HERSEY Bears

GP: 74 | W: 46 | L: 24 | OTL: 4 | P: 96
GF: 336 | GA: 137 | PP%: 19.13% | PK%: 83.19%
DG: Olivier Savoie | Morale : 94 | Moyenne d'Équipe : 63
Prochain matchs #981 vs TORONTO Marlies
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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
1Chandler Stephenson0X100.006235776575797764736463726456526379670
2Nick Paul0X100.006635686892576068556464576552516079640
3Lukas Sedlak0X100.007235716475736063736263666356524779640
4Anders Bjork (R)0X100.005335756672676065655858586152515579610
5Alexandre Fortin (R)0X100.005535736371596263575858575951504479600
6Kevin Roy (R)0X100.005035736163565161505454525451506079560
7Matt Grzelcyk (R)0X100.006344666664837966307170716855526179680
8Mike Reilly0X100.006535786576827064306261706856526079660
9Korbinian Holzer0X100.007935776387686163305754746456524779650
10Tim Heed (R)0X100.006035756868756868306860656953514879650
11Sami Niku (R)0X100.005535746573656565305653606351504979600
12Cody Goloubef0X100.005635586777525267305146565755526179570
13Sebastian D Aho0X100.005089647064505070305146515651505679550
Rayé
MOYENNE D'ÉQUIPE100.00604071657467636545605862625351557962
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
1Michael Hutchinson100.00767488837574767574757058675374670
2Anders Lindback100.00737380907578767575717160673979670
Rayé
MOYENNE D'ÉQUIPE100.0075748487757676757573715967467767
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dominique Ducharme65656565686880CAN461550,000$


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
1Chandler StephensonHERSEY Bears (WSH)C7463701331002009819351013332912.35%37194426.28114155418302279110461.38%227600051.37050001374
2Lukas SedlakHERSEY Bears (WSH)C7451521037728018617440812529512.50%23183524.814610361711125777163.19%143700051.1205000894
3Nick PaulHERSEY Bears (WSH)LW7437549162220120772987221312.42%17170223.017815341641014645056.77%60600041.0714000255
4Matt GrzelcykHERSEY Bears (WSH)D592455796918069802086812811.54%58149125.276511611421012732025.00%2400001.0600000243
5Mike ReillyHERSEY Bears (WSH)D742352755218043641976812911.68%62148720.1041115581670110765139.13%2300011.0100000603
6Tim HeedHERSEY Bears (WSH)D742154756014035681605212213.13%40147219.905914531370000661046.88%3200011.0200000302
7Anders BjorkHERSEY Bears (WSH)LW74274774501004482300832069.00%11174423.577512351780001394053.91%12800020.8522000235
8Korbinian HolzerHERSEY Bears (WSH)D74155166474201196615444919.74%55143719.423912541540001612150.00%800010.9200000147
9Alexandre FortinHERSEY Bears (WSH)LW742727547110039501986113913.64%13168122.72415291620001362155.63%14200020.6400000142
10Sami NikuHERSEY Bears (WSH)D7410435353140434794275710.64%44124516.831129400110110052.73%5500000.8500000101
11Cody GoloubefHERSEY Bears (WSH)D749394856180604077274811.69%35105914.320113230000262150.00%2600000.9100000131
12Kevin RoyHERSEY Bears (WSH)LW741120314260292913039948.46%10144319.5103361220000142045.29%17000000.4300000021
13Sebastian D AhoHERSEY Bears (WSH)D748152338100353163195212.70%1595612.921234550000341044.05%16800000.4800000000
14Michal KempnyWASHINGTON CapitalsD2022-120332260.00%24422.1202211100002000.00%000000.9000000000
15Ondrej KaseWASHINGTON CapitalsC/RW2000-200246160.00%05427.4500007000010061.29%3100000.0000000000
Stats d'équipe Total ou en Moyenne951326581907774232092510082805821191511.62%4221960120.61437712043717243582167843959.36%5126000210.93316000404138
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
1Michael HutchinsonHERSEY Bears (WSH)74462440.9121.81443962113415280610.83318740315
2Anders LindbackHERSEY Bears (WSH)10001.0000.0031000110000.0000074000
Stats d'équipe Total ou en Moyenne75462440.9131.80447162113415390610.833187474315


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
Alexandre FortinHERSEY Bears (WSH)LW221997-02-25Yes84 Kg183 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Anders BjorkHERSEY Bears (WSH)LW231996-08-05Yes86 Kg183 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Anders LindbackHERSEY Bears (WSH)G311988-05-03No98 Kg198 CMNoNoNo2Sans RestrictionPro & Farm650,000$0$0$NoLien
Chandler StephensonHERSEY Bears (WSH)C251994-04-22No92 Kg183 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Cody GoloubefHERSEY Bears (WSH)D291989-11-30No91 Kg185 CMNoNoNo1Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Kevin RoyHERSEY Bears (WSH)LW261993-05-20Yes77 Kg175 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Korbinian HolzerHERSEY Bears (WSH)D311988-02-16No99 Kg191 CMNoNoNo1Sans RestrictionPro & Farm900,000$0$0$NoLien
Lukas SedlakHERSEY Bears (WSH)C261993-02-25No93 Kg183 CMNoNoNo2Avec RestrictionPro & Farm900,000$0$0$NoLien
Matt GrzelcykHERSEY Bears (WSH)D251994-01-05Yes79 Kg175 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Michael HutchinsonHERSEY Bears (WSH)G291990-03-02No91 Kg191 CMNoNoNo6Sans RestrictionPro & Farm750,000$0$0$NoLien
Mike ReillyHERSEY Bears (WSH)D261993-07-13No89 Kg185 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Nick PaulHERSEY Bears (WSH)LW241995-03-20No105 Kg193 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Sami NikuHERSEY Bears (WSH)D221996-10-10Yes80 Kg185 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Sebastian D AhoHERSEY Bears (WSH)D231996-02-17No77 Kg178 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Tim HeedHERSEY Bears (WSH)D281991-01-27Yes82 Kg180 CMNoNoNo3Sans RestrictionPro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1526.0088 Kg185 CM2.60780,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nick PaulChandler StephensonAlexandre Fortin31122
2Anders BjorkLukas SedlakKevin Roy26122
3Alexandre FortinChandler StephensonLukas Sedlak23122
4Kevin RoyNick PaulAnders Bjork20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykMike Reilly31122
2Korbinian HolzerTim Heed26122
3Sami NikuCody Goloubef23122
4Sebastian D AhoMatt Grzelcyk20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nick PaulChandler StephensonAlexandre Fortin55122
2Anders BjorkLukas SedlakKevin Roy45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykMike Reilly55122
2Korbinian HolzerTim Heed45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Chandler StephensonLukas Sedlak55122
2Nick PaulAnders Bjork45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykMike Reilly55122
2Korbinian HolzerTim Heed45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Chandler Stephenson55122Matt GrzelcykMike Reilly55122
2Lukas Sedlak45122Korbinian HolzerTim Heed45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Chandler StephensonLukas Sedlak55122
2Nick PaulAnders Bjork45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykMike Reilly55122
2Korbinian HolzerTim Heed45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nick PaulChandler StephensonAlexandre FortinMatt GrzelcykMike Reilly
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nick PaulChandler StephensonAlexandre FortinMatt GrzelcykMike Reilly
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Alexandre Fortin, Kevin Roy, Nick PaulAlexandre Fortin, Kevin RoyNick Paul
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Sami Niku, Cody Goloubef, Sebastian D AhoSami NikuCody Goloubef, Sebastian D Aho
Tirs de Pénalité
Chandler Stephenson, Lukas Sedlak, Nick Paul, Anders Bjork, Alexandre Fortin
Gardien
#1 : Michael Hutchinson, #2 : Anders Lindback
Lignes d'Attaque Perso. en Prol.
Chandler Stephenson, Lukas Sedlak, Nick Paul, Anders Bjork, Alexandre Fortin, Kevin Roy, Kevin Roy, , , ,
Lignes de Défense Perso. en Prol.
Matt Grzelcyk, Mike Reilly, Korbinian Holzer, Tim Heed, Sami Niku


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 Senators330000001358110000005232200000083561.000132033001541156161439599719223245106596233.33%3166.67%01354222960.74%984182054.07%730114763.64%227617511343439854479
2BRIDGEPORT Sound Tigers413000001014-42020000047-32110000067-120.25010192900154115616909599719223210843144417211.76%6266.67%01354222960.74%984182054.07%730114763.64%227617511343439854479
3BROOKLYN Wolfpack44000000430432200000023023220000002002081.00043811240415411561629095997192232176254000.00%10100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
4CHICAGO Wolves53000200321220310002001394220000001931680.800326092011541156161779599719223210424166611545.45%8275.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
5CLEVELAND Monsters44000000391382200000022022220000001711681.0003970109031541156162919599719223251168426350.00%40100.00%11354222960.74%984182054.07%730114763.64%227617511343439854479
6COLORADO Eagles4220000089-1211000005502110000034-140.5008152310154115616100959971922321112814502328.70%50100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
7CORNWALL Aces22000000231221100000013112110000001001041.00023456801154115616153959971922321254236116.67%20100.00%11354222960.74%984182054.07%730114763.64%227617511343439854479
8HOLLYWOOD Oscar22000000230231100000012012110000001101141.000234265021541156161609599719223291019000.00%000.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
9IOWA Wild2110000011381010000002-2110000001111020.5001122330015411561679959971922324410637400.00%30100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
10LAVAL Rockets421000101183210000106422110000054160.7501115260115411561611895997192232702164929724.14%20100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
11LEHIGH VALLEY Phantoms2020000049-51010000013-21010000036-300.00047110015411561646959971922324615142810220.00%7271.43%01354222960.74%984182054.07%730114763.64%227617511343439854479
12MANITOBA Moose22000000716110000003121100000040441.000712190115411561650959971922327418162711218.18%60100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
13MILWAUKEE Admirals42100001770211000003302100000144050.6257121901154115616110959971922329422126118316.67%60100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
14MONT-LAURIER Sommet211000004401010000013-21100000031220.500481200154115616509599719223251144312150.00%2150.00%11354222960.74%984182054.07%730114763.64%227617511343439854479
15PROVIDENCE Bruins422000001013-3220000007432020000039-640.50010182800154115616909599719223212829204415426.67%8275.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
16PV Sharapovas2110000014-3110000001011010000004-420.5001230115411561649959971922323616122710110.00%6350.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
17ROCKFORD IceHogs4020101067-12020000025-32000101042240.50069150015411561694959971922321132622482100.00%10190.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
18SAN DIEGO Gulls22000000606220000006060000000000041.000612180215411561615595997192232116034100.00%000.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
19STOCKTON Flames20101000550100010004311010000012-120.5005712001541156164495997192232442712334125.00%6266.67%01354222960.74%984182054.07%730114763.64%227617511343439854479
20SYRACUSE Crunch2020000009-91010000002-21010000007-700.0000000015411561648959971922327526433300.00%20100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
21TORONTO Marlies11000000606110000006060000000000021.000610160115411561645959971922321741093266.67%50100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
22TUSCON Roadrunners4310000031328211000001138220000002002060.7503153840215411561620395997192232661910533133.33%50100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
Total744024032323361371993820130221016565100362011010221717299960.64933660694212115411561628669599719223215404492509972304419.13%1131983.19%31354222960.74%984182054.07%730114763.64%227617511343439854479
24UTICA Comets503010101115-4201010006603020001059-440.400112031001541156161159599719223214536246522418.18%10370.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
25VICTORIAVILLE Tigres2010000146-21010000012-11000000134-110.250481200154115616499599719223245201031400.00%50100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
26WILKIES-BARRIE Penguins22000000211201100000010010110000001111041.000213960011541156161179599719223224743011100.00%10100.00%01354222960.74%984182054.07%730114763.64%227617511343439854479
_Since Last GM Reset744024032323361371993820130221016565100362011010221717299960.64933660694212115411561628669599719223215404492509972304419.13%1131983.19%31354222960.74%984182054.07%730114763.64%227617511343439854479
_Vs Conference48251502231214891252513801210108466223127010211064363630.65621438459811415411561618339599719223210182761486101663118.67%651084.62%11354222960.74%984182054.07%730114763.64%227617511343439854479
_Vs Division17136010108027539720100040152586400010401228300.8828014222206154115616727959971922323261035023532721.88%23673.91%11354222960.74%984182054.07%730114763.64%227617511343439854479

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7496W133660694228661540449250997121
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7440243232336137
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
382013221016565
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
362011102217172
Derniers 10 Matchs
WLOTWOTL SOWSOL
430201
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2304419.13%1131983.19%3
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
95997192232154115616
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
1354222960.74%984182054.07%730114763.64%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
227617511343439854479


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2019-07-3011HERSEY Bears2LAVAL Rockets4LSommaire du Match
2 - 2019-07-3115ROCKFORD IceHogs1HERSEY Bears0LSommaire du Match
3 - 2019-08-0133HERSEY Bears4UTICA Comets3WXXSommaire du Match
4 - 2019-08-0245COLORADO Eagles1HERSEY Bears3WSommaire du Match
6 - 2019-08-0459CHICAGO Wolves2HERSEY Bears8WSommaire du Match
8 - 2019-08-0677HERSEY Bears10CHICAGO Wolves3WSommaire du Match
9 - 2019-08-0783TUSCON Roadrunners1HERSEY Bears10WSommaire du Match
10 - 2019-08-0894HERSEY Bears10TUSCON Roadrunners0WSommaire du Match
11 - 2019-08-09109BRIDGEPORT Sound Tigers3HERSEY Bears2LSommaire du Match
12 - 2019-08-10120HERSEY Bears2ROCKFORD IceHogs1WXXSommaire du Match
14 - 2019-08-12140HERSEY Bears2COLORADO Eagles1WSommaire du Match
15 - 2019-08-13152SAN DIEGO Gulls0HERSEY Bears2WSommaire du Match
17 - 2019-08-15163LAVAL Rockets3HERSEY Bears4WSommaire du Match
19 - 2019-08-17182HERSEY Bears10CLEVELAND Monsters1WSommaire du Match
20 - 2019-08-18192MILWAUKEE Admirals3HERSEY Bears1LSommaire du Match
21 - 2019-08-19202HERSEY Bears1UTICA Comets4LSommaire du Match
22 - 2019-08-20212MANITOBA Moose1HERSEY Bears3WSommaire du Match
24 - 2019-08-22227HERSEY Bears2ROCKFORD IceHogs1WXSommaire du Match
25 - 2019-08-23241UTICA Comets3HERSEY Bears2LSommaire du Match
26 - 2019-08-24256HERSEY Bears0SYRACUSE Crunch7LSommaire du Match
27 - 2019-08-25269HERSEY Bears11IOWA Wild1WSommaire du Match
28 - 2019-08-26273HERSEY Bears9CHICAGO Wolves0WSommaire du Match
29 - 2019-08-27285SAN DIEGO Gulls0HERSEY Bears4WSommaire du Match
30 - 2019-08-28303UTICA Comets3HERSEY Bears4WXSommaire du Match
31 - 2019-08-29318BROOKLYN Wolfpack0HERSEY Bears11WSommaire du Match
33 - 2019-08-31337HERSEY Bears3MONT-LAURIER Sommet1WSommaire du Match
34 - 2019-09-01348HERSEY Bears3BELLEVILLE Senators2WSommaire du Match
35 - 2019-09-02354HOLLYWOOD Oscar0HERSEY Bears12WSommaire du Match
36 - 2019-09-03370HERSEY Bears0UTICA Comets2LSommaire du Match
37 - 2019-09-04380HERSEY Bears10BROOKLYN Wolfpack0WSommaire du Match
38 - 2019-09-05388CORNWALL Aces1HERSEY Bears13WSommaire du Match
40 - 2019-09-07410COLORADO Eagles4HERSEY Bears2LSommaire du Match
42 - 2019-09-09421IOWA Wild2HERSEY Bears0LSommaire du Match
43 - 2019-09-10436HERSEY Bears10TUSCON Roadrunners0WSommaire du Match
45 - 2019-09-12446ROCKFORD IceHogs4HERSEY Bears2LSommaire du Match
46 - 2019-09-13457HERSEY Bears10CORNWALL Aces0WSommaire du Match
47 - 2019-09-14474HERSEY Bears3LAVAL Rockets0WSommaire du Match
48 - 2019-09-15488HERSEY Bears3LEHIGH VALLEY Phantoms6LSommaire du Match
49 - 2019-09-16496BELLEVILLE Senators2HERSEY Bears5WSommaire du Match
50 - 2019-09-17511BRIDGEPORT Sound Tigers4HERSEY Bears2LSommaire du Match
52 - 2019-09-19527CLEVELAND Monsters0HERSEY Bears11WSommaire du Match
53 - 2019-09-20539HERSEY Bears1COLORADO Eagles3LSommaire du Match
54 - 2019-09-21552LAVAL Rockets1HERSEY Bears2WXXSommaire du Match
57 - 2019-09-24570HERSEY Bears11HOLLYWOOD Oscar0WSommaire du Match
58 - 2019-09-25579BROOKLYN Wolfpack0HERSEY Bears12WSommaire du Match
59 - 2019-09-26593HERSEY Bears11WILKIES-BARRIE Penguins1WSommaire du Match
61 - 2019-09-28607LEHIGH VALLEY Phantoms3HERSEY Bears1LSommaire du Match
62 - 2019-09-29618HERSEY Bears5BELLEVILLE Senators1WSommaire du Match
65 - 2019-10-02634STOCKTON Flames3HERSEY Bears4WXSommaire du Match
67 - 2019-10-04653MILWAUKEE Admirals0HERSEY Bears2WSommaire du Match
68 - 2019-10-05666HERSEY Bears4MANITOBA Moose0WSommaire du Match
70 - 2019-10-07681TORONTO Marlies0HERSEY Bears6WSommaire du Match
72 - 2019-10-09695HERSEY Bears0PV Sharapovas4LSommaire du Match
73 - 2019-10-10704TUSCON Roadrunners2HERSEY Bears1LSommaire du Match
75 - 2019-10-12722HERSEY Bears10BROOKLYN Wolfpack0WSommaire du Match
76 - 2019-10-13733PV Sharapovas0HERSEY Bears1WSommaire du Match
77 - 2019-10-14749HERSEY Bears2MILWAUKEE Admirals3LXXSommaire du Match
78 - 2019-10-15757PROVIDENCE Bruins1HERSEY Bears3WSommaire du Match
80 - 2019-10-17778HERSEY Bears1STOCKTON Flames2LSommaire du Match
81 - 2019-10-18786CLEVELAND Monsters0HERSEY Bears11WSommaire du Match
83 - 2019-10-20807SYRACUSE Crunch2HERSEY Bears0LSommaire du Match
84 - 2019-10-21822HERSEY Bears7CLEVELAND Monsters0WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
85 - 2019-10-22826HERSEY Bears2BRIDGEPORT Sound Tigers4LSommaire du Match
86 - 2019-10-23838VICTORIAVILLE Tigres2HERSEY Bears1LSommaire du Match
87 - 2019-10-24855HERSEY Bears2PROVIDENCE Bruins3LSommaire du Match
88 - 2019-10-25862HERSEY Bears3VICTORIAVILLE Tigres4LXXSommaire du Match
90 - 2019-10-27872PROVIDENCE Bruins3HERSEY Bears4WSommaire du Match
91 - 2019-10-28890WILKIES-BARRIE Penguins0HERSEY Bears10WSommaire du Match
93 - 2019-10-30908HERSEY Bears1PROVIDENCE Bruins6LSommaire du Match
94 - 2019-10-31914MONT-LAURIER Sommet3HERSEY Bears1LSommaire du Match
96 - 2019-11-02931HERSEY Bears4BRIDGEPORT Sound Tigers3WSommaire du Match
97 - 2019-11-03940CHICAGO Wolves4HERSEY Bears3LXSommaire du Match
100 - 2019-11-06963CHICAGO Wolves3HERSEY Bears2LXSommaire du Match
101 - 2019-11-07966HERSEY Bears2MILWAUKEE Admirals1WSommaire du Match
102 - 2019-11-08981HERSEY Bears-TORONTO Marlies-
103 - 2019-11-09988HERSEY Bears-SAN DIEGO Gulls-
105 - 2019-11-11997ROCKFORD IceHogs-HERSEY Bears-
106 - 2019-11-121008HERSEY Bears-SAN DIEGO Gulls-



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
1 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,777,469$ 1,170,000$ 1,170,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,258,307$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 6 16,075$ 96,450$




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
327440240323233613719938201302210165651003620110102217172999633660694212115411561628669599719223215404492509972304419.13%1131983.19%31354222960.74%984182054.07%730114763.64%227617511343439854479
Total Saison Régulière7440240323233613719938201302210165651003620110102217172999633660694212115411561628669599719223215404492509972304419.13%1131983.19%31354222960.74%984182054.07%730114763.64%227617511343439854479