Comets

GP: 76 | W: 31 | L: 39 | OTL: 6 | P: 68
GF: 204 | GA: 244 | PP%: 13.58% | PK%: 81.99%
DG: Francis Lagace | Morale : 38 | Moyenne d'Équipe : 58
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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
1Dennis RasmussenX99.00685563787974666674626165557268132640
2Andrew AgozzinoX99.00605574736763696150606060557371148610
3Steven FogartyX99.00605565627975696050606060555050158590
4Chris BourqueX99.00595567676159735950585855557374157590
5Janne Kuokkanen (R)X100.00605555726060606050606060555050132580
6Rod PelleyX100.00775569627568695550555555556465177580
7Justin VaiveX100.00665559627975695550555556555050129570
8Justin Scott (R)X100.00735569627969695550555555555050159570
9Tyler RandellX100.00595562647468645550555559555050160570
10Mitch MorozX100.00745569637973625550555555555050157570
11Mitchell HeardX100.00595559627569545550555558555050174560
12Alexandre GrenierX100.00555555555555555550555555557574153540
13Phil LaneX100.00605562555860685550555555555050123540
14Fredrik ClaessonX100.00965578747977677025636179557473173710
15Jan KostalekX100.00595555605555655525555555555353157540
16Mat ClarkX100.00555555605555635525555555555353152540
17William Wrenn (R)X100.00575555605555615525555555555353157540
18Mark Friedman (R)X100.00555555605555555525555555556262123540
19Philip SamuelssonX100.00555555605555665525555555555353160540
Rayé
1Austin Wagner (R)X100.00565555555859595550555555557271120540
2Jeremiah Addison (R)X100.00655566557154545850555855555050119540
3Kevin Lynch (R)X100.00565555555556555550555555555050123520
4Tobias LindbergX100.00565555555555555550555555555050119520
5Michael DowningX100.00555555605555535525555555555555118530
MOYENNE D'ÉQUIPE99.8362556162656263574456565755585714557
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
1Jeff Glass100.0079707280807071788890556967168750
2Hunter Miska (R)100.0055678465515655615454555055122560
Rayé
1Kasimir Kaskisuo100.0075635776717171737977557068163700
2Jared Coreau100.0056807089656559775968557069120670
MOYENNE D'ÉQUIPE100.006670717867666472707255656514367
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Darryl Sutter50836377896452CAN5936,400,000$


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
1Steven FogartyComets (Van)C76234669-15595111189287712088.01%42167822.09320238334900061324051.74%115000000.8211001425
2Andrew AgozzinoComets (Van)LW76213859-7511573192247761668.50%30174022.901111225431612373273152.20%91000000.6816021344
3Chris BourqueComets (Van)LW762630568480821292266215111.50%19153120.16711185933631471593055.45%10100010.7323000346
4Dennis RasmussenComets (Van)C371924434295601271423310413.38%2089624.22511163417900051805163.23%86200010.9613000621
5Justin ScottComets (Van)C76162440-238210171103201581517.96%14117015.4083115616201121010049.37%47600000.6802002330
6Tyler RandellComets (Van)RW761416300435120721384411210.14%1498612.9936924200000001154.00%5000000.6100100231
7William WrennComets (Van)D7692029-79001205670274512.86%60116615.3536940156101214120100.00%100000.5000000012
8Alexandre GrenierComets (Van)RW3962026-159515119456926578.70%6184321.633912431620000112000.00%000000.6200002011
9Fredrik ClaessonComets (Van)D37111526-26801086581346313.58%3675620.455611531550002119200.00%000000.6900000222
10Mitch MorozComets (Van)LW76111223-145201127814536997.59%2183611.01000000001953154.74%9500000.5500000216
11Janne KuokkanenComets (Van)RW37813215200303058133313.79%236910.00551030190000002248.00%2500001.1400000031
12Jan KostalekComets (Van)D7641418-910410105514121219.76%77138718.26213101500111218010.00%000000.2600110200
13Philip SamuelssonComets (Van)D7651318-97715105575726338.77%55113114.89325331480000128000.00%000000.3200003100
14Tobias LindbergComets (Van)RW398816-12495595071265811.27%870518.0924619141000000248.90%40900000.4500001010
15Justin VaiveComets (Van)LW374913225529294214399.52%540210.8800000000000057.14%2800000.6500010010
16Mitchell HeardComets (Van)C37571245512173941412.82%41995.3822410460000171037.50%7200001.2000001020
17Rod PelleyComets (Van)C3747112421051475318397.55%1652014.060000000031091053.52%38300000.4201101100
18Mark FriedmanComets (Van)D7044240672220.00%314921.29011234000033000.00%000000.5400000000
19Jeremiah AddisonComets (Van)LW22022100463160.00%1823.74000010002680048.89%4500000.4900000000
20Mat ClarkComets (Van)D911256020581512.50%717719.76000540000038000.00%000000.2200000010
21Austin WagnerComets (Van)LW11011000020050.00%011.480000000000000.00%0000013.4800000000
Stats d'équipe Total ou en Moyenne1023196323519-7994910514971355198259314069.89%4951673616.3662981605552772551038198427953.57%460700020.625163412293129
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
1Jeff GlassComets (Van)2314720.9141.94133123435010100.5717230212
2Kasimir KaskisuoComets (Van)52100.9451.482430161090100.0000326100
Stats d'équipe Total ou en Moyenne2816820.9201.87157524496100200.57172626312


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 GrenierComets (Van)RW251991-09-04No200 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Andrew AgozzinoComets (Van)LW261991-01-02No187 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Austin WagnerComets (Van)LW191997-06-23Yes185 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Chris BourqueComets (Van)LW301986-01-29No174 Lbs5 ft8NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Dennis RasmussenComets (Van)C261990-07-03No205 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Fredrik ClaessonComets (Van)D241992-11-24No209 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Hunter MiskaComets (Van)G211995-07-07Yes174 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Jan KostalekComets (Van)D211995-02-17No181 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No
Janne KuokkanenComets (Van)RW181998-05-25Yes187 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Jared CoreauComets (Van)G251991-11-05No235 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jeff GlassComets (Van)G311985-11-18No206 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm750,000$0$0$No
Jeremiah AddisonComets (Van)LW201996-10-21Yes187 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Justin ScottComets (Van)C211995-08-13Yes201 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Justin VaiveComets (Van)LW271989-07-08No209 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Kasimir KaskisuoComets (Van)G231993-10-02No201 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Kevin LynchComets (Van)C251991-04-23Yes205 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Mark FriedmanComets (Van)D211995-12-25Yes185 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Mat ClarkComets (Van)D261990-10-16No225 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Michael DowningComets (Van)D211995-05-19No205 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm500,000$0$0$No
Mitch MorozComets (Van)LW221994-05-02No214 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Mitchell HeardComets (Van)C241992-03-11No200 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Phil LaneComets (Van)RW241992-05-28No203 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Philip SamuelssonComets (Van)D251991-07-25No194 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Rod PelleyComets (Van)C321984-08-31No200 Lbs5 ft11NoNoNo4Sans RestrictionPro & Farm300,000$0$0$No
Steven FogartyComets (Van)C231993-04-19No212 Lbs6 ft3NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Tobias LindbergComets (Van)RW211995-07-22No201 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No
Tyler RandellComets (Van)RW251991-06-14No197 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
William WrennComets (Van)D251991-03-16Yes209 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2823.96200 Lbs6 ft22.07351,786$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Andrew AgozzinoDennis RasmussenJanne Kuokkanen40122
2Chris BourqueSteven FogartyTyler Randell30122
3Justin VaiveRod PelleyDennis Rasmussen20122
4Mitch MorozJustin ScottAndrew Agozzino10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Fredrik ClaessonJan Kostalek40122
230122
3William WrennPhilip Samuelsson20122
4Fredrik ClaessonJan Kostalek10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Andrew AgozzinoDennis RasmussenJanne Kuokkanen60122
2Chris BourqueSteven FogartyTyler Randell40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Fredrik ClaessonJan Kostalek60122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Dennis RasmussenAndrew Agozzino60122
2Steven FogartyRod Pelley40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Fredrik ClaessonJan Kostalek60122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Dennis Rasmussen60122Fredrik ClaessonJan Kostalek60122
2Andrew Agozzino4012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Dennis RasmussenAndrew Agozzino60122
2Steven FogartyRod Pelley40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Fredrik ClaessonJan Kostalek60122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Andrew AgozzinoDennis RasmussenJanne KuokkanenFredrik ClaessonJan Kostalek
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Andrew AgozzinoDennis RasmussenJanne KuokkanenFredrik ClaessonJan Kostalek
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mitchell Heard, , Mitchell Heard,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
William Wrenn, Philip Samuelsson, William WrennPhilip Samuelsson,
Tirs de Pénalité
Dennis Rasmussen, Andrew Agozzino, Steven Fogarty, Rod Pelley, Chris Bourque
Gardien
#1 : , #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
1Americans1037000001330-17532000001113-250500000217-1560.3001323360183645092026586766914024457143224771114.29%681380.88%01168238349.01%1069210150.88%563111350.58%187513211829548897444
2Bears2020000027-51010000013-21010000014-300.0002460083645096865867669140591739541218.33%13376.92%01168238349.01%1069210150.88%563111350.58%187513211829548897444
3Bruins211000007701010000035-21100000042220.500791600836450957658676691405513284212433.33%13469.23%01168238349.01%1069210150.88%563111350.58%187513211829548897444
4Checkers440000002381522000000123922000000115681.00023386100836450919965867669140114343510811218.18%90100.00%01168238349.01%1069210150.88%563111350.58%187513211829548897444
5Crunch1236021003037-76230100016160613011001421-7110.458305484018364509239658676691402878117523977810.39%78988.46%21168238349.01%1069210150.88%563111350.58%187513211829548897444
6Devils816000101636-2040300010720-1341300000916-740.25016254100836450916765867669140195609514561813.11%431076.74%01168238349.01%1069210150.88%563111350.58%187513211829548897444
7Marlies660000003611253300000016793300000020416121.00036599501836450928665867669140147455916430413.33%27485.19%11168238349.01%1069210150.88%563111350.58%187513211829548897444
8Monsters40300001616-102010000126-420200000410-610.1256111700836450977658676691401062965702229.09%27677.78%01168238349.01%1069210150.88%563111350.58%187513211829548897444
9Penguins2010000147-31000000145-11010000002-210.250471100836450951658676691404013273517211.76%9366.67%01168238349.01%1069210150.88%563111350.58%187513211829548897444
10Phantoms2110000046-2110000002111010000025-320.500481200836450950658676691406817403014214.29%14192.86%01168238349.01%1069210150.88%563111350.58%187513211829548897444
11Rocket804020111625-940201001712-540201010913-470.43816274300836450917565867669140188641141894748.51%43783.72%01168238349.01%1069210150.88%563111350.58%187513211829548897444
12Senators614001001123-1230200100311-831200000812-430.25011203100836450913965867669140164438712341717.07%35877.14%01168238349.01%1069210150.88%563111350.58%187513211829548897444
13Sound Tigers2020000027-51010000004-41010000023-100.000235008364509546586766914033627451500.00%10370.00%01168238349.01%1069210150.88%563111350.58%187513211829548897444
14Thunderbirds4210010017134210001009452110000089-150.6251730470183645091426586766914012948799711436.36%26196.15%11168238349.01%1069210150.88%563111350.58%187513211829548897444
Total76243904333204244-4038141602213102113-1138102302120102131-29680.4472043485520483645092049658676691401913563105516444646313.58%4337881.99%51168238349.01%1069210150.88%563111350.58%187513211829548897444
16Wolf Pack4210001017116220000009362010001088060.750173047008364509143658676691408436427917423.53%18666.67%11168238349.01%1069210150.88%563111350.58%187513211829548897444
_Since Last GM Reset76243904333204244-4038141602213102113-1138102302120102131-29680.4472043485520483645092049658676691401913563105516444646313.58%4337881.99%51168238349.01%1069210150.88%563111350.58%187513211829548897444
_Vs Conference32151202111105871816940110155391616680101050482380.5941051772820383645091004658676691408222484307821762514.20%1732585.55%21168238349.01%1069210150.88%563111350.58%187513211829548897444

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7668OTW1204348552204919135631055164404
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7624394333204244
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3814162213102113
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3810232120102131
Derniers 10 Matchs
WLOTWOTL SOWSOL
341101
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4646313.58%4337881.99%5
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
658676691408364509
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
1168238349.01%1069210150.88%563111350.58%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
187513211829548897444


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
3 - 2018-09-071Marlies3Comets6WSommaire du Match
4 - 2018-09-0812Senators5Comets1LSommaire du Match
10 - 2018-09-1433Checkers2Comets7WSommaire du Match
11 - 2018-09-1545Comets6Marlies1WSommaire du Match
12 - 2018-09-1660Comets6Marlies3WSommaire du Match
15 - 2018-09-1963Americans4Comets0LSommaire du Match
17 - 2018-09-2172Monsters3Comets0LSommaire du Match
18 - 2018-09-2285Comets3Crunch5LSommaire du Match
22 - 2018-09-26104Checkers1Comets5WSommaire du Match
24 - 2018-09-28111Comets1Americans3LSommaire du Match
31 - 2018-10-05147Comets2Rocket5LSommaire du Match
32 - 2018-10-06153Comets3Rocket2WXXSommaire du Match
36 - 2018-10-10176Rocket2Comets1LXXSommaire du Match
38 - 2018-10-12181Wolf Pack1Comets5WSommaire du Match
39 - 2018-10-13199Comets1Devils4LSommaire du Match
43 - 2018-10-17218Comets3Senators5LSommaire du Match
45 - 2018-10-19224Crunch4Comets3LSommaire du Match
46 - 2018-10-20237Comets5Wolf Pack4WXXSommaire du Match
50 - 2018-10-24259Rocket3Comets1LSommaire du Match
52 - 2018-10-26270Comets0Americans6LSommaire du Match
53 - 2018-10-27279Senators5Comets2LSommaire du Match
57 - 2018-10-31304Comets2Devils6LSommaire du Match
59 - 2018-11-02309Comets3Senators1WSommaire du Match
60 - 2018-11-03319Comets1Rocket4LSommaire du Match
64 - 2018-11-07344Comets1Americans3LSommaire du Match
66 - 2018-11-09349Thunderbirds4Comets3LXSommaire du Match
67 - 2018-11-10370Comets0Devils5LSommaire du Match
71 - 2018-11-14383Bruins5Comets3LSommaire du Match
73 - 2018-11-16391Devils6Comets1LSommaire du Match
75 - 2018-11-18415Comets5Checkers3WSommaire du Match
77 - 2018-11-20423Comets6Checkers2WSommaire du Match
80 - 2018-11-23440Comets4Thunderbirds8LSommaire du Match
81 - 2018-11-24458Devils7Comets1LSommaire du Match
86 - 2018-11-29472Devils5Comets2LSommaire du Match
87 - 2018-11-30476Comets1Crunch5LSommaire du Match
88 - 2018-12-01490Americans4Comets1LSommaire du Match
92 - 2018-12-05511Crunch5Comets3LSommaire du Match
95 - 2018-12-08531Comets2Monsters5LSommaire du Match
96 - 2018-12-09545Comets2Monsters5LSommaire du Match
99 - 2018-12-12552Comets8Marlies0WSommaire du Match
101 - 2018-12-14562Sound Tigers4Comets0LSommaire du Match
102 - 2018-12-15577Crunch3Comets2LSommaire du Match
106 - 2018-12-19596Crunch1Comets3WSommaire du Match
108 - 2018-12-21606Devils2Comets3WXXSommaire du Match
109 - 2018-12-22621Senators1Comets0LXSommaire du Match
115 - 2018-12-28661Comets0Americans2LSommaire du Match
122 - 2019-01-04685Comets2Crunch0WSommaire du Match
123 - 2019-01-05704Comets4Thunderbirds1WSommaire du Match
129 - 2019-01-11723Phantoms1Comets2WSommaire du Match
130 - 2019-01-12740Americans3Comets5WSommaire du Match
131 - 2019-01-13748Comets2Sound Tigers3LSommaire du Match
134 - 2019-01-16764Rocket2Comets3WXSommaire du Match
137 - 2019-01-19787Comets0Penguins2LSommaire du Match
138 - 2019-01-20799Monsters3Comets2LXXSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25818Americans0Comets2WSommaire du Match
144 - 2019-01-26835Comets6Devils1WSommaire du Match
148 - 2019-01-30852Americans2Comets3WSommaire du Match
150 - 2019-02-01857Bears3Comets1LSommaire du Match
151 - 2019-02-02875Comets2Phantoms5LSommaire du Match
155 - 2019-02-06890Crunch1Comets2WSommaire du Match
157 - 2019-02-08897Comets4Crunch3WXSommaire du Match
158 - 2019-02-09910Comets3Rocket2WXSommaire du Match
162 - 2019-02-13938Comets0Americans3LSommaire du Match
164 - 2019-02-15944Thunderbirds0Comets6WSommaire du Match
165 - 2019-02-16957Wolf Pack2Comets4WSommaire du Match
169 - 2019-02-20979Comets2Senators6LSommaire du Match
171 - 2019-02-22984Rocket5Comets2LSommaire du Match
172 - 2019-02-23997Comets4Crunch5LXSommaire du Match
178 - 2019-03-011029Marlies3Comets4WSommaire du Match
179 - 2019-03-021043Comets0Crunch3LSommaire du Match
185 - 2019-03-081074Marlies1Comets6WSommaire du Match
186 - 2019-03-091088Comets3Wolf Pack4LSommaire du Match
187 - 2019-03-101101Comets4Bruins2WSommaire du Match
192 - 2019-03-151116Penguins5Comets4LXXSommaire du Match
193 - 2019-03-161129Comets1Bears4LSommaire du Match
194 - 2019-03-171147Crunch2Comets3WXSommaire 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
6,479,760$ 98,500$ 58,458$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 79,763$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 33,497$ 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
1376243904333204244-4038141602213102113-1138102302120102131-29682043485520483645092049658676691401913563105516444646313.58%4337881.99%51168238349.01%1069210150.88%563111350.58%187513211829548897444
Total Saison Régulière76243904333204244-4038141602213102113-1138102302120102131-29682043485520483645092049658676691401913563105516444646313.58%4337881.99%51168238349.01%1069210150.88%563111350.58%187513211829548897444