Heat

GP: 4 | W: 3 | L: 1 | OTL: 0 | P: 6
GF: 21 | GA: 7 | PP%: 25.00% | PK%: 78.57%
DG: Martin Thibault | Morale : 52 | Moyenne d'Équipe : N/A
Prochain matchs #92 vs Barracuda
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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
1Andy AndreoffX100.0092555873797273696464646655777715300
2Mike Vecchione (R)X100.0072557672696869605060625555505015300
3Teddy Blueger (R)X100.0071556562686469605060606055505015300
4Bobby ButlerX100.0058556755607269555055555555717115300
5Mario Lucia (R)X100.0056555555555555555055555555505015300
6Dominic Toninato (R)X100.0056555555565757556455556455727115300
7Henri IkonenX100.0065557164676274555055555655505015300
8Nick PaulX100.0085557366797272635060616155505015300
9Juho Lammikko (R)X100.0056555555555655555055555555505015300
10Reid Gardiner (R)X100.0056556361686665555055555555505015300
11Josh HennessyX100.0055555555555555555055555555505015300
12Alan QuineXXX100.0084557875786971666862606755777515300
13Colin SmithX100.0060556571647173635060626155717515300
14Mikhail GrigorenkoXX100.0055555555555555555055555555717015100
15Nail YakupovXX100.0075557686797379765067727255767115100
16Michael MerschX100.0056555555555555555055555555505015300
17Sena AcolatseX100.0055555560555568552555555555535315300
Rayé
MOYENNE D'ÉQUIPE100.006555636365636659515858595560601530
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
1Alexandar Georgiev (R)100.007266636680645571807255606015300
2Scott Wedgewood100.007088617789698680747155757015300
3Robin Lehner100.008587808685838284838055868415400
Rayé
1Michael McNiven (R)100.005169867946525056484855505514600
MOYENNE D'ÉQUIPE100.00707873777567687371685568671520
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Craig Ramsay55466262967165CAN655100,000$


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
1Andy AndreoffHeat (Cal)LW4437610013182362217.39%69122.981124110002201061.67%6000011.5200000101
2Alan QuineHeat (Cal)C/LW/RW42577402121931110.53%39423.610003110001201069.09%5500001.4800000020
3Colin SmithHeat (Cal)C416762037157106.67%28822.220110110110100070.42%7100001.5800000100
4Nick PaulHeat (Cal)LW4336660962581212.00%17719.371125110000110050.00%200001.5500000000
5Mike VecchioneHeat (Cal)C41344604483612.50%17819.6001129000000063.64%2200001.0200000001
6Bobby ButlerHeat (Cal)RW41345001064316.67%05213.160111120000000100.00%500001.5200000010
7Dominic ToninatoHeat (Cal)C42245001972628.57%15513.9900013000060069.81%5300001.4300000100
8Henri IkonenHeat (Cal)LW413442015102410.00%15213.11000000000000100.00%400001.5300000000
9Reid GardinerHeat (Cal)RW41345000416756.25%06516.450112110000010100.00%600001.2200000000
10Josh HennessyHeat (Cal)RW41344203253620.00%15213.1100000000000075.00%400001.5300000001
11Sena AcolatseHeat (Cal)D4134814020473414.29%58822.0411229000010010.00%000000.9100000000
12Teddy BluegerHeat (Cal)C42134605731966.67%27318.2511229000000062.50%1600000.8200000000
13Nail YakupovHeat (Cal)LW/RW3011-1007109780.00%07424.940005170000110033.33%300000.2700000001
14Mario LuciaHeat (Cal)LW4000000020000.00%2164.18000000000130066.67%1500000.0000000000
15Juho LammikkoHeat (Cal)LW4000100014010.00%0215.360000000002000.00%000000.0000000000
16Mikhail GrigorenkoHeat (Cal)C/LW3000100021110.00%0268.81000000000000100.00%100000.0000000000
17Michael MerschHeat (Cal)C4000000110000.00%0215.4300001000000064.29%1400000.0000000000
Stats d'équipe Total ou en Moyenne662039596552070941585710812.66%25103215.6548122712001131073168.28%33100011.1400000334
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
1Alexandar GeorgievHeat (Cal)43100.9361.762390171100000.000040001
2Robin LehnerHeat (Cal)31110.8892.31182007630000.000030010
Stats d'équipe Total ou en Moyenne74210.9191.9942201141730000.000070011


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 Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Alan QuineHeat (Cal)C/LW/RW231993-02-24No196 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Alexandar GeorgievHeat (Cal)G201996-02-10Yes176 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Andy AndreoffHeat (Cal)LW251991-05-16No207 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Bobby ButlerHeat (Cal)RW291987-04-25No190 Lbs6 ft0NoNoNo4Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Colin SmithHeat (Cal)C231993-06-20No175 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Dominic ToninatoHeat (Cal)C221994-05-09Yes165 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Henri IkonenHeat (Cal)LW221994-04-17No184 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Josh HennessyHeat (Cal)RW311985-02-07No190 Lbs6 ft0NoNoNo4Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Juho LammikkoHeat (Cal)LW201996-01-29Yes203 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Mario LuciaHeat (Cal)LW231993-08-25Yes201 Lbs6 ft3NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Michael McNivenHeat (Cal)G191997-07-09Yes216 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Michael MerschHeat (Cal)C251992-01-10No198 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Mike VecchioneHeat (Cal)C231993-02-25Yes194 Lbs5 ft10NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Mikhail GrigorenkoHeat (Cal)C/LW221994-05-15No209 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm1,000,000$0$0$No
Nail YakupovHeat (Cal)LW/RW231993-10-05No197 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No500,000$
Nick PaulHeat (Cal)LW211995-03-20No203 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Reid GardinerHeat (Cal)RW201996-01-18Yes193 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Robin LehnerHeat (Cal)G251991-07-23No225 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm2,500,000$0$0$No2,500,000$
Scott WedgewoodHeat (Cal)G241992-08-13No195 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Sena AcolatseHeat (Cal)D261990-11-27No210 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Teddy BluegerHeat (Cal)C221994-08-15Yes185 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2123.24196 Lbs6 ft12.52504,762$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Andy AndreoffAlan QuineBobby Butler40122
2Nick PaulColin SmithReid Gardiner30122
3Henri IkonenMike VecchioneJosh Hennessy20122
4Juho LammikkoTeddy BluegerAndy Andreoff10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sena Acolatse40122
2Mike VecchioneTeddy Blueger30122
3Sena Acolatse20122
4Alan QuineColin Smith10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Andy AndreoffAlan QuineBobby Butler60122
2Nick PaulColin SmithReid Gardiner40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sena Acolatse60122
2Mike VecchioneTeddy Blueger40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Andy AndreoffAlan Quine60122
2Colin SmithNick Paul40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sena Acolatse60122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Andy Andreoff60122Sena Acolatse60122
2Alan Quine4012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Andy AndreoffAlan Quine60122
2Colin SmithNick Paul40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sena Acolatse60122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Juho LammikkoMike VecchioneBobby ButlerSena Acolatse
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Andy AndreoffAlan QuineBobby ButlerSena Acolatse
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dominic Toninato, Michael Mersch, Mario LuciaDominic Toninato, Michael MerschMario Lucia
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Sena Acolatse, Sena Acolatse,
Tirs de Pénalité
Andy Andreoff, Alan Quine, Colin Smith, Nick Paul, Mike Vecchione
Gardien
#1 : Alexandar Georgiev, #2 : Scott Wedgewood


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
1Barracuda1010000034-11010000034-10000000000000.000369009750235053460421724154250.00%12375.00%09413171.76%7912861.72%516875.00%1168879234423
2Condors11000000523000000000001100000052321.000591400975037505346023818167228.57%9277.78%09413171.76%7912861.72%516875.00%1168879234423
3Reign2200000013112110000005051100000081741.0001324370197508950534604581840500.00%7185.71%19413171.76%7912861.72%516875.00%1168879234423
Total431000002171421100000844220000001331060.750213960019750149505346011033607116425.00%28678.57%19413171.76%7912861.72%516875.00%1168879234423
_Since Last GM Reset431000002171421100000844220000001331060.750213960019750149505346011033607116425.00%28678.57%19413171.76%7912861.72%516875.00%1168879234423
_Vs Conference11000000523000000000001100000052321.000591400975037505346023818167228.57%9277.78%09413171.76%7912861.72%516875.00%1168879234423

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
46L121396014911033607101
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4310000217
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
211000084
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2200000133
Derniers 10 Matchs
WLOTWOTL SOWSOL
310000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
16425.00%28678.57%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
50534609750
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
9413171.76%7912861.72%516875.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1168879234423


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 - 2018-09-078Heat5Condors2WSommaire du Match
4 - 2018-09-0820Reign0Heat5WSommaire du Match
10 - 2018-09-1441Heat8Reign1WSommaire du Match
11 - 2018-09-1556Barracuda4Heat3LSommaire du Match
18 - 2018-09-2292Barracuda-Heat-
19 - 2018-09-2399Heat-Barracuda-
24 - 2018-09-28117Heat-Gulls-
25 - 2018-09-29129Heat-Condors-
29 - 2018-10-03138Condors-Heat-
32 - 2018-10-06163Rampage-Heat-
34 - 2018-10-08172Heat-Barracuda-
38 - 2018-10-12191Reign-Heat-
40 - 2018-10-14210Heat-Reign-
42 - 2018-10-16213Heat-Eagles-
43 - 2018-10-17222Heat-Eagles-
45 - 2018-10-19234Roadrunners-Heat-
49 - 2018-10-23255Heat-Roadrunners-
50 - 2018-10-24262Heat-Roadrunners-
52 - 2018-10-26276Heat-Gulls-
54 - 2018-10-28297Gulls-Heat-
56 - 2018-10-30299Heat-Barracuda-
59 - 2018-11-02317Reign-Heat-
60 - 2018-11-03329Barracuda-Heat-
66 - 2018-11-09361Moose-Heat-
67 - 2018-11-10373Moose-Heat-
74 - 2018-11-17413Condors-Heat-
78 - 2018-11-21433Condors-Heat-
80 - 2018-11-23445Heat-Wild-
81 - 2018-11-24461Heat-Wild-
87 - 2018-11-30485Heat-Roadrunners-
88 - 2018-12-01497Heat-Roadrunners-
90 - 2018-12-03509Barracuda-Heat-
94 - 2018-12-07530Roadrunners-Heat-
95 - 2018-12-08543Eagles-Heat-
99 - 2018-12-12559Gulls-Heat-
102 - 2018-12-15585Reign-Heat-
103 - 2018-12-16591Heat-Barracuda-
106 - 2018-12-19603Heat-Condors-
108 - 2018-12-21615Heat-Condors-
109 - 2018-12-22628Stars-Heat-
111 - 2018-12-24640Eagles-Heat-
114 - 2018-12-27654Heat-Rampage-
115 - 2018-12-28664Heat-Stars-
122 - 2019-01-04696Barracuda-Heat-
123 - 2019-01-05698Heat-Barracuda-
129 - 2019-01-11731Heat-Eagles-
130 - 2019-01-12746Heat-Eagles-
134 - 2019-01-16768Heat-Condors-
137 - 2019-01-19791Eagles-Heat-
138 - 2019-01-20803Eagles-Heat-
141 - 2019-01-23812Heat-Reign-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
145 - 2019-01-27845Barracuda-Heat-
150 - 2019-02-01867Gulls-Heat-
151 - 2019-02-02879Gulls-Heat-
155 - 2019-02-06894Heat-Gulls-
157 - 2019-02-08909Condors-Heat-
159 - 2019-02-10930Heat-Barracuda-
164 - 2019-02-15953Roadrunners-Heat-
165 - 2019-02-16965Roadrunners-Heat-
171 - 2019-02-22992Wild-Heat-
173 - 2019-02-241015Wild-Heat-
179 - 2019-03-021052Heat-Gulls-
180 - 2019-03-031057Heat-Reign-
186 - 2019-03-091084Heat-Moose-
187 - 2019-03-101099Heat-Moose-
190 - 2019-03-131113Reign-Heat-
192 - 2019-03-151126Heat-Reign-
194 - 2019-03-171150Condors-Heat-



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
32 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
12,189$ 106,000$ 28,940$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 4,959$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 180 1,062$ 191,160$




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
1343100000217142110000084422000000133106213960019750149505346011033607116425.00%28678.57%19413171.76%7912861.72%516875.00%1168879234423
Total Saison Régulière43100000217142110000084422000000133106213960019750149505346011033607116425.00%28678.57%19413171.76%7912861.72%516875.00%1168879234423
Séries
12514000001021-112020000038-531200000713-62101828004240115383938011729789127311.11%37975.68%08815855.70%7613655.88%487762.34%10874131396026
12514000001021-112020000038-531200000713-62101828004240115383938011729789127311.11%37975.68%08815855.70%7613655.88%487762.34%10874131396026
Total Séries1028000002042-2240400000616-10624000001426-12420365600848023076787602345815618254611.11%741875.68%017631655.70%15227255.88%9615462.34%2161482627912053