Rampages

GP: 64 | W: 50 | L: 14 | OTL: 0 | P: 100
GF: 418 | GA: 255 | PP%: 56.29% | PK%: 65.75%
DG: Carl Morin | Morale : 84 | Moyenne d'Équipe : 67
Prochain matchs #761 vs Gulls
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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
1Drew StaffordX99.007041827480818271745160657281755068700
2Jussi JokinenX99.005941827169777975745557686588692560700
3J.T. CompherXX100.006242858069868477765265697153527654680
4Nikolay GoldobinXX100.005941807765698471587261716552518081680
5Tyler BertuzziXX100.006445778272787981506161626352516959670
6Mathieu Joseph (R)X100.005543696068719962506559605950504481670
7Jacob JosefsonX100.006341837170786760744454706863577081640
8Laurent Dauphin (R)X100.005346646169678160676157605751517581610
9Alex FormentonX100.005040796265523253535353605450507481570
10Carl GunnarssonX100.006242847075788669305056747372613081700
11Christian FolinX100.008742836679778271305354766857593741700
12Brandon DavidsonX100.008142847878797171304556717456554281690
Rayé
1Eric FehrX95.006343756382677462784560696473704956660
MOYENNE D'ÉQUIPE99.38644279707274776857545867666158557067
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
1Harri Sateri99.00747792828081797879727251634980750
Rayé
MOYENNE D'ÉQUIPE99.0074779282808179787972725163498075
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dave Camaron67656945777170can581400,000$


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'ÉquipePOS GP 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
1Drew StaffordRampages (COL)RW46687714530180654131210819821.79%28107923.463844827215832510798266.29%895243072.69110001393
2Jussi JokinenRampages (COL)LW3751661174345567522597915119.69%3494525.541931504012322491217563.60%2725330162.48010101177
3Carl GunnarssonRampages (COL)D522368913233155642161798514.29%84143027.50203858431750115164130.00%03799021.2700102374
4Brandon DavidsonRampages (COL)D59236790242006752207849311.11%90139323.621842605015411210155200.00%03985011.2900000454
5Nikolay GoldobinRampages (COL)LW/RW59354176722057462657814413.21%2994816.0891726211031015445271.60%817239021.6000000535
6Mike FisherAvalancheC262040601860375598224220.41%2559422.857212816811014612174.48%7171223012.0201000244
7Phil VaroneAvalancheC5723376005557165147579715.65%1395916.84121426211071016534165.94%12392635001.2500010023
8Laurent DauphinRampages (COL)C642032521672104346158648812.66%33105016.418122025940001122061.17%1031933000.9900100153
9Mathieu JosephRampages (COL)RW6423295235205942143379416.08%35107316.7791120141120225732264.17%1203441000.9700000206
10Jacob JosefsonRampages (COL)C64222951311004850171399712.87%3393114.561783250000222067.36%3863231001.0900000232
11Christian FolinRampages (COL)D3414324621220523793394315.05%6194627.851113242110103331202150.00%22849000.9700000014
12Eric FehrRampages (COL)C421824421880415286334820.93%2054512.994375381013291269.73%5221727001.5400000044
13Alex FormentonRampages (COL)LW6413213421260264397245613.40%1985013.281564370002471257.14%491631000.8000000211
14J.T. CompherRampages (COL)C/LW2022-1601313540.00%24422.1101113000240050.00%4014000.9000000000
15Tyler BertuzziRampages (COL)LW/RW2011220212320.00%02914.710001200000000.00%021000.6800000000
Stats d'équipe Total ou en Moyenne672353566919265397356926272212751124215.96%5061282219.08157259416337132110112165992392167.79%36204405711191.4313222455150
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
1Harri SateriRampages (COL)59451200.8923.663496222131978929321.0003590502
Stats d'équipe Total ou en Moyenne59451200.8923.663496222131978929321.0003590502


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
Alex FormentonRampages (COL)LW181999-09-13No165 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm784,166$0$0$NoLien
Brandon DavidsonRampages (COL)D261991-08-21No208 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Carl GunnarssonRampages (COL)D301986-11-09No198 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
Christian FolinRampages (COL)D261991-02-09No204 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm800,000$0$0$NoLien
Drew StaffordRampages (COL)RW311985-10-30No215 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
Eric Fehr (Sur la Masse Salariale)Rampages (COL)C321985-09-07No208 Lbs6 ft4NoNoNo1Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Harri SateriRampages (COL)G271989-12-29No205 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm750,000$0$0$NoLien
J.T. CompherRampages (COL)C/LW221995-04-08No193 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm925,000$0$0$NoLien
Jacob JosefsonRampages (COL)C261991-03-02No196 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Jussi JokinenRampages (COL)LW341983-04-01No191 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
Laurent DauphinRampages (COL)C221995-03-27Yes180 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Mathieu JosephRampages (COL)RW201997-02-09Yes173 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Nikolay GoldobinRampages (COL)LW/RW211995-10-07No185 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm863,333$0$0$NoLien
Tyler BertuzziRampages (COL)LW/RW221995-02-24No190 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm1,400,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1425.50194 Lbs6 ft11.14840,893$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jussi JokinenJ.T. CompherDrew Stafford40122
2Nikolay GoldobinJacob JosefsonTyler Bertuzzi30122
3Alex FormentonLaurent DauphinMathieu Joseph20122
4Drew StaffordJussi JokinenNikolay Goldobin10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinCarl Gunnarsson40122
2Brandon Davidson30122
320122
4Christian FolinCarl Gunnarsson10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jussi JokinenJ.T. CompherDrew Stafford60122
2Nikolay GoldobinJacob JosefsonTyler Bertuzzi40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinCarl Gunnarsson60122
2Brandon Davidson40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Jussi JokinenDrew Stafford60122
2Nikolay GoldobinJ.T. Compher40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinCarl Gunnarsson60122
2Brandon Davidson40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Jussi Jokinen60122Christian FolinCarl Gunnarsson60122
2Drew Stafford40122Brandon Davidson40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Jussi JokinenDrew Stafford60122
2Nikolay GoldobinJ.T. Compher40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinCarl Gunnarsson60122
2Brandon Davidson40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jussi JokinenJ.T. CompherDrew StaffordChristian FolinCarl Gunnarsson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jussi JokinenJ.T. CompherDrew StaffordChristian FolinCarl Gunnarsson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mathieu Joseph, Laurent Dauphin, Alex FormentonMathieu Joseph, Laurent DauphinAlex Formenton
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brandon Davidson, Christian Folin, Carl GunnarssonBrandon DavidsonChristian Folin, Carl Gunnarsson
Tirs de Pénalité
Jussi Jokinen, Drew Stafford, Nikolay Goldobin, J.T. Compher, Tyler Bertuzzi
Gardien
#1 : Harri Sateri, #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
1Admirals422000002327-410100000410-6321000001917240.500234063006818815931896429558786184494765211152.38%161318.75%1914137866.33%944151962.15%871134264.90%140779713415081100612
2Barracuda5500000049133622000000265213300000023815101.0004984133016818815932076429558786115453571372875.68%15473.33%0914137866.33%944151962.15%871134264.90%140779713415081100612
3Bears22000000734110000005231100000021141.000710170068188159366642955878653918236350.00%9188.89%0914137866.33%944151962.15%871134264.90%140779713415081100612
4Bruins330000003082222000000216151100000092761.00030487800681881593124642955878670231250211361.90%6183.33%1914137866.33%944151962.15%871134264.90%140779713415081100612
5Condors413000001720-31010000035-2312000001415-120.25017294620681881593148642955878614349385520945.00%19573.68%0914137866.33%944151962.15%871134264.90%140779713415081100612
6Crunch11000000624000000000001100000062421.0006814006818815935364295587861746207342.86%30100.00%0914137866.33%944151962.15%871134264.90%140779713415081100612
7Devils11000000321110000003210000000000021.00036900681881593396429558786522041522100.00%20100.00%0914137866.33%944151962.15%871134264.90%140779713415081100612
8Gulls3210000023131011000000808211000001513240.6672338610168188159310964295587869133275213969.23%11736.36%1914137866.33%944151962.15%871134264.90%140779713415081100612
9Heat321000002316722000000198111010000048-440.66723426500681881593143642955878665202243131184.62%11554.55%1914137866.33%944151962.15%871134264.90%140779713415081100612
10Icedogs4310000025151022000000126621100000139460.750254469006818815931586429558786125383451161062.50%17758.82%2914137866.33%944151962.15%871134264.90%140779713415081100612
11Marlies2110000078-1110000005411010000024-220.50071219006818815936464295587868833143413646.15%7357.14%0914137866.33%944151962.15%871134264.90%140779713415081100612
12Monsters220000001477110000007431100000073441.000142236006818815936664295587863810242916318.75%12283.33%1914137866.33%944151962.15%871134264.90%140779713415081100612
13Moose540010003422122200000014953200100020137101.000346094006818815931776429558786197576166191157.89%28871.43%4914137866.33%944151962.15%871134264.90%140779713415081100612
14Penguins220000001679110000007341100000094541.00016233900681881593826429558786712116299333.33%8187.50%0914137866.33%944151962.15%871134264.90%140779713415081100612
15Phantoms220000001596110000009451100000065141.000152944006818815938064295587868831162712758.33%8537.50%0914137866.33%944151962.15%871134264.90%140779713415081100612
16Reigh3300000027141322000000179811000000105561.00027457200681881593127642955878685193039171376.47%12375.00%1914137866.33%944151962.15%871134264.90%140779713415081100612
17Senateurs2100100012102100010006511100000065141.000121729006818815938764295587867529142114642.86%7357.14%0914137866.33%944151962.15%871134264.90%140779713415081100612
18Sound Tigers2200000015114110000008621100000075241.000152742006818815936064295587868123182710550.00%9455.56%0914137866.33%944151962.15%871134264.90%140779713415081100612
19Stars724000101821-3413000001014-43110001087160.4291826440068188159322764295587863191295289231147.83%261061.54%1914137866.33%944151962.15%871134264.90%140779713415081100612
20Thunderbird2200000014410110000008261100000062441.000142337006818815936564295587866418252911436.36%10190.00%0914137866.33%944151962.15%871134264.90%140779713415081100612
Total6447140201041825516331255010002201191013322901010198136621000.78141870111192268188159324786429558786218071054990933418856.29%2548765.75%13914137866.33%944151962.15%871134264.90%140779713415081100612
22Wolves541000004023173300000028151321100000128480.8004068108006818815932076429558786159503674342058.82%18477.78%0914137866.33%944151962.15%871134264.90%140779713415081100612
_Since Last GM Reset6447140201041825516331255010002201191013322901010198136621000.78141870111192268188159324786429558786218071054990933418856.29%2548765.75%13914137866.33%944151962.15%871134264.90%140779713415081100612
_Vs Conference432813010102791849520155000001418160231380101013810335600.6982794767552268188159316926429558786148348938260521313362.44%1736661.85%11914137866.33%944151962.15%871134264.90%140779713415081100612
_Vs Division251580101014010832128400000685414137401010725418340.6801402383780068188159395864295587869843232303451136355.75%1054260.00%8914137866.33%944151962.15%871134264.90%140779713415081100612

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
64100W141870111192478218071054990922
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6447142010418255
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
312551000220119
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
332291010198136
Derniers 10 Matchs
WLOTWOTL SOWSOL
730000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
33418856.29%2548765.75%13
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
6429558786681881593
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
914137866.33%944151962.15%871134264.90%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
140779713415081100612


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 - 2018-10-091Rampages7Admirals4WSommaire du Match
4 - 2018-10-1216Stars4Rampages6WSommaire du Match
7 - 2018-10-1528Rampages3Stars4LSommaire du Match
12 - 2018-10-2041Rampages5Moose4WXSommaire du Match
14 - 2018-10-2245Moose4Rampages8WSommaire du Match
17 - 2018-10-2554Rampages6Wolves1WSommaire du Match
19 - 2018-10-2765Icedogs2Rampages4WSommaire du Match
21 - 2018-10-2978Rampages10Icedogs4WSommaire du Match
22 - 2018-10-3080Rampages3Condors5LSommaire du Match
26 - 2018-11-0396Admirals10Rampages4LSommaire du Match
28 - 2018-11-05110Rampages9Barracuda3WSommaire du Match
30 - 2018-11-07119Wolves2Rampages10WSommaire du Match
32 - 2018-11-09130Rampages4Admirals6LSommaire du Match
34 - 2018-11-11142Stars3Rampages2LSommaire du Match
37 - 2018-11-14156Rampages3Stars2WSommaire du Match
40 - 2018-11-17168Reigh4Rampages5WSommaire du Match
45 - 2018-11-22189Wolves3Rampages7WSommaire du Match
48 - 2018-11-25202Rampages9Bruins2WSommaire du Match
51 - 2018-11-28213Bears2Rampages5WSommaire du Match
54 - 2018-12-01224Rampages6Thunderbird2WSommaire du Match
58 - 2018-12-05237Reigh5Rampages12WSommaire du Match
60 - 2018-12-07246Rampages6Gulls7LSommaire du Match
64 - 2018-12-11258Thunderbird2Rampages8WSommaire du Match
66 - 2018-12-13267Rampages2Stars1WXXSommaire du Match
68 - 2018-12-15274Rampages7Monsters3WSommaire du Match
70 - 2018-12-17285Monsters4Rampages7WSommaire du Match
72 - 2018-12-19291Rampages6Senateurs5WSommaire du Match
74 - 2018-12-21303Rampages5Moose3WSommaire du Match
75 - 2018-12-22310Senateurs5Rampages6WXSommaire du Match
78 - 2018-12-25320Rampages9Gulls6WSommaire du Match
81 - 2018-12-28334Sound Tigers6Rampages8WSommaire du Match
83 - 2018-12-30342Rampages7Sound Tigers5WSommaire du Match
85 - 2019-01-01353Rampages10Moose6WSommaire du Match
86 - 2019-01-02359Wolves10Rampages11WSommaire du Match
90 - 2019-01-06378Rampages2Bears1WSommaire du Match
91 - 2019-01-07384Bruins2Rampages11WSommaire du Match
96 - 2019-01-12405Icedogs4Rampages8WSommaire du Match
101 - 2019-01-17425Rampages6Barracuda3WSommaire du Match
103 - 2019-01-19430Heat2Rampages12WSommaire du Match
106 - 2019-01-22446Rampages3Icedogs5LSommaire du Match
108 - 2019-01-24454Barracuda0Rampages8WSommaire du Match
113 - 2019-01-29475Heat6Rampages7WSommaire du Match
115 - 2019-01-31481Rampages6Crunch2WSommaire du Match
119 - 2019-02-04501Marlies4Rampages5WSommaire du Match
124 - 2019-02-09518Rampages8Barracuda2WSommaire du Match
127 - 2019-02-12526Gulls0Rampages8WSommaire du Match
130 - 2019-02-15541Rampages5Condors6LSommaire du Match
131 - 2019-02-16549Devils2Rampages3WSommaire du Match
135 - 2019-02-20568Stars5Rampages1LSommaire du Match
140 - 2019-02-25590Bruins4Rampages10WSommaire du Match
142 - 2019-02-27598Rampages6Wolves7LSommaire du Match
146 - 2019-03-03613Phantoms4Rampages9WSommaire du Match
148 - 2019-03-05626Rampages2Marlies4LSommaire du Match
150 - 2019-03-07635Rampages6Condors4WSommaire du Match
151 - 2019-03-08643Stars2Rampages1LSommaire du Match
154 - 2019-03-11655Rampages8Admirals7WSommaire du Match
156 - 2019-03-13666Barracuda5Rampages18WSommaire du Match
158 - 2019-03-15676Rampages4Heat8LSommaire du Match
161 - 2019-03-18687Rampages10Reigh5WSommaire du Match
163 - 2019-03-20694Moose5Rampages6WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
167 - 2019-03-24712Rampages6Phantoms5WSommaire du Match
168 - 2019-03-25718Penguins3Rampages7WSommaire du Match
173 - 2019-03-30738Condors5Rampages3LSommaire du Match
179 - 2019-04-05757Rampages9Penguins4WSommaire du Match
181 - 2019-04-07761Gulls-Rampages-
185 - 2019-04-11780Rocket-Rampages-
187 - 2019-04-13789Rampages-Icedogs-
190 - 2019-04-16803Rampages-Reigh-
192 - 2019-04-18810Rampages-Rocket-
193 - 2019-04-19815Admirals-Rampages-
198 - 2019-04-24834Rampages-Blacknight-
200 - 2019-04-26838Condors-Rampages-
203 - 2019-04-29856Rampages-Blacknight-
205 - 2019-05-01863Admirals-Rampages-
207 - 2019-05-03870Rampages-Heat-
209 - 2019-05-05882Rampages-Devils-
212 - 2019-05-08888Moose-Rampages-
217 - 2019-05-13911Icedogs-Rampages-
219 - 2019-05-15924Rampages-Wolves-
222 - 2019-05-18935Crunch-Rampages-
229 - 2019-05-25957Blacknight-Rampages-
235 - 2019-05-31982Blacknight-Rampages-



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
10 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,035,284$ 1,077,250$ 1,077,250$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 731,493$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 57 6,233$ 355,281$




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
264471402010418255163312550100022011910133229010101981366210041870111192268188159324786429558786218071054990933418856.29%2548765.75%13914137866.33%944151962.15%871134264.90%140779713415081100612
Total Saison Régulière64471402010418255163312550100022011910133229010101981366210041870111192268188159324786429558786218071054990933418856.29%2548765.75%13914137866.33%944151962.15%871134264.90%140779713415081100612