Ailes Rouges

GP: 15 | W: 3 | L: 10 | T: 1 | P: 8
GF: 41 | GA: 58 | PP%: 12.50% | PK%: 79.31%
DG: Jérémy Côté | Morale : 42 | Moyenne d'Équipe : 64
Prochain matchs #106 vs As
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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
1Keith PrimeauX100.007156657179747372687878707339348945680
2Nelson EmersonX100.006348717270757572687473667238376046660
3Tom FergusX100.006759566373727167617070766671682441660
4Dan VinceletteX100.008175406576616369647467756340486047650
5Stephane MorinX100.006455586671676774677667676255417646640
6Chris KontosX100.006751726773757461586071636972793146640
7Ken McRaeX100.007269426974646666616863696035566846630
8Scott PearsonX100.006749726876656566627065726232327546630
9Joey KocurX100.009388305778666858566462776058524046630
10Todd EwenX100.007567505880656862586461756047475346620
11Dwayne NorrisX100.005748697469677067636967656529318146620
12Rusty FitzgeraldX100.006050737072595966636960635632369646600
13Randy MollerX100.008778486177788058566342744072733143670
14David ShawX100.006756616177727360546252814867704146660
15Kerry HuffmanX100.005846726776757466637350814853586846660
16Tommy SjodinX100.005846716673666875687966726041434835640
17Brad BombadirX100.006958606377676961576749794533349646630
18Tommy AlbelinX100.006946886475676962606646784434424038630
Rayé
1Tony TwistX100.009379426080666854556452715040366835590
2Steven RiceX100.006556706378555658675961646234339035580
3Jason RuffX100.006563556476585963535765546238378135570
4Ken KleeX100.006548786478727464546061775527329027630
5Bryan FogartyX100.005144767372646866606651734936377435620
MOYENNE D'ÉQUIPE100.00695862657567696561676171584446644263
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
1Ron Tugnutt100.00818477747871858781787838426040730
2Stephane Beauregard100.00727684818176818179787543486741730
Rayé
1Jimmy Waite100.00727575747457687767727037377535650
MOYENNE D'ÉQUIPE100.0075787976786878827676743942673970
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Keenan73757664889083CAN43295,000$


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
1Keith PrimeauAiles Rouges (DET)C157613-5115164141114117.07%336024.0521311600002700049.45%45300000.7200001102
2Dan VinceletteAiles Rouges (DET)LW154812-3275471433122512.12%326617.740229580111420040.00%2000000.9000001100
3Tom FergusAiles Rouges (DET)C154711-32552042509328.00%230820.5814515540001640049.18%30500000.7100000011
4Igor KravchukRed WingsD13189-660221258134.00%1632224.820331647000059000.00%000000.5600000000
5Nelson EmersonAiles Rouges (DET)RW15459-38001634102811.76%327018.0211211621012401044.26%6100000.6700000010
6Ken McRaeAiles Rouges (DET)RW15459-3100411229152313.79%224716.52314555000000019.05%2100000.7300000001
7David ShawAiles Rouges (DET)D15178-72403615213154.76%1833222.170221056000054000.00%000000.4800000000
8Randy MollerAiles Rouges (DET)D13257564205110144214.29%1529522.751011052000050100.00%000000.4700112100
9Kerry HuffmanAiles Rouges (DET)D1516701001319208135.00%2533322.221231658000065000.00%000000.4200000001
10Joey KocurAiles Rouges (DET)RW152460180353188511.11%321014.06000000000150247.83%2300000.5700000110
11Tommy SjodinAiles Rouges (DET)D1533611201211182916.67%1423715.81000621000019000.00%000000.5100000000
12Stephane MorinAiles Rouges (DET)C15145100135236194.35%121814.53000030000120055.41%23100000.4600000001
13Scott PearsonAiles Rouges (DET)LW153140000122661911.54%422214.85000000001261050.00%1200000.3600000010
14Rusty FitzgeraldAiles Rouges (DET)C15213-12001171528.57%0805.3800000000070044.90%9800000.7400000000
15Brad BombadirAiles Rouges (DET)D15033-616034115260.00%1322815.2500023011025000.00%000000.2600000000
16Chris KontosAiles Rouges (DET)LW15123-300414203215.00%225016.71000357000010040.00%2000000.2400000000
17Todd EwenAiles Rouges (DET)RW151010408464716.67%0785.2000004000000046.15%1300000.2600000000
18Dwayne NorrisAiles Rouges (DET)RW15011-200123320.00%0392.6401125000000041.67%1200000.5000000000
19Ken KleeAiles Rouges (DET)D2000000310000.00%22613.110000000001000.00%000000.0000000000
20Tommy AlbelinAiles Rouges (DET)D2000-320110000.00%63316.860000100005000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne2704176117-382393532529539311528510.43%132436416.169172611660512375643248.94%126900000.5400114446
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
1Ron TugnuttAiles Rouges (DET)143910.8823.5680900484060020.0000132000
2Stephane BeauregardAiles Rouges (DET)30200.8465.1194008520000.0000213000
Stats d'équipe Total ou en Moyenne1731110.8783.7290300564580020.00001515000


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
Brad BombadirAiles Rouges (DET)D211999-02-09 9:08:37 PMNo205 Lbs6 ft1NoNoNo1Pro & Farm250,000$25,000$20,588$No
Bryan FogartyAiles Rouges (DET)D241996-02-09 9:08:37 PMNo185 Lbs6 ft0NoNoNo1Pro & Farm350,000$35,000$28,824$No
Chris KontosAiles Rouges (DET)LW301990-02-09 9:08:37 PMNo195 Lbs6 ft1NoNoNo2Pro & Farm520,000$52,000$42,824$No520,000$
Dan VinceletteAiles Rouges (DET)LW261994-02-09 9:08:37 PMNo200 Lbs6 ft2NoNoNo2Pro & Farm485,000$48,500$39,941$No485,000$
David ShawAiles Rouges (DET)D291991-02-09 9:08:37 PMNo204 Lbs6 ft2NoNoNo1Pro & Farm225,000$22,500$18,529$No
Dwayne NorrisAiles Rouges (DET)RW231997-02-09 9:08:37 PMNo175 Lbs5 ft10NoNoNo3Pro & Farm402,000$40,200$33,106$No402,000$402,000$
Jason RuffAiles Rouges (DET)LW231997-02-09 9:08:37 PMNo203 Lbs6 ft2NoNoNo1Pro & Farm311,000$31,100$25,612$No
Jimmy WaiteAiles Rouges (DET)G241996-02-09 9:08:37 PMNo180 Lbs6 ft1NoNoNo1Pro & Farm380,000$38,000$31,294$No
Joey KocurAiles Rouges (DET)RW291991-02-09 9:08:37 PMNo220 Lbs6 ft0NoNoNo1Pro & Farm360,000$36,000$29,647$No
Keith PrimeauAiles Rouges (DET)C221998-02-09 9:08:37 PMNo212 Lbs6 ft4NoNoNo2Pro & Farm500,000$50,000$41,176$No500,000$
Ken KleeAiles Rouges (DET)D221998-02-09 9:08:37 PMNo212 Lbs6 ft1NoNoNo1Pro & Farm250,000$25,000$20,588$No
Ken McRaeAiles Rouges (DET)RW251995-02-09 9:08:37 PMNo195 Lbs6 ft1NoNoNo2Pro & Farm375,000$37,500$30,882$No375,000$
Kerry HuffmanAiles Rouges (DET)D251995-02-09 9:08:37 PMNo202 Lbs6 ft2NoNoNo3Pro & Farm650,000$65,000$53,529$No650,000$650,000$
Nelson EmersonAiles Rouges (DET)RW261994-02-09 9:08:37 PMNo175 Lbs5 ft11NoNoNo1Pro & Farm640,000$64,000$52,706$No
Randy MollerAiles Rouges (DET)D301990-02-09 9:08:37 PMNo205 Lbs6 ft2NoNoNo1Pro & Farm275,000$27,500$22,647$No
Ron TugnuttAiles Rouges (DET)G261994-02-09 9:08:37 PMNo156 Lbs5 ft11NoNoNo2Pro & Farm720,000$72,000$59,294$No720,000$
Rusty FitzgeraldAiles Rouges (DET)C211999-02-09 9:08:37 PMNo185 Lbs6 ft1NoNoNo1Pro & Farm275,000$27,500$22,647$No
Scott PearsonAiles Rouges (DET)LW241996-02-09 9:08:37 PMNo205 Lbs6 ft1NoNoNo3Pro & Farm400,000$40,000$32,941$No400,000$400,000$
Stephane BeauregardAiles Rouges (DET)G251995-02-09 9:08:37 PMNo190 Lbs5 ft11NoNoNo1Pro & Farm530,000$53,000$43,647$No
Stephane MorinAiles Rouges (DET)C241996-02-09 9:08:37 PMNo175 Lbs6 ft1NoNoNo3Pro & Farm499,000$49,900$41,094$No499,000$499,000$
Steven RiceAiles Rouges (DET)RW221998-02-09 9:08:37 PMNo223 Lbs6 ft0NoNoNo1Pro & Farm450,000$45,000$37,059$No
Todd EwenAiles Rouges (DET)RW271993-02-09 9:08:37 PMNo230 Lbs6 ft3NoNoNo3Pro & Farm335,000$33,500$27,588$No335,000$335,000$
Tom FergusAiles Rouges (DET)C311989-02-09 9:08:37 PMNo200 Lbs6 ft0NoNoNo1Pro & Farm450,000$45,000$37,059$No
Tommy AlbelinAiles Rouges (DET)D291991-02-09 9:08:37 PMNo202 Lbs6 ft1NoNoNo1Pro & Farm300,000$30,000$24,706$No
Tommy SjodinAiles Rouges (DET)D281992-02-09 9:08:37 PMNo195 Lbs6 ft0NoNoNo2Pro & Farm580,000$58,000$47,765$No580,000$
Tony TwistAiles Rouges (DET)LW251995-02-09 9:08:37 PMNo230 Lbs6 ft1NoNoNo1Pro & Farm225,000$22,500$18,529$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2625.42198 Lbs6 ft11.62412,962$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Dan VinceletteKeith PrimeauNelson Emerson35122
2Chris KontosTom FergusKen McRae30122
3Scott PearsonStephane MorinJoey Kocur20122
4Keith PrimeauRusty FitzgeraldDwayne Norris15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Randy MollerDavid Shaw35122
2Kerry HuffmanTommy Sjodin30122
3Brad BombadirTommy Albelin20122
4Randy MollerDavid Shaw15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Dan VinceletteKeith PrimeauNelson Emerson60122
2Chris KontosTom FergusKen McRae40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Randy MollerDavid Shaw60122
2Kerry HuffmanTommy Sjodin40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Keith PrimeauTom Fergus60122
2Nelson EmersonDan Vincelette40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Randy MollerDavid Shaw60122
2Kerry HuffmanTommy Sjodin40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Keith Primeau60122Randy MollerDavid Shaw60122
2Tom Fergus40122Kerry HuffmanTommy Sjodin40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Keith PrimeauTom Fergus60122
2Nelson EmersonDan Vincelette40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Randy MollerDavid Shaw60122
2Kerry HuffmanTommy Sjodin40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Dan VinceletteKeith PrimeauNelson EmersonRandy MollerDavid Shaw
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Dan VinceletteKeith PrimeauNelson EmersonRandy MollerDavid Shaw
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Todd Ewen, Stephane Morin, Scott PearsonTodd Ewen, Stephane MorinScott Pearson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brad Bombadir, Tommy Albelin, Kerry HuffmanBrad BombadirTommy Albelin, Kerry Huffman
Tirs de Pénalité
Keith Primeau, Tom Fergus, Nelson Emerson, Dan Vincelette, Stephane Morin
Gardien
#1 : Ron Tugnutt, #2 : Stephane Beauregard


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
1As21000100761000000000002100010076130.750714210016141107811413913914714384416318.75%7357.14%024050048.00%26753749.72%11423249.14%34222436811819497
2Banshees2011000057-22011000057-20000000000010.2505914001614110451141391391531437426116.67%12191.67%024050048.00%26753749.72%11423249.14%34222436811819497
3Chiefs1010000012-1000000000001010000012-100.000112001614110171141391391219624700.00%30100.00%024050048.00%26753749.72%11423249.14%34222436811819497
4Croque-Morts30300000816-81010000058-32020000038-500.000816241016141107911413913919828486113215.38%24866.67%124050048.00%26753749.72%11423249.14%34222436811819497
5Harvard2110000056-12110000056-10000000000020.50059140016141106311413913916622374211218.18%13192.31%024050048.00%26753749.72%11423249.14%34222436811819497
6Pacifiques de la route1010000015-4000000000001010000015-400.00012300161411021114139139141101219500.00%6266.67%024050048.00%26753749.72%11423249.14%34222436811819497
Total15310101004158-17715100002130-9825001002028-880.2674176117201614110393114139139146013223932572912.50%871879.31%124050048.00%26753749.72%11423249.14%34222436811819497
8Wolves413000001416-22020000069-32110000087120.2501425391016141109011413913911343561931417.14%22386.36%024050048.00%26753749.72%11423249.14%34222436811819497
_Since Last GM Reset15410001004158-17715100002130-9835-101002028-890.3004176117201614110393114139139146013223932572912.50%871879.31%124050048.00%26753749.72%11423249.14%34222436811819497
_Vs Conference1027001003043-13303000001117-6724001001926-750.25030578720161411026811413913913208715921748612.50%591672.88%124050048.00%26753749.72%11423249.14%34222436811819497
_Vs Division926001002938-9303000001117-6623001001821-350.27829558420161411024711413913912797714719843613.95%531473.58%124050048.00%26753749.72%11423249.14%34222436811819497

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
158L1417611739346013223932520
Tous les Matchs
GPWLOTWOTL TGFGA
153100114158
Matchs locaux
GPWLOTWOTL TGFGA
7150012130
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
8250102028
Derniers 10 Matchs
WLOTWOTL T
27001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
72912.50%871879.31%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
11413913911614110
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
24050048.00%26753749.72%11423249.14%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
34222436811819497


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 - 2020-09-215Ailes Rouges5Wolves3WSommaire du Match
2 - 2020-09-2210Wolves5Ailes Rouges3LSommaire du Match
4 - 2020-09-2420Ailes Rouges3Wolves4LSommaire du Match
5 - 2020-09-2523Ailes Rouges4As5LXSommaire du Match
6 - 2020-09-2626Croque-Morts8Ailes Rouges5LSommaire du Match
7 - 2020-09-2735Ailes Rouges0Croque-Morts3LSommaire du Match
9 - 2020-09-2941Wolves4Ailes Rouges3LSommaire du Match
10 - 2020-09-3051Harvard3Ailes Rouges1LSommaire du Match
11 - 2020-10-0158Banshees3Ailes Rouges3TXSommaire du Match
14 - 2020-10-0466Ailes Rouges3As1WSommaire du Match
15 - 2020-10-0572Ailes Rouges1Pacifiques de la route5LSommaire du Match
17 - 2020-10-0779Banshees4Ailes Rouges2LSommaire du Match
19 - 2020-10-0986Ailes Rouges1Chiefs2LSommaire du Match
21 - 2020-10-1192Harvard3Ailes Rouges4WSommaire du Match
23 - 2020-10-13100Ailes Rouges3Croque-Morts5LSommaire du Match
25 - 2020-10-15106As-Ailes Rouges-
27 - 2020-10-17114Ailes Rouges-Croque-Morts-
29 - 2020-10-19118Ailes Rouges-Wolves-
31 - 2020-10-21125Harvard-Ailes Rouges-
33 - 2020-10-23134Snipers-Ailes Rouges-
35 - 2020-10-25140Ailes Rouges-Harvard-
37 - 2020-10-27148Croque-Morts-Ailes Rouges-
39 - 2020-10-29156Ailes Rouges-Banshees-
42 - 2020-11-01163Citadelles-Ailes Rouges-
43 - 2020-11-02171Spoonman's-Ailes Rouges-
44 - 2020-11-03177Ailes Rouges-As-
46 - 2020-11-05179Ailes Rouges-Spoonman's-
47 - 2020-11-06190Ailes Rouges-Snipers-
48 - 2020-11-07195Citadelles-Ailes Rouges-
50 - 2020-11-09204Ailes Rouges-Banshees-
52 - 2020-11-11207Spoonman's-Ailes Rouges-
53 - 2020-11-12219Croque-Morts-Ailes Rouges-
55 - 2020-11-14225Ailes Rouges-Canadiens-
56 - 2020-11-15229Ailes Rouges-Riverman-
58 - 2020-11-17238Wolves-Ailes Rouges-
59 - 2020-11-18244Ailes Rouges-Wolves-
61 - 2020-11-20251Isotopes-Ailes Rouges-
62 - 2020-11-21258Ailes Rouges-Riverman-
64 - 2020-11-23263Riverman-Ailes Rouges-
65 - 2020-11-24270Ailes Rouges-Citadelles-
67 - 2020-11-26278Pacifiques de la route-Ailes Rouges-
68 - 2020-11-27286Ailes Rouges-Pacifiques de la route-
70 - 2020-11-29291Ailes Rouges-Spoonman's-
71 - 2020-11-30295Pacifiques de la route-Ailes Rouges-
72 - 2020-12-01304Ailes Rouges-Isotopes-
73 - 2020-12-02308Canadiens-Ailes Rouges-
74 - 2020-12-03317Ailes Rouges-As-
76 - 2020-12-05324Chiefs-Ailes Rouges-
78 - 2020-12-07332Ailes Rouges-Isotopes-
79 - 2020-12-08338Spoonman's-Ailes Rouges-
80 - 2020-12-09349Spoonman's-Ailes Rouges-
83 - 2020-12-12358Pacifiques de la route-Ailes Rouges-
84 - 2020-12-13363Ailes Rouges-As-
86 - 2020-12-15372Snipers-Ailes Rouges-
88 - 2020-12-17373Ailes Rouges-Canadiens-
90 - 2020-12-19384Ailes Rouges-Wolves-
92 - 2020-12-21388Ailes Rouges-Snipers-
94 - 2020-12-23394Canadiens-Ailes Rouges-
96 - 2020-12-25406Isotopes-Ailes Rouges-
98 - 2020-12-27414As-Ailes Rouges-
100 - 2020-12-29415Ailes Rouges-Canadiens-
101 - 2020-12-30427Ailes Rouges-Croque-Morts-
103 - 2021-01-01430Canadiens-Ailes Rouges-
104 - 2021-01-02436Ailes Rouges-Spoonman's-
106 - 2021-01-04447Croque-Morts-Ailes Rouges-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
109 - 2021-01-07453Ailes Rouges-Citadelles-
110 - 2021-01-08460Riverman-Ailes Rouges-
112 - 2021-01-10470Citadelles-Ailes Rouges-
114 - 2021-01-12477Ailes Rouges-Harvard-
115 - 2021-01-13483Ailes Rouges-Isotopes-
116 - 2021-01-14487Harvard-Ailes Rouges-
118 - 2021-01-16495Ailes Rouges-Riverman-
119 - 2021-01-17502Chiefs-Ailes Rouges-
120 - 2021-01-18508Ailes Rouges-Isotopes-
121 - 2021-01-19512Ailes Rouges-Banshees-
122 - 2021-01-20518Chiefs-Ailes Rouges-
123 - 2021-01-21529Ailes Rouges-Snipers-
124 - 2021-01-22531As-Ailes Rouges-
127 - 2021-01-25543As-Ailes Rouges-
130 - 2021-01-28555Wolves-Ailes Rouges-
132 - 2021-01-30563Wolves-Ailes Rouges-
134 - 2021-02-01570Ailes Rouges-Chiefs-



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
34 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
209,515$ 1,073,700$ 1,073,700$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
1,073,700$ 209,515$ 26 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 112 8,593$ 962,416$




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
199315310101004158-17715100002130-9825001002028-884176117201614110393114139139146013223932572912.50%871879.31%124050048.00%26753749.72%11423249.14%34222436811819497
Total Saison Régulière15310101004158-17715100002130-9825001002028-884176117201614110393114139139146013223932572912.50%871879.31%124050048.00%26753749.72%11423249.14%34222436811819497