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Senators

GP: 49 | W: 35 | L: 11 | OTL: 3 | P: 73
GF: 235 | GA: 150 | PP%: 26.92% | PK%: 82.64%
DG: Kevin Brassard | Morale : 50 | Moyenne d'Équipe : 62
Prochain matchs #762 vs Americans
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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 SPÂgeContratSalaire
1Matt BeleskeyX100.006249856176788062555959636180720506303113,800,000$
2Matt PuempelXX100.00624589647882796257616163657367050630261675,000$
3Alex Barre-BouletX100.00514389675688916563626456676563050620222759,258$
4Kyle RauXX100.00563984636479806256616059637568050620261700,000$
5Michael BuntingXX100.00594884637276736158626059636965050620242737,500$
6Paul BittnerX100.00735187599085825855575660596764050620221863,333$
7Isac LundestromX100.00593886637279776274615759626163050610192925,000$
8Graham KnottX100.00674688568376785451535257566563050590221935,833$
9Manuel WiedererX100.00564389587277765753555659586764050590221736,667$
10Dylan CoghlanX100.00624590597887895830575760456362050610212715,556$
11Jordan SchmaltzX100.00624389618078725930585760517367050610261700,000$
12Keegan LoweX100.00635681577987895630555154467377050600261675,000$
13Jack DoughertyX100.00644985578086885530545356456764050590231650,000$
14Patrick SieloffX100.00655480567881835430535257457166050590251700,000$
Rayé
MOYENNE D'ÉQUIPE100.0062468660768181594858575956696605061
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
1Laurent Brossoit100.0081858384807981807981807377050690
2Spencer Martin100.0068777583676668676668676973050620
Rayé
MOYENNE D'ÉQUIPE100.007581798474737574737574717505066
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Matt PuempelSenators (OTT)LW/RW4845388344220761053496620812.89%16109122.73831148107000054348.89%9000031.52040001133
2Kyle RauSenators (OTT)C/LW482442664120721381864813612.90%1497820.38214162110711281353050.09%157900111.3513000334
3Alex Barre-BouletSenators (OTT)C48233962164039162252611949.13%1893719.52491332970000632250.60%125700011.3200000331
4Matt BeleskeySenators (OTT)LW48213455411558999212551659.91%1796820.19511162310711271283044.33%9700001.1424100137
5Michael BuntingSenators (OTT)LW/RW482131521610070912105316610.00%1792619.3033625960001574052.94%6800011.1224000432
6Jordan SchmaltzSenators (OTT)D48113647452201035497327311.34%81116424.2653839102000096100.00%000000.8100000150
7Dylan CoghlanSenators (OTT)D486354144340102579934766.06%76115924.1525745102011092300.00%000000.7100000131
8MacKenzie EntwistleSenateursRW461624401915511054178451288.99%1081817.793692894000002043.06%7200010.9800001233
9Isac LundestromSenators (OTT)C48162238186046120172601139.30%1268914.3600000000002358.53%87300001.1000000014
10Keegan LoweSenators (OTT)D487303725440141428720428.05%8398320.49291131102000093100.00%000000.7500000030
11Manuel WiedererSenators (OTT)RW48171936194024691493911911.41%1569014.3900000000004143.55%6200101.0400000221
12Cody McLeodSenateursLW289142317235784489236410.11%740714.54000000000122135.14%3700011.1300100220
13Patrick SieloffSenators (OTT)D48117181337579293820332.63%5573115.240000000002000.00%000000.4900001000
14Sebastien AhoSenateursD1841115960152625111616.00%3136720.431341138000039110.00%000000.8200000000
15Jack DoughertySenators (OTT)D4841014123007721439279.30%4278016.2600001011138000.00%000000.3600000001
16Paul BittnerSenators (OTT)LW486511621532177314348.22%32886.0100000000001044.44%1800000.7600000001
17Graham KnottSenators (OTT)C48191062019253013283.33%52875.9900000000000047.33%39300000.7000000000
Stats d'équipe Total ou en Moyenne76423241664839129725117211532289603162210.14%5021326817.37356610130395924617766331151.17%454600280.98515202303428
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
1Laurent BrossoitSenators (OTT)48351030.9212.7828116313016520220.66715480435
2Spencer MartinSenators (OTT)20000.9472.0588003570000.0000048000
Stats d'équipe Total ou en Moyenne50351030.9222.7529006313317090220.667154848435


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Alex Barre-BouletSenators (OTT)C221997-05-21No170 Lbs5 ft1NoNoNo2Pro & Farm759,258$0$0$No759,258$Lien / Lien NHL
Dylan CoghlanSenators (OTT)D211998-02-19No190 Lbs6 ft2NoNoNo2Pro & Farm715,556$0$0$No715,556$Lien / Lien NHL
Graham KnottSenators (OTT)C221997-01-13No199 Lbs6 ft3NoNoNo1Pro & Farm935,833$0$0$NoLien / Lien NHL
Isac LundestromSenators (OTT)C191999-11-06No187 Lbs6 ft0NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Jack DoughertySenators (OTT)D231996-05-25No196 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Jordan SchmaltzSenators (OTT)D261993-10-08No196 Lbs6 ft2NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Keegan LoweSenators (OTT)D261993-03-29No191 Lbs6 ft2NoNoNo1Pro & Farm675,000$0$0$NoLien / Lien NHL
Kyle RauSenators (OTT)C/LW261992-10-24No176 Lbs5 ft8NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Laurent BrossoitSenators (OTT)G261993-03-23No204 Lbs6 ft3NoNoNo1Pro & Farm1,225,000$0$0$NoLien / Lien NHL
Manuel WiedererSenators (OTT)RW221996-11-21No175 Lbs6 ft1NoNoNo1Pro & Farm736,667$0$0$NoLien / Lien NHL
Matt BeleskeySenators (OTT)LW311988-06-07No207 Lbs6 ft0NoNoNo1Pro & Farm3,800,000$0$0$NoLien / Lien NHL
Matt PuempelSenators (OTT)LW/RW261993-01-24No201 Lbs6 ft1NoNoNo1Pro & Farm675,000$0$0$NoLien / Lien NHL
Michael BuntingSenators (OTT)LW/RW241995-09-17No197 Lbs5 ft11NoNoNo2Pro & Farm737,500$0$0$No737,500$Lien / Lien NHL
Patrick SieloffSenators (OTT)D251994-05-15No205 Lbs6 ft1NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Paul BittnerSenators (OTT)LW221996-11-04No205 Lbs6 ft5NoNoNo1Pro & Farm863,333$0$0$NoLien
Spencer MartinSenators (OTT)G241995-06-08No200 Lbs6 ft3NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1624.06194 Lbs6 ft11.25968,634$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt BeleskeyKyle RauMatt Puempel35104
2Michael BuntingAlex Barre-Boulet27113
3Isac LundestromManuel Wiederer23131
4Paul BittnerGraham KnottMatt Puempel15140
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan CoghlanJordan Schmaltz35131
2Keegan Lowe26131
3Jack DoughertyPatrick Sieloff24131
4Dylan CoghlanJordan Schmaltz15131
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt BeleskeyKyle RauMatt Puempel60104
2Michael BuntingAlex Barre-Boulet40104
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan CoghlanJordan Schmaltz60104
2Keegan Lowe40104
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kyle RauMatt Beleskey60140
2Alex Barre-BouletMichael Bunting40140
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan CoghlanJordan Schmaltz60140
2Keegan Lowe40140
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Kyle Rau60140Dylan CoghlanJordan Schmaltz60140
2Alex Barre-Boulet40140Keegan Lowe40140
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kyle RauMatt Beleskey60122
2Alex Barre-BouletMichael Bunting40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan CoghlanJordan Schmaltz60122
2Keegan Lowe40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt BeleskeyKyle RauMatt PuempelDylan CoghlanJordan Schmaltz
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt BeleskeyKyle RauMatt PuempelDylan CoghlanJordan Schmaltz
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Paul Bittner, Alex Barre-Boulet, Paul Bittner
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Keegan Lowe, Jack Dougherty, Patrick SieloffKeegan LoweKeegan Lowe, Jack Dougherty
Tirs de Pénalité
Matt Puempel, Matt Beleskey, Michael Bunting, Kyle Rau,
Gardien
#1 : Laurent Brossoit, #2 : Spencer Martin


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
1Admirals11000000734110000007340000000000021.00071219001037060557731724855253994343133.33%20100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
2Americans11000000927110000009270000000000021.00091524001037060552731724855254318103222100.00%5180.00%11068204552.22%863176748.84%41784449.41%12348921118332611312
3Barracuda11000000615000000000001100000061521.0006111700103706052773172485525346413100.00%20100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
4Bears2110000011651010000035-21100000081720.500111829001037060511973172485525631575011100.00%10100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
5Bruins430001001651121000100651220000001001070.8751627430210370605163731724855251444918911516.67%90100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
6Checkers21100000990211000009900000000000020.5009142300103706051047317248552553148496116.67%4250.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
7Comets22000000183151100000010191100000082641.00018335100103706051737317248552544154542150.00%20100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
8Condors1100000010370000000000011000000103721.00010182800103706058973172485525295219100.00%000.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
9Crunch312000001114-32020000059-41100000065120.3331119300010370605114731724855251405524649444.44%12191.67%01068204552.22%863176748.84%41784449.41%12348921118332611312
10Devils21000010963110000005321000001043141.0009162500103706058973172485525923214545120.00%7185.71%01068204552.22%863176748.84%41784449.41%12348921118332611312
11Eagles2200000013310110000005321100000080841.00013263901103706059373172485525711510533266.67%3166.67%01068204552.22%863176748.84%41784449.41%12348921118332611312
12Griffins2020000058-32020000058-30000000000000.000591410103706059273172485525642519617228.57%7271.43%01068204552.22%863176748.84%41784449.41%12348921118332611312
13Heat32100000151141010000015-422000000146840.6671528430010370605180731724855251163015756350.00%4250.00%11068204552.22%863176748.84%41784449.41%12348921118332611312
14IceHogs1010000035-21010000035-20000000000000.000358001037060521731724855255391025100.00%5260.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
15Marlies320000101394100000104312200000096361.000132437001037060512673172485525109442280500.00%10190.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
16Monsters32000001171251100000054121000001128450.8331730470010370605139731724855258629185412650.00%7271.43%01068204552.22%863176748.84%41784449.41%12348921118332611312
17Moose2200000014681100000010371100000043141.0001423370010370605118731724855256222862100.00%4250.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
18Penguins11000000954000000000001100000095421.000918270010370605597317248552545100203266.67%000.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
19Phantoms1010000013-2000000000001010000013-200.0001231010370605477317248552543111230300.00%5180.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
20Rampage11000000422000000000001100000042221.00048120010370605447317248552543126264125.00%30100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
21Reign11000000431110000004310000000000021.0004610001037060535731724855253964244250.00%20100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
22Roadrunners11000000211110000002110000000000021.00023500103706054073172485525376616400.00%20100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
23Rocket211000005411010000023-11100000031220.50059140010370605577317248552564173848300.00%9188.89%01068204552.22%863176748.84%41784449.41%12348921118332611312
24Sound Tigers21000001770000000000002100000177030.7507142100103706057273172485525742116557114.29%50100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
25Thunderbirds22000000936110000005231100000041341.0009172600103706058573172485525681812499333.33%40100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
Total493311001222351508524121000110101901125211000121346074730.7452354186532310370605232073172485525179254230711931303526.92%1212182.64%21068204552.22%863176748.84%41784449.41%12348921118332611312
26Wild11000000413000000000001100000041321.0004610001037060540731724855253074264125.00%20100.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
27Wolf Pack10100000113-1210100000113-120000000000000.000123001037060529731724855258134414200.00%110.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
28Wolves11000000321000000000001100000032121.00035800103706055673172485525268815700.00%4175.00%01068204552.22%863176748.84%41784449.41%12348921118332611312
_Since Last GM Reset493311001222351508524121000110101901125211000121346074730.7452354186532310370605232073172485525179254230711931303526.92%1212182.64%21068204552.22%863176748.84%41784449.41%12348921118332611312
_Vs Conference28177001211288939146600110595541411100011693435400.71412822835612103706051289731724855251063353189690721723.61%74987.84%11068204552.22%863176748.84%41784449.41%12348921118332611312
_Vs Division1783000206845231033000103632475000010321319200.58868120188121037060568973172485525632226143425501224.00%56689.29%11068204552.22%863176748.84%41784449.41%12348921118332611312

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4973W123541865323201792542307119323
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4933110122235150
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
241210011010190
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
25211001213460
Derniers 10 Matchs
WLOTWOTL SOWSOL
720001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1303526.92%1212182.64%2
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
7317248552510370605
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
1068204552.22%863176748.84%41784449.41%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12348921118332611312


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 - 2020-10-067Wolf Pack13Senators1LSommaire du Match
4 - 2020-10-0830Senators4Bruins0WSommaire du Match
6 - 2020-10-1039Crunch6Senators3LSommaire du Match
8 - 2020-10-1257Senators6Bruins0WSommaire du Match
10 - 2020-10-1471IceHogs5Senators3LSommaire du Match
12 - 2020-10-1684Senators3Rocket1WSommaire du Match
14 - 2020-10-18101Roadrunners1Senators2WSommaire du Match
16 - 2020-10-20115Senators3Sound Tigers2WSommaire du Match
18 - 2020-10-22126Senators4Marlies3WSommaire du Match
20 - 2020-10-24139Senators4Thunderbirds1WSommaire du Match
21 - 2020-10-25152Checkers5Senators6WSommaire du Match
24 - 2020-10-28169Senators8Bears1WSommaire du Match
25 - 2020-10-29179Senators1Phantoms3LSommaire du Match
27 - 2020-10-31189Americans2Senators9WSommaire du Match
30 - 2020-11-03211Griffins5Senators3LSommaire du Match
31 - 2020-11-04223Senators9Heat5WSommaire du Match
34 - 2020-11-07244Bruins4Senators3LXSommaire du Match
35 - 2020-11-08254Senators4Monsters5LXXSommaire du Match
38 - 2020-11-11272Moose3Senators10WSommaire du Match
40 - 2020-11-13290Senators3Wolves2WSommaire du Match
41 - 2020-11-14299Senators6Crunch5WSommaire du Match
43 - 2020-11-16310Reign3Senators4WSommaire du Match
46 - 2020-11-19329Senators4Wild1WSommaire du Match
47 - 2020-11-20340Admirals3Senators7WSommaire du Match
50 - 2020-11-23365Eagles3Senators5WSommaire du Match
52 - 2020-11-25375Senators8Eagles0WSommaire du Match
54 - 2020-11-27394Marlies3Senators4WXXSommaire du Match
57 - 2020-11-30414Senators4Moose3WSommaire du Match
58 - 2020-12-01427Rocket3Senators2LSommaire du Match
61 - 2020-12-04447Senators4Devils3WXXSommaire du Match
62 - 2020-12-05458Monsters4Senators5WSommaire du Match
66 - 2020-12-09483Heat5Senators1LSommaire du Match
68 - 2020-12-11496Senators10Condors3WSommaire du Match
70 - 2020-12-13511Senators8Comets2WSommaire du Match
71 - 2020-12-14520Bears5Senators3LSommaire du Match
74 - 2020-12-17542Griffins3Senators2LSommaire du Match
76 - 2020-12-19554Senators9Penguins5WSommaire du Match
79 - 2020-12-22577Thunderbirds2Senators5WSommaire du Match
81 - 2020-12-24587Senators8Monsters3WSommaire du Match
83 - 2020-12-26600Senators4Sound Tigers5LXXSommaire du Match
84 - 2020-12-27615Checkers4Senators3LSommaire du Match
87 - 2020-12-30631Senators6Barracuda1WSommaire du Match
88 - 2020-12-31644Bruins1Senators3WSommaire du Match
91 - 2021-01-03660Senators4Rampage2WSommaire du Match
92 - 2021-01-04674Devils3Senators5WSommaire du Match
96 - 2021-01-08700Comets1Senators10WSommaire du Match
99 - 2021-01-11718Senators5Marlies3WSommaire du Match
101 - 2021-01-13731Crunch3Senators2LSommaire du Match
102 - 2021-01-14746Senators5Heat1WSommaire du Match
104 - 2021-01-16762Americans-Senators-
107 - 2021-01-19775Senators-Rocket-
109 - 2021-01-21788Senators-Reign-
111 - 2021-01-23800Penguins-Senators-
113 - 2021-01-25816Senators-Bears-
114 - 2021-01-26829Senators-Americans-
116 - 2021-01-28835Stars-Senators-
119 - 2021-01-31857Senators-Gulls-
120 - 2021-02-01865Condors-Senators-
123 - 2021-02-04883Senators-Phantoms-
125 - 2021-02-06896Wild-Senators-
127 - 2021-02-08912Senators-Stars-
129 - 2021-02-10924Phantoms-Senators-
132 - 2021-02-13948Senators-IceHogs-
134 - 2021-02-15957Roadrunners-Senators-
136 - 2021-02-17972Senators-Thunderbirds-
138 - 2021-02-19986Wolves-Senators-
139 - 2021-02-201002Senators-Roadrunners-
142 - 2021-02-231020Senators-Checkers-
143 - 2021-02-241028Sound Tigers-Senators-
146 - 2021-02-271049Gulls-Senators-
148 - 2021-03-011064Senators-Bruins-
150 - 2021-03-031081Wolf Pack-Senators-
153 - 2021-03-061100Senators-Wolf Pack-
155 - 2021-03-081114Wolf Pack-Senators-
158 - 2021-03-111137Rampage-Senators-
160 - 2021-03-131152Senators-Admirals-
162 - 2021-03-151169Penguins-Senators-
167 - 2021-03-201197IceHogs-Senators-
169 - 2021-03-221207Senators-Griffins-
173 - 2021-03-261227Barracuda-Senators-
174 - 2021-03-271234Senators-Wolf Pack-
180 - 2021-04-021266Devils-Senators-



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
17 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
954,706$ 1,549,815$ 1,132,232$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 954,706$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 80 8,515$ 681,200$




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
2824325024442862345241249001431431162741191602301143118258628649878436101101789265384485592356258772992215013467321.10%3716781.94%61454273553.16%1386272850.81%652131349.66%1986136019246191065530
382522301132265166994126120011113783544126110102112883451042654597240109384846304610131046972302220662104116533667520.49%4176384.89%61982315362.86%1588275657.62%723119360.60%2171152317445901033539
48245200117826618977412211001521318942412390102613510035902664827481910295611530049681055937992226716150519866158814.31%6039085.07%101837335354.79%1646293956.01%713126056.59%2121143818226501059542
582542102041318172146412980102116977924125130102014995541083185608780131141138511321210171068111033219164858020832214520.36%2604283.85%21864305161.09%1543259159.55%743128557.82%2222162717145441009530
682541404244397199198413050211219780117412490213220011981108397718111501016612010314419113591361142778238064852319892766122.10%2414382.16%22250352763.79%1518254659.62%827135760.94%240518051586528987528
782333302527297291641131802215133150-1741201500312164141236629748578241122977483550115311731180784140122741720921873317.65%1853879.46%11461309047.28%1656389842.48%661137648.04%175012512270570960449
88287300100239644-4054153600000123308-1854133700100116336-220162394026410012470450306610321010102405769162025418471491610.74%1094459.63%0906245236.95%1101332333.13%534156834.06%12558642764562900365
88287300100239644-4054153600000123308-1854133700100116336-220162394026410012470450306610321010102405769162025418471491610.74%1094459.63%0906245236.95%1101332333.13%534156834.06%12558642764562900365
9493311001222351508524121000110101901125211000121346074732354186532310370605232073172485525179254230711931303526.92%1212182.64%21068204552.22%863176748.84%41784449.41%12348921118332611312
Total Saison Régulière70533029301216262825422689-147352166145057151412571301-44353164148079111412851388-103667254244246966105210498206356828108914993029452399290748412580316191243944218.12%241645281.29%29137282585853.09%124022587147.94%58041176449.34%164031162717710496385274163
Séries
2514000001319-62110000088030300000511-62132538004531159445257617347308534411.76%12558.33%07116443.29%6115140.40%399242.39%12083121386934
3624000001012-23120000068-2312000004404101727023430193636565017846751422015.00%37586.49%010421548.37%11621753.46%397850.00%13690145487737
4514000001014-43120000068-22020000046-22101929003340168544947181734810512846510.87%38392.11%010720851.44%10621649.07%387451.35%13288129467036
5231670000072591312930000041311011740000031283327212619801282616274023527022213685202177552991212.12%821482.93%242582051.83%44683253.61%16435745.94%570395539180299149
61385000003942-37520000020200633000001922-3163968107001214121497169174150440111484325461021.74%40782.50%031354957.01%24644555.28%11619958.29%3372392839216182
Total Séries52282400000144146-22717100000081756251114000006371-856144255399035052384175756561054141161045747112322453213.06%2093483.73%21020195652.15%975186152.39%39680049.50%12988961219406678340