513000011000.00%035000.5800000000
5Peter Holland3L (WAS)C503320091213120.00%18717.57022110000050046.03%6353000.6800000010
6Carter Ashton3L (WAS)RW51122006864516.67%08116.2201111100000000.00%321000.4900000000
7Boo Nieves3L (WAS)C5202-310041621569.52%512124.231011110001131046.56%13157000.3300000000
8Fedor Tyutin3L (WAS)D4022160583100.00%57919.770110800001100100.00%114000.5100000000
9Freddie Hamilton3L (WAS)C5011000271110.00%25210.5200000000000052.17%2341000.3800000000
10Bryan Allen3L (WAS)D5011200564000.00%56212.530000100001000.00%034000.3200000000
11Zack Mitchell3L (WAS)RW51011003883412.50%1499.8500000000000050.00%212000.4100000000
12Paul Postma3L (WAS)D5011120296220.00%310020.0901119000112000.00%006000.2000000000
13Samuel Henley3L (WAS)C5000-100244010.00%05110.3600005000050062.50%810000.0000000000
14Drew Shore3L (WAS)C5000120855520.00%26913.90000100000140043.24%3722000.0000000000
15Josh Currie3L (WAS)RW5000-4201347160.00%28016.06000113000050050.00%435000.0000000000
16Sheldon Rempal3L (WAS)RW5000000100210.00%1255.120000300000000.00%100000.0000000000
17Ryan Sproul3L (WAS)D5000220464000.00%66513.110000000009000.00%040000.0000000000
18Justin Shugg3L (WAS)RW5000000435210.00%05210.470000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne88111728-548010214414356527.69%49141016.0369151712400021291047.18%2844351000.4000000122
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
1Steve Mason3L (WAS)31110.9172.531660078443100.000025000
2Mackenzie Blackwood3L (WAS)30200.9103.611330088949000.000030000
Stats d'équipe Total ou en Moyenne61310.9133.00300001517392100.000055000


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 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
Alex Biega3L (WAS)D321988-01-01No199 Lbs5 ft10NoNoNo1Pro & Farm500,000$0$0$NoLien / Lien NHL
Boo Nieves3L (WAS)C261994-01-01No210 Lbs6 ft3NoNoNo1Pro & Farm600,000$0$0$NoLien NHL
Bryan Allen3L (WAS)D401980-01-01No223 Lbs6 ft5NoNoNo1Pro & Farm500,000$0$0$NoLien
Carter Ashton3L (WAS)RW291991-01-01No215 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$
Christian Thomas3L (WAS)LW281992-01-01Yes175 Lbs5 ft9NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$
Connor Brickley3L (WAS)LW281992-01-01No203 Lbs6 ft0NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien NHL
Drew Shore3L (WAS)C291991-01-01No205 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$
Dylan Ferguson3L (WAS)G221998-01-01Yes189 Lbs6 ft1NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien NHL
Fedor Tyutin3L (WAS)D371983-01-01No221 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLien
Freddie Hamilton3L (WAS)C281992-01-01No195 Lbs6 ft1NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien NHL
Josh Currie3L (WAS)RW281992-01-01Yes172 Lbs5 ft10NoNoNo1Pro & Farm700,000$0$0$No
Justin Shugg3L (WAS)RW291991-01-01No185 Lbs5 ft11NoNoNo1Pro & Farm600,000$0$0$No
Mackenzie Blackwood3L (WAS)G241996-01-01Yes225 Lbs6 ft4NoNoNo1Pro & Farm750,000$0$0$No
Matt Grzelcyk3L (WAS)D261994-01-01No174 Lbs5 ft9NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Paul Postma3L (WAS)D311989-01-01No195 Lbs6 ft3NoNoNo1Pro & Farm600,000$0$0$NoLien / Lien NHL
Peter Holland3L (WAS)C291991-01-01No205 Lbs6 ft2NoNoNo2Pro & Farm1,000,000$0$0$No1,000,000$Lien NHL
Ronalds Kenins3L (WAS)LW291991-01-01No201 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Ryan Sproul3L (WAS)D271993-01-01No211 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien / Lien NHL
Samuel Henley3L (WAS)C271993-01-01Yes210 Lbs6 ft4NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$
Scott Wedgewood3L (WAS)G281992-01-01Yes195 Lbs6 ft2NoNoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$Lien NHL
Sergey Tolchinsky3L (WAS)LW251995-01-01Yes170 Lbs5 ft8NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Sheldon Rempal3L (WAS)RW251995-01-01Yes165 Lbs5 ft10NoNoNo1Pro & Farm700,000$0$0$No
Steve Mason3L (WAS)G321988-01-01No210 Lbs6 ft4NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien NHL
Zack Mitchell3L (WAS)RW271993-01-01Yes196 Lbs6 ft1NoNoNo1Pro & Farm600,000$0$0$NoLien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2428.58198 Lbs6 ft12.00595,833$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Connor BrickleyBoo NievesJosh Currie40122
2Ronalds KeninsPeter HollandCarter Ashton30122
3Boo NievesDrew ShoreZack Mitchell20122
4Connor BrickleyFreddie HamiltonJustin Shugg10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykAlex Biega40122
2Paul Postma30122
3Bryan AllenRyan Sproul20122
4Matt GrzelcykAlex Biega10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Connor BrickleyBoo NievesJosh Currie60122
2Ronalds KeninsPeter HollandCarter Ashton40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykAlex Biega60122
2Paul Postma40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Boo NievesConnor Brickley60122
2Peter HollandJosh Currie40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykAlex Biega60122
2Paul Postma40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Boo Nieves60122Matt GrzelcykAlex Biega60122
2Connor Brickley40122Paul Postma40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Boo NievesConnor Brickley60122
2Peter HollandJosh Currie40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykAlex Biega60122
2Paul Postma40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Connor BrickleyBoo NievesJosh CurrieMatt GrzelcykAlex Biega
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Connor BrickleyBoo NievesJosh CurrieMatt GrzelcykAlex Biega
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Samuel Henley, Sheldon Rempal, Drew ShoreSamuel Henley, Sheldon RempalDrew Shore
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Bryan Allen, Ryan Sproul, Bryan AllenRyan Sproul,
Tirs de Pénalité
Boo Nieves, Connor Brickley, Peter Holland, Josh Currie, Drew Shore
Gardien
#1 : Mackenzie Blackwood, #2 : Steve Mason


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
Total514000001115-4312000008802020000037-420.2001117280032601443242700173504810217635.29%24962.50%0389141.76%6612552.80%306844.12%9344109519749
2Wolf Pack514000001115-4312000008802020000037-420.2001117280032601443242700173504810217635.29%24962.50%0389141.76%6612552.80%306844.12%9344109519749
_Since Last GM Reset514000001115-4312000008802020000037-420.2001117280032601443242700173504810217635.29%24962.50%0389141.76%6612552.80%306844.12%9344109519749
_Vs Conference514000001115-4312000008802020000037-420.2001117280032601443242700173504810217635.29%24962.50%0389141.76%6612552.80%306844.12%9344109519749

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
52L3111728144173504810200
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
51400001115
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
312000088
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
202000037
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
17635.29%24962.50%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
32427003260
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
389141.76%6612552.80%306844.12%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
9344109519749


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 - 2020-07-202Wolf Pack23L5WSommaire du Match
2 - 2020-07-2110Wolf Pack23L1LXSommaire du Match
3 - 2020-07-22183L1Wolf Pack3LSommaire du Match
4 - 2020-07-23263L2Wolf Pack4LSommaire du Match
5 - 2020-07-2434Wolf Pack43L2LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance6,0003,000
Assistance PCT100.00%100.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
36 3000 - 100.00% 97,750$293,250$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 1,430,000$ 1,430,000$ 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$ 0 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
1178293700723215255-4039121900512109130-2139171800211106125-19582153595742131869652135577801738352337842661127526010440.00%31313656.55%6644146943.84%658155842.23%545118346.07%158788817087381422688
1282342903268228229-141151303136113112141191600132115117-2682283575851129106841624326209288241162748906411160130212942.72%2028657.43%1815170547.80%813167148.65%568116948.59%160984518477801541778
13823528072552332102341201204221124101234115160303410910907023337961234389885182345613894789852566844495147330112641.86%23510455.74%1786154950.74%871178048.93%576114950.13%162782417737711595834
14823130042312222225-341141302237112125-13411717020051101001062222334556142887100152357575843894962492817669152428112444.13%31611463.92%5870167152.06%901176651.02%590112752.35%165784717767681569818
1582342306667239197424118110343210892164116120323513110526682393636021235791131723736287958741242431842440142528614249.65%2208959.55%4828159951.78%890169752.45%644118654.30%169088217557331565838
16824722024433042109441221102222159105544125110022114510540943044857893645120133132497634933905472451807562131032218457.14%27710960.65%3826159051.95%859174449.25%689128653.58%171495617957321460756
1782402604345272223494124904121148925641161700224124131-780272444716123196137122549675877955792566863574138130215751.99%26510460.75%5822165649.64%822166149.49%662125552.75%168393018247431468749
1882372805282271201704121130311214094464116150217013110724742714126830136119103192243501881832662540826529143131315950.80%26210161.45%6865151257.21%904172852.31%683121356.31%163482918047331547838
19823325062124244208364117140315111198134116110317313311023662443766201130100963022355828547441162780932424141329214047.95%2118858.29%3751154948.48%809167248.39%599119250.25%160282418557591555810
207842190144827420965392010003331411023939229011151331072684274441715263510612872397561860943772487789440138030114849.17%2208959.55%5788154650.97%813163649.69%594117950.38%159287117557081401720
Total Saison Régulière81236226703834545725022167335406183125024222527126510512144061791420141229301237111612172425023950645215283389971075152235635966866684988412539884685205142132960141347.74%2521102059.54%3979951584650.45%83401691349.31%61501193951.51%163998703178987469151257833
Séries
12734000001517-23120000068-24220000099061524390032911764066646243754413319736.84%22959.09%05913543.70%7917345.66%459447.87%132601747414573
1351400000813-52020000026-43120000067-1281321001430141424455013641369813538.46%18855.56%0449546.32%5611449.12%256240.32%96481015210147
15514000001218-630300000614-8211000006422121931001380157474664020061517016850.00%231152.17%0329732.99%6314842.57%338439.29%9752119478642
16514000001218-630300000614-8211000006422121931001380157474664020061517016850.00%231152.17%0329732.99%6314842.57%338439.29%9752119478642
172116500000554213954000001922-312111000003620163255921470251926550110417719426597188106349602745.00%532356.60%216733749.55%20044445.05%13226250.38%398183452221463234
187340000011110321000006424130000057-2611193000235118125735825243813812120630.00%19573.68%06614645.21%8018643.01%337842.31%135621677314777
194040000016-52020000014-32020000002-2011200010045149220963920705120.00%10460.00%0224252.38%317243.06%162857.14%682573429849
20514000001115-4312000008802020000037-421117280032601443242700173504810217635.29%24962.50%0389141.76%6612552.80%306844.12%9344109519749
Total Séries59263300000125140-1528919000005480-263117140000071601152125204329021637657150235150359157188859639410131666840.96%1928058.33%2460104044.23%638141045.25%34776045.66%111953013186101226616