PV Sharapovas

GP: 7 | W: 5 | L: 2 | OTL: 0 | P: 10
GF: 38 | GA: 15 | PP%: 11.11% | PK%: 80.77%
DG: Justin Guitard | Morale : 98 | Moyenne d'Équipe : 62
Prochain matchs #96 vs IOWA Wild
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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
1Anthony Beauvillier0X100.006835806869829467726569606859538097690
2Tomas Nosek0XXX100.006835746685808165766565726556523796690
3Miikka Salomaki0XX100.007635756473746863586362606356526897650
4Michael Chaput0X100.006435696780626667726563636457525497650
5Charles Hudon0X100.008235746470786663666264606454515697650
6Phil Varone0X100.005835716669648265726464576454514597640
7Trevor Moore (R)0X100.005435706967586269506967546751504397620
8Ryan MacInnis0X100.005942746079587654675454605450504497600
9Keegan Kolesar0X100.006289526886505068506262506250504497600
10Ryan Gropp0X100.005489696779505067505757505750504497580
11Zach Nastasiuk0X100.005589716281485062505555525550504397570
12Justin Kirkland0XX100.005289606680505066505555505550504497570
13MacKenzie Weegar0X100.007953676674807765306362756955524795680
14Dennis Cholowski0X100.005735756676719066306270606952518294670
15Yannick Weber0X100.006735746372717563306158686668565197660
16Victor Mete0X100.005835806366789163306253706355516297650
17Cale Fleury (R)0X100.005389686578505065305146505650504497550
Rayé
1Guillaume Brisebois0X100.005135705975515459304945535550506794540
2Gabriel Carlsson0X100.005835705788465057304641505151507993530
MOYENNE D'ÉQUIPE100.00625171657663676450595959615451549662
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
1Christopher Gibson100.00756881827474757474746951636196660
2Zachary Fucale100.00656171786669666666666350584497590
Rayé
MOYENNE D'ÉQUIPE100.0070657680707271707070665161539763
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Steve Yzerman60606060696964CAN552150,000$


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
1Tomas NosekPV Sharapovas (DET)C/LW/RW696151960121347133219.15%214724.58000270001140069.47%13100022.0300000210
2MacKenzie WeegarPV Sharapovas (DET)D73912161002321851716.67%516022.9010149000018010.00%000001.5000000010
3Phil VaronePV Sharapovas (DET)C7651110209726132223.08%010415.0000000000030073.12%9300012.1000000200
4Dennis CholowskiPV Sharapovas (DET)D629111400461431214.29%513923.2001115000018000.00%000001.5800000002
5Miikka SalomakiPV Sharapovas (DET)LW/RW7099142089226110.00%212117.32011180110160044.00%2500001.4800000000
6Anthony BeauvillierPV Sharapovas (DET)LW7279112061379205.41%112818.29000580001241042.86%700001.4100000002
7Ryan GroppPV Sharapovas (DET)LW7279109563218129.52%010515.0000000000070050.00%1000001.7100100010
8Yannick WeberPV Sharapovas (DET)D715676075102910.00%414520.7700038000121100.00%000000.8300000101
9Michael ChaputPV Sharapovas (DET)C7224040883011316.67%112718.24000281011140068.18%11000000.6300000000
10Zach NastasiukPV Sharapovas (DET)RW713410207519375.26%09814.1100000000000012.50%800000.8100000000
11Justin KirklandPV Sharapovas (DET)C/LW740460023162825.00%0608.65000000000010100.00%500001.3200000010
12Ryan MacInnisPV Sharapovas (DET)C713464024106610.00%0628.9100000000000067.21%6100001.2800000000
13Victor MetePV Sharapovas (DET)D722450056134515.38%414320.4900047011121100.00%000000.5600000000
14Cale FleuryPV Sharapovas (DET)D7134560233101310.00%611416.390000000005000.00%000000.7000000000
15Trevor MoorePV Sharapovas (DET)LW7202-30033225309.09%211115.9500008000001066.67%900000.3600000000
16Guillaume BriseboisPV Sharapovas (DET)D1000-100100000.00%21616.420000000001000.00%000000.0000000000
17Keegan KolesarPV Sharapovas (DET)RW7000-340104229240.00%011115.8800038000000050.00%200000.0000000000
Stats d'équipe Total ou en Moyenne11138701081265751368233710024911.28%34189817.10123257912351675166.59%46100031.1400100545
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
1Christopher GibsonPV Sharapovas (DET)65100.8911.673600110920000.000060000
2Zachary FucalePV Sharapovas (DET)10100.8785.0060205410000.000017000
Stats d'équipe Total ou en Moyenne75200.8872.1442021151330000.000077000


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Anthony BeauvillierPV Sharapovas (DET)LW221997-06-08 15:11:08No83 Kg180 CMNoNoNo1Pro & Farm1,000,000$909,909$1,000,000$909,909$0$0$NoLien
Cale FleuryPV Sharapovas (DET)D201998-10-19Yes91 Kg185 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Charles HudonPV Sharapovas (DET)LW251994-06-23No89 Kg178 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Christopher GibsonPV Sharapovas (DET)G261992-12-27No94 Kg188 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Dennis CholowskiPV Sharapovas (DET)D211998-02-15No89 Kg185 CMNoNoNo4Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$750,000$Lien
Gabriel CarlssonPV Sharapovas (DET)D221997-01-02No87 Kg196 CMNoNoNo1Pro & Farm1,000,000$909,909$1,000,000$909,909$0$0$NoLien
Guillaume BriseboisPV Sharapovas (DET)D221997-07-21No80 Kg188 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Justin KirklandPV Sharapovas (DET)C/LW231996-08-02No83 Kg191 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Keegan KolesarPV Sharapovas (DET)RW221997-04-08No103 Kg188 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
MacKenzie WeegarPV Sharapovas (DET)D251994-01-07No91 Kg183 CMNoNoNo3Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$Lien
Michael ChaputPV Sharapovas (DET)C271992-04-09No90 Kg188 CMNoNoNo5Pro & Farm800,000$727,927$800,000$727,927$0$0$No800,000$800,000$800,000$800,000$Lien
Miikka SalomakiPV Sharapovas (DET)LW/RW261993-03-09No92 Kg180 CMNoNoNo4Pro & Farm950,000$864,414$950,000$864,414$0$0$No950,000$950,000$950,000$Lien
Phil VaronePV Sharapovas (DET)C281990-12-04No88 Kg178 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Ryan GroppPV Sharapovas (DET)LW221996-09-16No89 Kg188 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Ryan MacInnisPV Sharapovas (DET)C231996-02-14No90 Kg193 CMNoNoNo5Pro & Farm850,000$773,423$850,000$773,423$0$0$No850,000$850,000$850,000$850,000$Lien
Tomas NosekPV Sharapovas (DET)C/LW/RW261992-09-01No95 Kg191 CMNoNoNo6Pro & Farm1,250,000$1,137,387$1,250,000$1,137,387$0$0$No1,250,000$1,250,000$1,250,000$1,250,000$1,250,000$Lien
Trevor MoorePV Sharapovas (DET)LW241995-03-21Yes83 Kg178 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Victor MetePV Sharapovas (DET)D211998-06-07No83 Kg175 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Yannick WeberPV Sharapovas (DET)D301988-09-23No91 Kg180 CMNoNoNo5Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$750,000$750,000$Lien
Zach NastasiukPV Sharapovas (DET)RW241995-03-30No92 Kg188 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Zachary FucalePV Sharapovas (DET)G241995-05-28No85 Kg188 CMNoNoNo5Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$750,000$750,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2123.9589 Kg185 CM2.57814,286$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Anthony BeauvillierTomas NosekMiikka Salomaki31113
2Trevor MooreMichael ChaputKeegan Kolesar26113
3Ryan GroppPhil VaroneZach Nastasiuk23122
4Justin KirklandRyan MacInnisTomas Nosek20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1MacKenzie WeegarDennis Cholowski31122
2Yannick WeberVictor Mete26122
3Cale Fleury23122
4MacKenzie WeegarDennis Cholowski20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Anthony BeauvillierTomas NosekMiikka Salomaki55005
2Trevor MooreMichael ChaputKeegan Kolesar45005
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1MacKenzie WeegarDennis Cholowski55122
2Yannick WeberVictor Mete45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Tomas NosekAnthony Beauvillier55140
2Miikka SalomakiMichael Chaput45140
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1MacKenzie WeegarDennis Cholowski55140
2Yannick WeberVictor Mete45140
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Tomas Nosek55050MacKenzie WeegarDennis Cholowski55050
2Anthony Beauvillier45050Yannick WeberVictor Mete45050
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Tomas NosekAnthony Beauvillier55122
2Miikka SalomakiMichael Chaput45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1MacKenzie WeegarDennis Cholowski55122
2Yannick WeberVictor Mete45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Anthony BeauvillierTomas NosekMiikka SalomakiMacKenzie WeegarDennis Cholowski
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Anthony BeauvillierTomas NosekMiikka SalomakiMacKenzie WeegarDennis Cholowski
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Phil Varone, Ryan MacInnis, Ryan GroppPhil Varone, Ryan MacInnisRyan Gropp
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Cale Fleury, Yannick WeberCale Fleury, Yannick Weber
Tirs de Pénalité
Tomas Nosek, Anthony Beauvillier, Miikka Salomaki, Michael Chaput, Phil Varone
Gardien
#1 : Christopher Gibson, #2 : Zachary Fucale
Lignes d'Attaque Perso. en Prol.
Tomas Nosek, Anthony Beauvillier, Miikka Salomaki, Michael Chaput, Phil Varone, Trevor Moore, Trevor Moore, Keegan Kolesar, Ryan MacInnis, Ryan Gropp, Justin Kirkland
Lignes de Défense Perso. en Prol.
MacKenzie Weegar, Dennis Cholowski, Yannick Weber, Victor Mete,


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
1BELLEVILLE Senators220000001411300000000000220000001411341.000142640011910811551031161153136050100.00%000.00%017224271.07%7215446.75%6410163.37%237191111347241
2PROVIDENCE Bruins10001000321100010003210000000000021.00036900191081241031161153226818300.00%4175.00%017224271.07%7215446.75%6410163.37%237191111347241
3STOCKTON Flames2020000039-61010000015-41010000024-200.00035800191081451031161153681433364125.00%14378.57%017224271.07%7215446.75%6410163.37%237191111347241
4Syracruse Crunch11000000725110000007250000000000021.00071320001910813410311611532691621100.00%7185.71%117224271.07%7215446.75%6410163.37%237191111347241
Total742010003815233110100011924310000027621100.714387010801191081337103116115313337591409111.11%26580.77%117224271.07%7215446.75%6410163.37%237191111347241
6WILKIES-BARRIE Penguins110000001111000000000000110000001111021.0001120310019108179103116115342215000.00%10100.00%017224271.07%7215446.75%6410163.37%237191111347241
_Since Last GM Reset742010003815233110100011924310000027621100.714387010801191081337103116115313337591409111.11%26580.77%117224271.07%7215446.75%6410163.37%237191111347241
_Vs Conference6420000035132221100000871431000002762180.66735649901191081313103116115311131511226116.67%22481.82%117224271.07%7215446.75%6410163.37%237191111347241
_Vs Division130000001111000000000000130000001111063.0001120310019108179103116115342215000.00%10100.00%017224271.07%7215446.75%6410163.37%237191111347241

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
710L13870108337133375914001
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
74210003815
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3111000119
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4310000276
Derniers 10 Matchs
WLOTWOTL SOWSOL
520000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
9111.11%26580.77%1
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
1031161153191081
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
17224271.07%7215446.75%6410163.37%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
237191111347241


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 - 2020-01-1512PROVIDENCE Bruins2PV Sharapovas3WXSommaire du Match
2 - 2020-01-1622PV Sharapovas2STOCKTON Flames4LSommaire du Match
3 - 2020-01-1727PV Sharapovas8BELLEVILLE Senators1WSommaire du Match
4 - 2020-01-1846Syracruse Crunch2PV Sharapovas7WSommaire du Match
5 - 2020-01-1959PV Sharapovas6BELLEVILLE Senators0WSommaire du Match
7 - 2020-01-2170PV Sharapovas11WILKIES-BARRIE Penguins1WSommaire du Match
9 - 2020-01-2380STOCKTON Flames5PV Sharapovas1LSommaire du Match
11 - 2020-01-2596IOWA Wild-PV Sharapovas-
13 - 2020-01-27107PV Sharapovas-STOCKTON Flames-
15 - 2020-01-29128LEHIGH VALLEY Phantoms-PV Sharapovas-
17 - 2020-01-31136CORNWALL Aces-PV Sharapovas-
20 - 2020-02-03157PV Sharapovas-HOLLYWOOD Oscar-
21 - 2020-02-04162PV Sharapovas-BELLEVILLE Senators-
22 - 2020-02-05174Manitoba Moose-PV Sharapovas-
23 - 2020-02-06188PV Sharapovas-Syracruse Crunch-
24 - 2020-02-07198PV Sharapovas-STOCKTON Flames-
25 - 2020-02-08208WILKIES-BARRIE Penguins-PV Sharapovas-
27 - 2020-02-10227BRIDGEPORT Sound Tigers-PV Sharapovas-
28 - 2020-02-11235PV Sharapovas-VICTORIAVILLE Tigres-
29 - 2020-02-12250BELLEVILLE Senators-PV Sharapovas-
31 - 2020-02-14266PV Sharapovas-WILKIES-BARRIE Penguins-
32 - 2020-02-15271PV Sharapovas-BELLEVILLE Senators-
33 - 2020-02-16286HOLLYWOOD Oscar-PV Sharapovas-
34 - 2020-02-17304UTICA Comets-PV Sharapovas-
36 - 2020-02-19317PV Sharapovas-BRIDGEPORT Sound Tigers-
37 - 2020-02-20328Syracruse Crunch-PV Sharapovas-
38 - 2020-02-21344HOLLYWOOD Oscar-PV Sharapovas-
39 - 2020-02-22347PV Sharapovas-Syracruse Crunch-
41 - 2020-02-24367PV Sharapovas-MONT-LAURIER Sommet-
42 - 2020-02-25379ROCKFORD IceHogs-PV Sharapovas-
44 - 2020-02-27395PV Sharapovas-LAVAL Rockets-
45 - 2020-02-28408PV Sharapovas-Marlies de Toronto-
46 - 2020-02-29420HERSEY Bears-PV Sharapovas-
47 - 2020-03-01433PV Sharapovas-HERSEY Bears-
48 - 2020-03-02444Manitoba Moose-PV Sharapovas-
49 - 2020-03-03458IOWA Wild-PV Sharapovas-
52 - 2020-03-06475TUSCON Roadrunners-PV Sharapovas-
53 - 2020-03-07487PV Sharapovas-SAN DIEGO Gulls-
54 - 2020-03-08499PV Sharapovas-BROOKLYN Wolfpack-
55 - 2020-03-09510PV Sharapovas-ROCKFORD IceHogs-
56 - 2020-03-10519BELLEVILLE Senators-PV Sharapovas-
58 - 2020-03-12537PV Sharapovas-PROVIDENCE Bruins-
59 - 2020-03-13546TUSCON Roadrunners-PV Sharapovas-
61 - 2020-03-15563LAVAL Rockets-PV Sharapovas-
62 - 2020-03-16582PV Sharapovas-Manitoba Moose-
63 - 2020-03-17589PV Sharapovas-CORNWALL Aces-
64 - 2020-03-18600WILKIES-BARRIE Penguins-PV Sharapovas-
65 - 2020-03-19614MONT-LAURIER Sommet-PV Sharapovas-
67 - 2020-03-21631PV Sharapovas-Manitoba Moose-
68 - 2020-03-22640PV Sharapovas-COLORADO Eagles-
69 - 2020-03-23653MILWAUKEE Admirals-PV Sharapovas-
70 - 2020-03-24670LEHIGH VALLEY Phantoms-PV Sharapovas-
71 - 2020-03-25685VICTORIAVILLE Tigres-PV Sharapovas-
73 - 2020-03-27697PV Sharapovas-Binghampton Devils-
74 - 2020-03-28711PV Sharapovas-CORNWALL Aces-
75 - 2020-03-29718CORNWALL Aces-PV Sharapovas-
76 - 2020-03-30736PV Sharapovas-VICTORIAVILLE Tigres-
77 - 2020-03-31749CHICAGO Wolves-PV Sharapovas-
78 - 2020-04-01762COLORADO Eagles-PV Sharapovas-
79 - 2020-04-02774PV Sharapovas-IOWA Wild-
81 - 2020-04-04791Syracruse Crunch-PV Sharapovas-
82 - 2020-04-05797PV Sharapovas-IOWA Wild-
83 - 2020-04-06816SAN DIEGO Gulls-PV Sharapovas-
85 - 2020-04-08827PV Sharapovas-Binghampton Devils-
86 - 2020-04-09840Binghampton Devils-PV Sharapovas-
87 - 2020-04-10854PV Sharapovas-MILWAUKEE Admirals-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
89 - 2020-04-12870STOCKTON Flames-PV Sharapovas-
90 - 2020-04-13881PV Sharapovas-HOLLYWOOD Oscar-
91 - 2020-04-14894Binghampton Devils-PV Sharapovas-
92 - 2020-04-15911PV Sharapovas-CHICAGO Wolves-
93 - 2020-04-16922VICTORIAVILLE Tigres-PV Sharapovas-
94 - 2020-04-17934PV Sharapovas-MONT-LAURIER Sommet-
95 - 2020-04-18946PV Sharapovas-LEHIGH VALLEY Phantoms-
96 - 2020-04-19955Marlies de Toronto-PV Sharapovas-
98 - 2020-04-21972STOCKTON Flames-PV Sharapovas-
99 - 2020-04-22984PV Sharapovas-TUSCON Roadrunners-
100 - 2020-04-23996BROOKLYN Wolfpack-PV Sharapovas-
101 - 2020-04-241001PV Sharapovas-STOCKTON Flames-
104 - 2020-04-271021BROOKLYN Wolfpack-PV Sharapovas-
107 - 2020-04-301044MONT-LAURIER Sommet-PV Sharapovas-
108 - 2020-05-011049PV Sharapovas-LEHIGH VALLEY Phantoms-
109 - 2020-05-021056PV Sharapovas-UTICA Comets-



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
38 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
166,984$ 1,710,000$ 1,710,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 153,465$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 101 16,757$ 1,692,457$




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
3374201000381523311010001192431000002762110387010801191081337103116115313337591409111.11%26580.77%117224271.07%7215446.75%6410163.37%237191111347241
Total Saison Régulière74201000381523311010001192431000002762110387010801191081337103116115313337591409111.11%26580.77%117224271.07%7215446.75%6410163.37%237191111347241
Séries
32171070000047407954000002822685300000191812047861330018121706271802152082444412220035860915.00%951089.47%246068267.45%32953761.27%15224462.30%486355370120210107
Total Séries171070000047407954000002822685300000191812047861330018121706271802152082444412220035860915.00%951089.47%246068267.45%32953761.27%15224462.30%486355370120210107