Roadrunners

GP: 24 | W: 21 | L: 2 | OTL: 1 | P: 43
GF: 123 | GA: 76 | PP%: 30.69% | PK%: 81.55%
DG: Richard Boivin | Morale : 75 | Moyenne d'Équipe : 61
Prochain matchs #411 vs Wolves
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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
1Conor ShearyXX100.005636916864779167596668566573703780640
2Cole SchneiderX100.006437876278918761655961596277795678630
3Brad MaloneX100.007538865784756556685755655378705280610
4Eric TangradiX100.006838865892806557525956615478705980610
5Justin DowlingX100.005835946066837059746356595877794682610
6Brendan WoodsX100.007344685688908555575453595473675880600
7Axel HolmstromX100.006135945874928956635554575965636231590
8Jamie DevaneX100.008146625396787253545152595575685781590
9Ben HolmstromX100.006438865478837752575351565280725331580
10Mike SisloX100.005636905670837754595553575479715480580
11Ryan WhiteX100.007144675574787254535254585479715277580
12Luke WitkowskiX100.008057655282655552555451585277694080570
13Linus Olund (R)X100.005735945571928854565352534963626331570
14Christian JarosX100.008044855984777458306653624865635680640
15Zach TrotmanX100.006839815887796257305853654577694880630
16Matt BartkowskiX100.005736906277817160305860594879714663620
Rayé
MOYENNE D'ÉQUIPE100.00674083587982755754575559547570527060
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
1Michael Leighton100.00717068817069717069717088922533710
Rayé
MOYENNE D'ÉQUIPE100.0071706881706971706971708892253371
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dominique Ducharme73727068696479CAN4651,000,000$


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
1Conor ShearyRoadrunners (PHX)LW/RW242519441414058551604511015.63%1356223.43571230840004863368.33%18000021.5712000722
2Justin DowlingRoadrunners (PHX)C2416193587583799247016.16%739316.3858132571000071075.30%42100001.7800100232
3Cole SchneiderRoadrunners (PHX)LW24142034122152035109388612.84%1350421.017714237101151012071.43%3500011.3512001212
4Ryan WhiteRoadrunners (PHX)RW248233184210561961254313.11%537415.5839121971000001076.19%2100001.6600110104
5Zach TrotmanRoadrunners (PHX)D245232896043275518269.09%3059324.722572875000165000.00%000000.9400000013
6Matt BartkowskiRoadrunners (PHX)D1952227626040155413359.26%3548125.364592567101354010.00%000001.1200000122
7Eric TangradiRoadrunners (PHX)LW24815236195132172175311.11%932813.67022461014621071.43%1400001.4000100211
8Brendan WoodsRoadrunners (PHX)C241271985515463353234822.64%1130412.69000361012343069.50%28200001.2500102111
9Christian JarosRoadrunners (PHX)D24514197240751348152110.42%2658824.533142574000061300.00%000000.6500000231
10Mike SisloRoadrunners (PHX)RW245121792041347103810.64%325710.7401138000002175.00%2000001.3200000010
11Brad MaloneRoadrunners (PHX)C245611610011166016328.33%51948.1002228000001069.84%18900001.1300000010
12Jamie DevaneRoadrunners (PHX)LW2423532551913377225.41%51676.9800000000010070.00%1000000.6000001010
13Luke WitkowskiRoadrunners (PHX)RW24145112019102810273.57%31767.3700000000000080.00%1000000.5700000000
14Ben HolmstromRoadrunners (PHX)C2022-100011140.00%03517.6201101011020085.71%700001.1300000000
15Chris CastoPhoenix CoyotesD1000-100003010.00%02323.100001400002000.00%000000.0000000000
16Axel HolmstromRoadrunners (PHX)C2000040022100.00%0115.7300000000000090.00%1000000.0000000000
17Linus OlundRoadrunners (PHX)C2000000021000.00%0199.9100001000000083.33%600000.0000000000
Stats d'équipe Total ou en Moyenne314111189300952674541231289026361612.47%165501615.982948771885543251948117572.12%120500031.2024414181718
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
1Michael LeightonRoadrunners (PHX)22000.9132.00120004460200.000020000
Stats d'équipe Total ou en Moyenne22000.9132.00120004460200.000020000


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
Axel HolmstromRoadrunners (PHX)C231996-06-29No198 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm500,000$0$0$NoLien
Ben HolmstromRoadrunners (PHX)C321987-04-09No203 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm499,994$0$0$NoLien
Brad MaloneRoadrunners (PHX)C301989-05-20No217 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm499,994$0$0$NoLien
Brendan WoodsRoadrunners (PHX)C271992-06-11No210 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm499,994$0$0$NoLien
Christian JarosRoadrunners (PHX)D231996-04-02No201 Lbs6 ft3NoNoNo3Avec RestrictionPro & Farm500,000$0$0$NoLien
Cole SchneiderRoadrunners (PHX)LW281990-08-26No203 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm499,994$0$0$NoLien
Conor ShearyRoadrunners (PHX)LW/RW271992-06-08No176 Lbs5 ft8NoNoNo1Avec RestrictionPro & Farm1,000,000$0$0$NoLien
Eric TangradiRoadrunners (PHX)LW301989-02-10No226 Lbs6 ft4NoNoNo3Sans RestrictionPro & Farm499,994$0$0$NoLien
Jamie DevaneRoadrunners (PHX)LW281991-02-20No232 Lbs6 ft5NoNoNo2Sans RestrictionPro & Farm499,994$0$0$NoLien
Justin DowlingRoadrunners (PHX)C281990-10-01No180 Lbs5 ft10NoNoNo1Sans RestrictionPro & Farm499,994$0$0$NoLien
Linus OlundRoadrunners (PHX)C221997-06-05Yes185 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Luke WitkowskiRoadrunners (PHX)RW291990-04-14No210 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Matt BartkowskiRoadrunners (PHX)D311988-06-04No198 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Michael LeightonRoadrunners (PHX)G381981-05-19No186 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Mike SisloRoadrunners (PHX)RW311988-01-20No190 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm499,994$0$0$NoLien
Ryan WhiteRoadrunners (PHX)RW311988-03-17No200 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm498,984$0$0$NoLien
Zach TrotmanRoadrunners (PHX)D281990-08-26No217 Lbs6 ft3NoNoNo3Sans RestrictionPro & Farm499,994$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1728.59202 Lbs6 ft12.24517,584$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Conor ShearyJustin DowlingMike Sislo40122
2Cole SchneiderBrad MaloneRyan White30122
3Eric TangradiBrendan WoodsLuke Witkowski20122
4Jamie DevaneAxel HolmstromConor Sheary10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian JarosZach Trotman40122
2Matt BartkowskiEric Tangradi30122
3Christian JarosZach Trotman20122
4Matt BartkowskiCole Schneider10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Conor ShearyJustin DowlingMike Sislo60122
2Cole SchneiderBrad MaloneRyan White40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian JarosZach Trotman60122
2Matt BartkowskiEric Tangradi40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Conor ShearyCole Schneider60122
2Justin DowlingBrad Malone40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian JarosZach Trotman60122
2Matt Bartkowski40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Conor Sheary60122Christian JarosZach Trotman60122
2Cole Schneider40122Matt Bartkowski40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Conor ShearyCole Schneider60122
2Justin DowlingBrad Malone40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian JarosZach Trotman60122
2Matt Bartkowski40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Conor ShearyJustin DowlingMike SisloChristian JarosZach Trotman
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Conor ShearyJustin DowlingMike SisloChristian JarosZach Trotman
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ben Holmstrom, Linus Olund, Brendan WoodsBen Holmstrom, Linus OlundBrendan Woods
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Christian Jaros, Zach Trotman, Matt BartkowskiChristian JarosZach Trotman, Matt Bartkowski
Tirs de Pénalité
Conor Sheary, Cole Schneider, Justin Dowling, Brad Malone, Eric Tangradi
Gardien
#1 : Michael Leighton, #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
1Barracuda30201000915-62010100068-21010000037-420.333917260050442566037031931316902641446116.67%17570.59%052880365.75%35153066.23%25439564.30%754582439135262145
2Condors2100001010730000000000021000010107341.0001016260050442567637031931316601822379333.33%11281.82%152880365.75%35153066.23%25439564.30%754582439135262145
3Eagles440000002111102200000012482200000097281.000213758005044256180370319313169225779424625.00%15193.33%152880365.75%35153066.23%25439564.30%754582439135262145
4Gulls540010002613132200000010373200100016106101.00026507600504425620337031931316128477010920735.00%17476.47%052880365.75%35153066.23%25439564.30%754582439135262145
5Heat320001001082210001007611100000032150.833101626005044256124370319313167626495016425.00%16287.50%052880365.75%35153066.23%25439564.30%754582439135262145
6IceHogs2100001010732100001010730000000000041.0001017270050442569437031931316431220408225.00%9277.78%152880365.75%35153066.23%25439564.30%754582439135262145
7Reign550000003715222200000012663300000025916101.000376710400504425627537031931316133383812718844.44%18383.33%052880365.75%35153066.23%25439564.30%754582439135262145
Total24172021201237647128101110573423129101010664224430.8961232203430050442561012370319313166221923175011013130.69%1031981.55%352880365.75%35153066.23%25439564.30%754582439135262145
_Since Last GM Reset24172021201237647128101110573423129101010664224430.8961232203430050442561012370319313166221923175011013130.69%1031981.55%352880365.75%35153066.23%25439564.30%754582439135262145
_Vs Conference1392020007243296410100028171175101000442618220.8467213420600504425653837031931316351111149280441636.36%521276.92%052880365.75%35153066.23%25439564.30%754582439135262145

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2443W7123220343101262219231750100
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
24172212012376
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
128111105734
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
129110106642
Derniers 10 Matchs
WLOTWOTL SOWSOL
800110
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1013130.69%1031981.55%3
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
370319313165044256
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
52880365.75%35153066.23%25439564.30%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
754582439135262145


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
4 - 2019-09-0523Gulls1Roadrunners3WSommaire du Match
10 - 2019-09-1142Roadrunners6Gulls5WXSommaire du Match
11 - 2019-09-1257Roadrunners4Condors2WSommaire du Match
17 - 2019-09-1881IceHogs3Roadrunners5WSommaire du Match
18 - 2019-09-1995IceHogs4Roadrunners5WXXSommaire du Match
24 - 2019-09-25116Roadrunners8Reign3WSommaire du Match
25 - 2019-09-26130Roadrunners5Gulls3WSommaire du Match
31 - 2019-10-02150Roadrunners5Eagles4WSommaire du Match
32 - 2019-10-03165Roadrunners4Eagles3WSommaire du Match
36 - 2019-10-07178Gulls2Roadrunners7WSommaire du Match
38 - 2019-10-09189Barracuda3Roadrunners4WXSommaire du Match
39 - 2019-10-10203Barracuda5Roadrunners2LSommaire du Match
45 - 2019-10-16234Roadrunners3Heat2WSommaire du Match
46 - 2019-10-17235Roadrunners3Barracuda7LSommaire du Match
49 - 2019-10-20255Heat4Roadrunners3LXSommaire du Match
50 - 2019-10-21262Heat2Roadrunners4WSommaire du Match
53 - 2019-10-24289Roadrunners6Condors5WXXSommaire du Match
54 - 2019-10-25296Roadrunners9Reign3WSommaire du Match
61 - 2019-11-01338Roadrunners8Reign3WSommaire du Match
64 - 2019-11-04348Roadrunners5Gulls2WSommaire du Match
66 - 2019-11-06359Reign2Roadrunners4WSommaire du Match
67 - 2019-11-07374Reign4Roadrunners8WSommaire du Match
70 - 2019-11-10382Eagles3Roadrunners5WSommaire du Match
71 - 2019-11-11389Eagles1Roadrunners7WSommaire du Match
74 - 2019-11-14411Roadrunners-Wolves-
75 - 2019-11-15419Roadrunners-Wolves-
80 - 2019-11-20448Roadrunners-Barracuda-
81 - 2019-11-21462Roadrunners-Barracuda-
87 - 2019-11-27485Heat-Roadrunners-
88 - 2019-11-28497Heat-Roadrunners-
94 - 2019-12-04530Roadrunners-Heat-
95 - 2019-12-05544Roadrunners-Condors-
101 - 2019-12-11571Wolves-Roadrunners-
102 - 2019-12-12586Wolves-Roadrunners-
108 - 2019-12-18613Roadrunners-Eagles-
109 - 2019-12-19629Roadrunners-Eagles-
111 - 2019-12-21642Stars-Roadrunners-
113 - 2019-12-23651Stars-Roadrunners-
115 - 2019-12-25666Condors-Roadrunners-
116 - 2019-12-26669Condors-Roadrunners-
122 - 2020-01-01693Eagles-Roadrunners-
123 - 2020-01-02709Eagles-Roadrunners-
129 - 2020-01-08730Roadrunners-IceHogs-
130 - 2020-01-09744Roadrunners-IceHogs-
133 - 2020-01-12761Roadrunners-Barracuda-
136 - 2020-01-15777Roadrunners-Stars-
137 - 2020-01-16790Roadrunners-Stars-
141 - 2020-01-20813Roadrunners-Gulls-
144 - 2020-01-23838Condors-Roadrunners-
146 - 2020-01-25846Condors-Roadrunners-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
151 - 2020-01-30880Roadrunners-Eagles-
152 - 2020-01-31886Roadrunners-Eagles-
157 - 2020-02-05907Reign-Roadrunners-
158 - 2020-02-06921Reign-Roadrunners-
164 - 2020-02-12953Roadrunners-Heat-
165 - 2020-02-13965Roadrunners-Heat-
168 - 2020-02-16976Wild-Roadrunners-
169 - 2020-02-17983Wild-Roadrunners-
172 - 2020-02-201007Barracuda-Roadrunners-
173 - 2020-02-211014Barracuda-Roadrunners-
178 - 2020-02-261038Eagles-Roadrunners-
179 - 2020-02-271053Eagles-Roadrunners-
182 - 2020-03-011062Roadrunners-Wild-
183 - 2020-03-021069Roadrunners-Wild-
187 - 2020-03-061103Roadrunners-Reign-
190 - 2020-03-091111Roadrunners-Condors-
192 - 2020-03-111127Gulls-Roadrunners-
193 - 2020-03-121141Gulls-Roadrunners-



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
22 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
405,514$ 87,990$ 15,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 34,369$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 5,608$ 684,176$




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
1424172021201237647128101110573423129101010664224431232203430050442561012370319313166221923175011013130.69%1031981.55%352880365.75%35153066.23%25439564.30%754582439135262145
Total Saison Régulière24172021201237647128101110573423129101010664224431232203430050442561012370319313166221923175011013130.69%1031981.55%352880365.75%35153066.23%25439564.30%754582439135262145