Bears

GP: 76 | W: 42 | L: 25 | OTL: 9 | P: 93
GF: 199 | GA: 155 | PP%: 15.36% | PK%: 88.43%
DG: Mathieu Girard | Morale : 58 | 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
1Jason DickinsonXX100.008243806580748064766761736267667778660
2Paul ThompsonX100.006343726277949361645960586179815469640
3Tom KuhnhacklXX100.008336916180705959536258815773675280640
4Kyle CliffordX100.008578656383678562546164566375706377630
5Brett SutterX100.006138856074939059645858575980725377620
6Christoffer Ehn (R)XX100.007037886380737262706158675665646669620
7Anton BlidhX100.007338865675867355535654655267645580600
8Gage QuinneyX100.005436925962939058645756545967646369600
9Cooper Marody (R)X100.005336906171766960696257595665635669600
10Timothy Gettinger (R)X100.007836925896777257545655615361635669600
11Dennis YanX100.006239825977908557545355565263626377590
12Reid DukeX100.005938845673857956585553545065636277580
13Jayden HalbgewachsX100.005336915860928957535854525663626369580
14Rich CluneX100.006338845673666454535152535774714831550
15Kyle WoodX100.008638855898939156306052634665636269670
16Sami NikuX100.005637896473777163306858614865635677620
17Michael KaplaX100.006136925674939054305852534669656075610
18Trevor MurphyX100.005140785866928957305853564867646174600
Rayé
MOYENNE D'ÉQUIPE100.00664085607683805853595660556866597161
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
1Vitek Vanecek100.00777876747675777675777665695367730
Rayé
MOYENNE D'ÉQUIPE100.0077787674767577767577766569536773
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jay Leach73676657605786USA394100,000$


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
1Jason DickinsonBears (Was)C/LW764034744109151922494511333188.87%50177923.419918842351013739258.97%136000020.8349111759
2Anton BlidhBears (Was)LW76383573161091516516635910926110.58%40179923.67121527922630003746347.06%11900010.8135210754
3Brett SutterBears (Was)C76324173165630972083781032698.47%32149019.616222883281000005255.05%163300020.9811123761
4Kyle CliffordBears (Was)LW76353873221614521516929510223211.86%31164221.61714218225700062609145.95%64200010.8917206657
5Trevor MurphyBears (Was)D761555701813115162100178521258.43%150166321.891017271182620111222500.00%000000.8400111438
6Sami NikuBears (Was)D76164561151320160140184581138.70%129175023.0389171272830000223320.00%000000.7000000344
7Tom KuhnhacklBears (Was)LW/RW37161733122405845138378111.59%1474320.105611321581121546146.88%6400100.8911000513
8Michael KaplaBears (Was)D7652631-2114101456350153210.00%95114515.07000000000120000.00%000000.5400011013
9Reid DukeBears (Was)C7631518720447479416.38%44135.4400000000000048.81%50600000.8700000010
10Dennis YanBears (Was)LW76011000013160.00%0250.330000000000000.00%000000.8000000000
Stats d'équipe Total ou en Moyenne72120030750710883813011981188208361914789.60%5451245217.2757921496181742224141028431153.86%432400160.8110237612393139
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
1Vitek VanecekBears (Was)76422590.9301.91455061514520790910.690297601473
Stats d'équipe Total ou en Moyenne76422590.9301.91455061514520790910.690297601473


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
Anton BlidhBears (Was)LW241995-03-14No201 Lbs6 ft0NoNoNo1Pro & Farm300,000$0$0$NoLien
Brett SutterBears (Was)C321987-06-02No200 Lbs6 ft0NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Christoffer EhnBears (Was)C/LW231996-04-05Yes181 Lbs6 ft3NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Cooper MarodyBears (Was)C221996-12-20Yes184 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Dennis YanBears (Was)LW221997-04-14No197 Lbs6 ft1NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Gage QuinneyBears (Was)C231995-07-29No200 Lbs5 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Jason DickinsonBears (Was)C/LW241995-07-04No200 Lbs6 ft2NoNoNo1Pro & Farm900,000$0$0$NoLien
Jayden HalbgewachsBears (Was)LW221997-03-22No160 Lbs5 ft8NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Kyle CliffordBears (Was)LW281991-01-13No211 Lbs6 ft2NoNoNo1Pro & Farm300,000$0$0$NoLien
Kyle WoodBears (Was)D231996-05-04No235 Lbs6 ft7NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Michael KaplaBears (Was)D241994-09-19No200 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Paul ThompsonBears (Was)RW301988-11-30No200 Lbs6 ft1NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Reid DukeBears (Was)C231996-01-28No191 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Rich CluneBears (Was)LW321987-04-25No207 Lbs5 ft10NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Sami NikuBears (Was)D221996-10-10No176 Lbs6 ft1NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Timothy GettingerBears (Was)LW211998-04-14Yes220 Lbs6 ft6NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Tom KuhnhacklBears (Was)LW/RW271992-01-21No196 Lbs6 ft2NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Trevor MurphyBears (Was)D231995-07-17No180 Lbs5 ft10NoNoNo1Pro & Farm300,000$0$0$NoLien
Vitek VanecekBears (Was)G231996-01-09No181 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1924.63196 Lbs6 ft02.79405,263$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJason Dickinson40122
2Brett SutterAnton Blidh30122
3Anton BlidhReid DukeKyle Clifford20122
4Jason Dickinson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku40122
2Trevor Murphy30122
3Michael Kapla20122
4Sami Niku10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJason Dickinson60122
2Brett SutterAnton Blidh40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku60122
2Trevor Murphy40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kyle Clifford60122
2Jason DickinsonAnton Blidh40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku60122
2Trevor Murphy40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Kyle Clifford60122Sami Niku60122
240122Trevor Murphy40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kyle Clifford60122
2Jason DickinsonAnton Blidh40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku60122
2Trevor Murphy40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJason DickinsonSami Niku
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJason DickinsonSami Niku
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Dennis Yan, , Dennis Yan
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Michael Kapla, Trevor MurphyMichael Kapla, Trevor Murphy
Tirs de Pénalité
Kyle Clifford, , Jason Dickinson, Anton Blidh,
Gardien
#1 : Vitek Vanecek, #2 :


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
1Admirals211000005501010000023-11100000032120.50058130072615714396857156815966213945300.00%16193.75%01110227348.83%1093253543.12%508101250.20%181213201943525863412
2Americans21100000312110000003031010000001-120.5003470172615714356857156815966182634400.00%120100.00%01110227348.83%1093253543.12%508101250.20%181213201943525863412
3Bruins624000001516-1312000009723120000069-340.333152439007261571413668571568159185531158521419.05%43295.35%01110227348.83%1093253543.12%508101250.20%181213201943525863412
4Checkers44000000304262200000017116220000001331081.0003046760272615714218685715681598429428615320.00%100100.00%01110227348.83%1093253543.12%508101250.20%181213201943525863412
5Comets22000000936110000004311100000050541.00091625017261571481685715681594913182715533.33%8187.50%01110227348.83%1093253543.12%508101250.20%181213201943525863412
6Crunch22000000312110000002111100000010141.000358017261571444685715681595211194011218.18%6183.33%01110227348.83%1093253543.12%508101250.20%181213201943525863412
7Devils2110000045-11010000024-21100000021120.50046100072615714536857156815963161830800.00%7271.43%01110227348.83%1093253543.12%508101250.20%181213201943525863412
8Griffins22000000725110000003211100000040441.0007101701726157145668571568159452229319333.33%12283.33%01110227348.83%1093253543.12%508101250.20%181213201943525863412
9IceHogs220000001019110000004131100000060641.0001018280172615714946857156815937714388112.50%7185.71%11110227348.83%1093253543.12%508101250.20%181213201943525863412
10Marlies220000001028110000006241100000040441.000101626017261571478685715681595215282914535.71%60100.00%01110227348.83%1093253543.12%508101250.20%181213201943525863412
11Monsters412000101215-3201000107702110000058-340.5001219310172615714986857156815911735428019631.58%21480.95%01110227348.83%1093253543.12%508101250.20%181213201943525863412
12Penguins12440200221201621020011192623000011011-1140.583213455017261571431568571568159336961141858278.54%54394.44%01110227348.83%1093253543.12%508101250.20%181213201943525863412
13Phantoms1246000112232-1061300011814-6633000001418-4110.45822335511726157143056857156815934312015619555916.36%47882.98%01110227348.83%1093253543.12%508101250.20%181213201943525863412
14Rocket201010004401010000012-11000100032120.500471100726157144868571568159531322408112.50%10280.00%01110227348.83%1093253543.12%508101250.20%181213201943525863412
15Senators210001007611000010023-11100000053230.75071320007261571456685715681596516433610110.00%11372.73%01110227348.83%1093253543.12%508101250.20%181213201943525863412
16Sound Tigers6100212011743000111065131001010523110.917111526027261571416068571568159160415410418211.11%26484.62%01110227348.83%1093253543.12%508101250.20%181213201943525863412
17Thunderbirds6310010113121310001017613210000066080.6671324370172615714157685715681591715158952627.69%19384.21%01110227348.83%1093253543.12%508101250.20%181213201943525863412
Total763325055441991554438131203433101802138201302111987523930.61219931951811472615714211068571568159211162389212673585515.36%3373988.43%11110227348.83%1093253543.12%508101250.20%181213201943525863412
19Wolf Pack604002001319-630200100710-33020010069-320.16713213400726157141376857156815916746558732412.50%22290.91%01110227348.83%1093253543.12%508101250.20%181213201943525863412
_Since Last GM Reset763325055441991554438131203433101802138201302111987523930.61219931951811472615714211068571568159211162389212673585515.36%3373988.43%11110227348.83%1093253543.12%508101250.20%181213201943525863412
_Vs Conference52162104443108121-1326510033325460-6261111011115461-7550.529108170278167261571413046857156815914884346168422563513.67%2372987.76%01110227348.83%1093253543.12%508101250.20%181213201943525863412
_Vs Division467402102113102112331021015850823430000155523210.228113174287177261571412866857156815912703834817672293113.54%1872387.70%01110227348.83%1093253543.12%508101250.20%181213201943525863412

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7693OTL1199319518211021116238921267114
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7633255544199155
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
381312343310180
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
38201321119875
Derniers 10 Matchs
WLOTWOTL SOWSOL
431110
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3585515.36%3373988.43%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
6857156815972615714
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
1110227348.83%1093253543.12%508101250.20%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
181213201943525863412


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
4 - 2019-09-0511Crunch1Bears2WSommaire du Match
5 - 2019-09-0626Sound Tigers1Bears2WXXSommaire du Match
10 - 2019-09-1134Bears4Griffins0WSommaire du Match
11 - 2019-09-1248Bears3Admirals2WSommaire du Match
12 - 2019-09-1362Bears6IceHogs0WSommaire du Match
15 - 2019-09-1666Bears1Penguins2LSommaire du Match
17 - 2019-09-1870Bears7Checkers0WSommaire du Match
18 - 2019-09-1984Bears6Checkers3WSommaire du Match
24 - 2019-09-25109Bears1Penguins2LXXSommaire du Match
25 - 2019-09-26118Penguins2Bears3WSommaire du Match
26 - 2019-09-27134Phantoms3Bears1LSommaire du Match
31 - 2019-10-02145Bears0Americans1LSommaire du Match
32 - 2019-10-03156Americans0Bears3WSommaire du Match
33 - 2019-10-04168Wolf Pack3Bears2LSommaire du Match
39 - 2019-10-10195Thunderbirds0Bears3WSommaire du Match
40 - 2019-10-11209Bears1Crunch0WSommaire du Match
45 - 2019-10-16223Monsters4Bears3LSommaire du Match
46 - 2019-10-17238Monsters3Bears4WXXSommaire du Match
52 - 2019-10-23268Bears1Phantoms3LSommaire du Match
53 - 2019-10-24282Bears4Penguins2WSommaire du Match
57 - 2019-10-28300Penguins3Bears2LSommaire du Match
60 - 2019-10-31323Thunderbirds4Bears3LXSommaire du Match
61 - 2019-11-01335Devils4Bears2LSommaire du Match
66 - 2019-11-06352Bears1Phantoms5LSommaire du Match
67 - 2019-11-07364Wolf Pack3Bears2LSommaire du Match
68 - 2019-11-08379Penguins0Bears1WSommaire du Match
74 - 2019-11-14408Bears3Bruins2WSommaire du Match
75 - 2019-11-15417Bears4Thunderbirds1WSommaire du Match
78 - 2019-11-18427Bears3Phantoms2WSommaire du Match
80 - 2019-11-20434Penguins2Bears1LXXSommaire du Match
81 - 2019-11-21456Phantoms4Bears2LSommaire du Match
87 - 2019-11-27479Bears1Penguins2LSommaire du Match
88 - 2019-11-28488Bruins3Bears2LSommaire du Match
89 - 2019-11-29501Bruins1Bears5WSommaire du Match
95 - 2019-12-05536Griffins2Bears3WSommaire du Match
96 - 2019-12-06549Admirals3Bears2LSommaire du Match
101 - 2019-12-11566Bears2Thunderbirds1WSommaire du Match
102 - 2019-12-12580Bears3Phantoms2WSommaire du Match
103 - 2019-12-13590Phantoms5Bears0LSommaire du Match
106 - 2019-12-16598Bears2Devils1WSommaire du Match
109 - 2019-12-19624Bears1Penguins2LSommaire du Match
110 - 2019-12-20632Bears1Sound Tigers0WSommaire du Match
113 - 2019-12-23649Bears3Phantoms5LSommaire du Match
116 - 2019-12-26672Rocket2Bears1LSommaire du Match
123 - 2020-01-02700Phantoms1Bears0LXXSommaire du Match
124 - 2020-01-03711Senators3Bears2LXSommaire du Match
127 - 2020-01-06718Bears0Thunderbirds4LSommaire du Match
130 - 2020-01-09737Checkers1Bears10WSommaire du Match
131 - 2020-01-10755Checkers0Bears7WSommaire du Match
134 - 2020-01-13762Penguins1Bears2WXSommaire du Match
137 - 2020-01-16781Phantoms1Bears2WXXSommaire du Match
138 - 2020-01-17801Bears3Phantoms1WSommaire du Match
143 - 2020-01-22822Bears2Penguins1WSommaire du Match
144 - 2020-01-23833IceHogs1Bears4WSommaire du Match
145 - 2020-01-24840Bears1Sound Tigers0WXSommaire du Match
148 - 2020-01-27851Bears2Wolf Pack3LXSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29857Bears5Comets0WSommaire du Match
151 - 2020-01-30870Sound Tigers2Bears1LXSommaire du Match
157 - 2020-02-05901Bears1Bruins4LSommaire du Match
158 - 2020-02-06912Bears2Bruins3LSommaire du Match
159 - 2020-02-07923Bears3Wolf Pack4LSommaire du Match
162 - 2020-02-10935Thunderbirds2Bears1LXXSommaire du Match
164 - 2020-02-12945Marlies2Bears6WSommaire du Match
165 - 2020-02-13956Sound Tigers2Bears3WXSommaire du Match
168 - 2020-02-16972Penguins1Bears2WXSommaire du Match
172 - 2020-02-20996Bears3Monsters0WSommaire du Match
173 - 2020-02-211009Bears2Monsters8LSommaire du Match
179 - 2020-02-271040Bruins3Bears2LSommaire du Match
180 - 2020-02-281054Bears3Sound Tigers2WXXSommaire du Match
184 - 2020-03-031072Bears4Marlies0WSommaire du Match
185 - 2020-03-041073Bears5Senators3WSommaire du Match
186 - 2020-03-051083Bears3Rocket2WXSommaire du Match
189 - 2020-03-081105Phantoms0Bears3WSommaire du Match
192 - 2020-03-111122Bears1Wolf Pack2LSommaire du Match
193 - 2020-03-121129Comets3Bears4WSommaire du Match
194 - 2020-03-131146Wolf Pack4Bears3LXSommaire du Match



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
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
174,428$ 77,000$ 24,940$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 74,418$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 912$ 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
147633250554419915544381312034331018021382013021119875239319931951811472615714211068571568159211162389212673585515.36%3373988.43%11110227348.83%1093253543.12%508101250.20%181213201943525863412
Total Saison Régulière7633250554419915544381312034331018021382013021119875239319931951811472615714211068571568159211162389212673585515.36%3373988.43%11110227348.83%1093253543.12%508101250.20%181213201943525863412