Login

Phantoms
GP: 54 | W: 28 | L: 21 | OTL: 5 | P: 61
GF: 167 | GA: 167 | PP%: 22.60% | PK%: 81.48%
GM : Jean-Phillipe Dame | Morale : 50 | Team Overall : 61
Next Games #809 vs Oil Kings
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Game Center
Griffins
32-17-3, 67pts
1
FINAL
2 Phantoms
28-21-5, 61pts
Team Stats
W1StreakOTL1
19-7-1Home Record15-9-3
13-10-2Away Record13-12-2
4-4-2Last 10 Games6-2-2
3.42Goals Per Game3.09
2.88Goals Against Per Game3.09
25.25%Power Play Percentage22.60%
82.19%Penalty Kill Percentage81.48%
Rocket
25-24-5, 55pts
4
FINAL
3 Phantoms
28-21-5, 61pts
Team Stats
OTW1StreakOTL1
12-10-4Home Record15-9-3
13-14-1Away Record13-12-2
4-5-1Last 10 Games6-2-2
2.93Goals Per Game3.09
3.15Goals Against Per Game3.09
17.65%Power Play Percentage22.60%
74.77%Penalty Kill Percentage81.48%
Phantoms
28-21-5, 61pts
2023-01-30
Oil Kings
36-16-2, 74pts
Team Stats
OTL1StreakW5
15-9-3Home Record18-8-0
13-12-2Away Record18-8-2
6-2-2Last 10 Games10-0-0
3.09Goals Per Game3.65
3.09Goals Against Per Game3.65
22.60%Power Play Percentage24.29%
81.48%Penalty Kill Percentage78.69%
Bears
26-23-6, 58pts
2023-02-01
Phantoms
28-21-5, 61pts
Team Stats
L1StreakOTL1
15-7-4Home Record15-9-3
11-16-2Away Record13-12-2
4-6-0Last 10 Games6-2-2
3.18Goals Per Game3.09
2.91Goals Against Per Game3.09
18.37%Power Play Percentage22.60%
77.04%Penalty Kill Percentage81.48%
Americans
24-25-5, 53pts
2023-02-05
Phantoms
28-21-5, 61pts
Team Stats
OTL1StreakOTL1
11-12-3Home Record15-9-3
13-13-2Away Record13-12-2
3-6-1Last 10 Games6-2-2
3.20Goals Per Game3.09
3.20Goals Against Per Game3.09
19.90%Power Play Percentage22.60%
76.14%Penalty Kill Percentage81.48%
Team Leaders
Frederik GauthierGoals
Frederik Gauthier
22
Simon BenoitAssists
Simon Benoit
31
Frederik GauthierPoints
Frederik Gauthier
50
Scott WilsonPlus/Minus
Scott Wilson
11
Erik KallgrenWins
Erik Kallgren
28
Antoine BibeauSave Percentage
Antoine Bibeau
0.922

Team Stats
Goals For
167
3.09 GFG
Shots For
1730
32.04 Avg
Power Play Percentage
22.6%
47 GF
Offensive Zone Start
41.1%
Goals Against
167
3.09 GAA
Shots Against
1728
32.00 Avg
Penalty Kill Percentage
81.5%%
40 GA
Defensive Zone Start
40.8%
Team Info

General ManagerJean-Phillipe Dame
CoachMike Vellucci
DivisionAtlantic
ConferenceCanadian
Captain
Assistant #1
Assistant #2


Arena Info

Capacity3,000
Attendance1,994
Season Tickets0


Roster Info

Pro Team23
Farm Team19
Contract Limit42 / 250
Prospects19


Filter Tips
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
# Player Name C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPAgeContractSalary
1Frederik GauthierX100.00837884639776786085646171586769044660272900,000$
2Fredrik Karlstrom (R)X100.00683892638276886672655861596466050640251800,000$
3Brandon BaddockX100.00858076558772815654575859566769050620291750,000$
4Stefan MatteauX100.00784479598278665771605864566870050620281750,000$
5Connor BunnamanX100.00723893567976875778585963566466050620241750,000$
6Maxim LetunovX100.00733990588278925761546062596668050620261750,000$
7Scott WilsonX100.00593789586987855761565958567072050610301750,000$
8Sven BaertschiXX100.00603683587086725963585956607172050610301750,000$
9Donald Busdeker (R)X100.00573878586681865762605657616365050600231800,000$
10James Hamblin (R)X100.00563679576580825855596156576365050600231800,000$
11Vincent ArseneauX100.00717561568075695554535859567072050600301750,000$
12Jeremy Mckenna (R)X100.00563789546572665354555253576365050570231800,000$
13Radim Simek (R)X100.00863891607583856230615768527072044640301800,000$
14Simon BenoitX100.00864289608480796130625867456466050640242850,000$
15Brinson Pasichnuk (R)X100.00534382617577766230605764516764050610251800,000$
16Trevor CarrickX100.00664173587572905730605659466870050610282750,000$
17Tobie Paquette-Bisson (R)X100.00733984568267825430585357456567050600251800,000$
18Jeremy Groleau (R)X100.00733975538264725130535256456365050580231800,000$
Scratches
1Evan Weinger (R)X100.00613886567377865253565754566567050590251750,000$
2Tyrell GoulbourneX100.00643871547366635257535156526870050570291825,000$
3Jonathan Aspirot (R)X100.00654267587469765730585756456668050600232750,000$
TEAM AVERAGE100.0069458158777679575258576054666804961
Filter Tips
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
# Goalie Name CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SPAgeContractSalary
1Erik Kallgren (R)100.0074858382737274737274736675050650262750,000$
2Antoine Bibeau100.0070676884696870696870696981050630281750,000$
Scratches
TEAM AVERAGE100.007276768371707271707271687805064
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Mike Vellucci68747572837765USA552250,000$


Filter Tips
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
# Player Name Team NamePOSGP 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
1Frederik GauthierPhantoms (Phi)C5022285083951051861985212811.11%29108021.62710174516101191842355.16%162800100.9304100823
2Fredrik KarlstromPhantoms (Phi)C542222440200441591846012111.96%16111320.62411153816900021176251.45%134700010.7914000341
3Radim SimekPhantoms (Phi)D501529443300107105105436214.29%82125125.0281018681710000168230.00%000000.7011000353
4Simon BenoitPhantoms (Phi)D5483139-14401169410835667.41%88134424.9061117611790000170100.00%000000.5801000002
5Scott WilsonPhantoms (Phi)RW541622381160849149469010.74%7113621.0636932170000003141.67%9600000.6711000215
6Brandon BaddockPhantoms (Phi)LW54132033953513954105328512.38%12113220.9855102816800051853029.52%10500000.5814010341
7Connor BunnamanPhantoms (Phi)C54121830-111006611513132979.16%1374513.811126150000712053.91%81800100.8012000211
8Stefan MatteauPhantoms (Phi)LW54101828-648101517115437986.49%13106619.754913331690000913053.73%6700000.5302110012
9Brinson PasichnukPhantoms (Phi)D5472128-17180327810235706.86%84114921.2941014551591121152200.00%000000.4911000100
10Sven BaertschiPhantoms (Phi)LW/RW5461723-81404472110331005.45%973013.520001120000300040.82%4900000.6301000002
11Trevor CarrickPhantoms (Phi)D5461521-157401504560254810.00%59114421.19257341570000141010.00%000000.3701000024
12Tobie Paquette-BissonPhantoms (Phi)D54219211135581463016176.67%6284415.65000313000075000.00%000000.5000001212
13Donald BusdekerPhantoms (Phi)RW5471219-512026499333797.53%494217.4624617159000001039.68%6300000.4001000110
14Jeremy MckennaPhantoms (Phi)RW479413-1560273265203913.85%656912.1200000000001043.48%2300000.4611000010
15Maxim LetunovPhantoms (Phi)C54661238032536516349.23%23937.28101241012250047.16%38800000.6111000010
16Jeremy GroleauPhantoms (Phi)D4711011881156723229134.55%3364013.6400012000011000.00%000000.3400011000
17Vincent ArseneauPhantoms (Phi)LW54055-414041333512310.00%43436.35000000000100050.00%3600000.2911000000
18Evan WeingerPhantoms (Phi)RW1121320084124916.67%2898.1100000000000085.71%700000.6700000010
19James HamblinPhantoms (Phi)C8000-400371130.00%0415.2100000000040041.67%4800000.00%00000000
20Jonathan AspirotPhantoms (Phi)D4000-200850100.00%05814.570000000000000.00%000000.00%00000000
Team Total or Average919164298462-335124012551280172954211909.49%5251582117.2247821294241714224191441261051.79%467500210.58926232252526
Filter Tips
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
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Erik KallgrenPhantoms (Phi)54282050.9043.0231640415916630110.64025540631
2Antoine BibeauPhantoms (Phi)40100.9222.97101005640000.00%0054000
Team Total or Average58282150.9053.013266041641727011255454631


Filter Tips
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
Player Name Team NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Force Waivers Contract Type Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Link
Antoine BibeauPhantoms (Phi)G281994-05-01No213 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Brandon BaddockPhantoms (Phi)LW291993-03-29No218 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Brinson PasichnukPhantoms (Phi)D251997-11-24Yes205 Lbs6 ft0NoNoNo1Pro & Farm800,000$0$0$No
Connor BunnamanPhantoms (Phi)C241998-04-16No207 Lbs6 ft1NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Donald BusdekerPhantoms (Phi)RW231999-09-25Yes178 Lbs5 ft10NoNoNo1Pro & Farm800,000$0$0$NoNHL Link
Erik KallgrenPhantoms (Phi)G261996-10-14Yes198 Lbs6 ft3NoNoNo2Pro & Farm750,000$0$0$No750,000$NHL Link
Evan WeingerPhantoms (Phi)RW251997-04-18Yes185 Lbs5 ft10NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Frederik GauthierPhantoms (Phi)C271995-04-26No232 Lbs6 ft5NoNoNo2Pro & Farm900,000$0$0$No900,000$NHL Link
Fredrik KarlstromPhantoms (Phi)C251998-01-12Yes195 Lbs6 ft3NoNoNo1Pro & Farm800,000$0$0$NoNHL Link
James HamblinPhantoms (Phi)C231999-04-27Yes181 Lbs5 ft10NoNoNo1Pro & Farm800,000$0$0$NoNHL Link
Jeremy GroleauPhantoms (Phi)D231999-10-25Yes193 Lbs6 ft3NoNoNo1Pro & Farm800,000$0$0$NoNHL Link
Jeremy MckennaPhantoms (Phi)RW231999-04-20Yes180 Lbs5 ft10NoNoNo1Pro & Farm800,000$0$0$NoNHL Link
Jonathan AspirotPhantoms (Phi)D231999-05-16Yes190 Lbs6 ft0NoNoNo2Pro & Farm750,000$0$0$No750,000$NHL Link
Maxim LetunovPhantoms (Phi)C261996-02-20No175 Lbs6 ft4NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Radim SimekPhantoms (Phi)D301992-09-20Yes200 Lbs5 ft11NoNoNo1Pro & Farm800,000$0$0$NoNHL Link
Scott WilsonPhantoms (Phi)RW301992-04-24No183 Lbs5 ft11NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Simon BenoitPhantoms (Phi)D241998-09-19No189 Lbs6 ft3NoNoNo2Pro & Farm850,000$0$0$No850,000$NHL Link
Stefan MatteauPhantoms (Phi)LW281994-02-23No220 Lbs6 ft2NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Sven BaertschiPhantoms (Phi)LW/RW301992-10-05No192 Lbs5 ft11NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Tobie Paquette-BissonPhantoms (Phi)D251997-02-01Yes194 Lbs6 ft3NoNoNo1Pro & Farm800,000$0$0$NoNHL Link
Trevor CarrickPhantoms (Phi)D281994-07-04No186 Lbs6 ft2NoNoNo2Pro & Farm750,000$0$0$No750,000$NHL Link
Tyrell GoulbournePhantoms (Phi)LW291994-01-26No195 Lbs5 ft11NoNoNo1Pro & Farm825,000$0$0$NoNHL Link
Vincent ArseneauPhantoms (Phi)LW301992-03-26No200 Lbs6 ft2NoNoNo1Pro & Farm750,000$0$0$NoNHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2326.26196 Lbs6 ft11.22781,522$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Brandon BaddockFrederik GauthierScott Wilson40122
2Stefan MatteauFredrik KarlstromDonald Busdeker30122
3Sven BaertschiConnor BunnamanJeremy Mckenna20122
4Vincent ArseneauMaxim LetunovScott Wilson10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Radim SimekSimon Benoit40122
2Brinson PasichnukTrevor Carrick30122
3Tobie Paquette-BissonJeremy Groleau20122
4Radim SimekSimon Benoit10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Brandon BaddockFrederik GauthierScott Wilson60122
2Stefan MatteauFredrik KarlstromDonald Busdeker40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Radim SimekSimon Benoit60122
2Brinson PasichnukTrevor Carrick40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Frederik GauthierBrandon Baddock60122
2Fredrik KarlstromStefan Matteau40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Radim SimekSimon Benoit60122
2Brinson PasichnukTrevor Carrick40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Frederik Gauthier60122Radim SimekSimon Benoit60122
2Fredrik Karlstrom40122Brinson PasichnukTrevor Carrick40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Frederik GauthierBrandon Baddock60122
2Fredrik KarlstromStefan Matteau40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Radim SimekSimon Benoit60122
2Brinson PasichnukTrevor Carrick40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Brandon BaddockFrederik GauthierScott WilsonRadim SimekSimon Benoit
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Brandon BaddockFrederik GauthierScott WilsonRadim SimekSimon Benoit
Extra Forwards
Normal PowerPlayPenalty Kill
Connor Bunnaman, Maxim Letunov, Sven BaertschiConnor Bunnaman, Maxim LetunovConnor Bunnaman
Extra Defensemen
Normal PowerPlayPenalty Kill
Trevor Carrick, Tobie Paquette-Bisson, Jeremy GroleauTrevor CarrickTrevor Carrick, Tobie Paquette-Bisson
Penalty Shots
Frederik Gauthier, Fredrik Karlstrom, Brandon Baddock, Stefan Matteau, Connor Bunnaman
Goalie
#1 : Erik Kallgren, #2 : Antoine Bibeau
Custom OT Lines Forwards
Frederik Gauthier, Fredrik Karlstrom, Brandon Baddock, Stefan Matteau, Connor Bunnaman, Maxim Letunov, Maxim Letunov, Sven Baertschi, Scott Wilson, Donald Busdeker, Vincent Arseneau
Custom OT Lines Defensemen
Radim Simek, Simon Benoit, Brinson Pasichnuk, Trevor Carrick, Tobie Paquette-Bisson


Filter Tips
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
OverallHomeVisitor
# VS Team 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
1Aces1000000134-11000000134-10000000000010.50036900674550123358152960541371110185120.00%4175.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
2Americans2010001069-31010000026-41000001043120.500681400674550125458152960541741827488112.50%10370.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
3Bears41300000816-82110000069-32020000027-520.25081422106745501212358152960541129374210115213.33%20575.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
4Bruins522001001213-1320001008532020000048-450.500122436006745501218758152960541147454111120525.00%15193.33%01022190953.54%972189651.27%42784150.77%12578501308414706347
5Crunch11000000422110000004220000000000021.00046100067455012315815296054133762611100.00%3166.67%11022190953.54%972189651.27%42784150.77%12578501308414706347
6Devils1010000014-3000000000001010000014-300.000123006745501230581529605413798223133.33%4175.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
7Falcons43100000171341010000034-133000000149560.75017304701674550121335815296054114950538611436.36%20385.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
8Griffins10001000211100010002110000000000021.0002460067455012295815296054130126164125.00%30100.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
9Gulls1010000023-1000000000001010000023-100.000246006745501226581529605413011619300.00%3166.67%01022190953.54%972189651.27%42784150.77%12578501308414706347
10Heat1010000023-11010000023-10000000000000.0002460067455012325815296054147141025400.00%5180.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
11Ice Hogs1010000036-31010000036-30000000000000.000369006745501240581529605412856275120.00%30100.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
12Marlies11000000312110000003120000000000021.00036900674550122258152960541451012254250.00%6183.33%01022190953.54%972189651.27%42784150.77%12578501308414706347
13Monsters11000000211000000000001100000021121.000246006745501230581529605412696245120.00%3166.67%01022190953.54%972189651.27%42784150.77%12578501308414706347
14Moose11000000312110000003120000000000021.000358006745501229581529605412798292150.00%30100.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
15Oil Kings1010000003-3000000000001010000003-300.0000000067455012345815296054140121021400.00%50100.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
16Penguins21100000633110000004041010000023-120.500611170167455012825815296054151148496233.33%40100.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
17Rampage20200000510-51010000024-21010000036-300.000581300674550124958152960541811726545120.00%13561.54%01022190953.54%972189651.27%42784150.77%12578501308414706347
18Reign2110000067-1000000000002110000067-120.5006111700674550127558152960541622112465120.00%6183.33%01022190953.54%972189651.27%42784150.77%12578501308414706347
19Rocket3200010014122210001007701100000075250.83314264000674550121075815296054110533168713538.46%7357.14%01022190953.54%972189651.27%42784150.77%12578501308414706347
20Senators22000000945110000004131100000053241.0009172600674550127558152960541411612349333.33%60100.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
21Sound Tigers541000002016432100000121022200000086280.800203858006745501215358152960541164444611220525.00%21480.95%01022190953.54%972189651.27%42784150.77%12578501308414706347
22Swamp Rabbits10001000431000000000001000100043121.00047110067455012325815296054133166195240.00%30100.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
23Thunderbirds412000101415-12020000058-32100001097240.50014203400674550121235815296054112643499721314.29%20480.00%11022190953.54%972189651.27%42784150.77%12578501308414706347
24Wheat Kings10001000321100010003210000000000021.000358006745501211581529605412592819200.00%7185.71%01022190953.54%972189651.27%42784150.77%12578501308414706347
25Wolfpack412000011012-21100000010130200001912-330.37510172701674550121215815296054111639419916318.75%16381.25%01022190953.54%972189651.27%42784150.77%12578501308414706347
26Wolves21000100835110000006061000010023-130.7508152301674550126958152960541451517411218.33%60100.00%01022190953.54%972189651.27%42784150.77%12578501308414706347
Total542321033221671670271390220183749271012011218493-9610.5651672984651467455012173058152960541172852651212552084722.60%2164081.48%21022190953.54%972189651.27%42784150.77%12578501308414706347
_Since Last GM Reset542321033221671670271390220183749271012011218493-9610.5651672984651467455012173058152960541172852651212552084722.60%2164081.48%21022190953.54%972189651.27%42784150.77%12578501308414706347
_Vs Conference3918150122112512501810600200565242189010216973-4450.577125220345136745501212855815296054112453833659121523724.34%1542881.82%21022190953.54%972189651.27%42784150.77%12578501308414706347
_Vs Division151210001014841797300100262156570000122202260.8674889137006745501250458152960541468143120345631828.57%50982.00%01022190953.54%972189651.27%42784150.77%12578501308414706347

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
5461OTL116729846517301728526512125514
All Games
GPWLOTWOTL SOWSOLGFGA
5423213322167167
Home Games
GPWLOTWOTL SOWSOLGFGA
2713922018374
Visitor Games
GPWLOTWOTL SOWSOLGFGA
27101211218493
Last 10 Games
WLOTWOTL SOWSOL
422101
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2084722.60%2164081.48%2
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
5815296054167455012
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1022190953.54%972189651.27%42784150.77%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
12578501308414706347


Last Played Games
Filter Tips
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
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
2 - 2022-10-1113Phantoms6Falcons5AWBoxScore
4 - 2022-10-1326Falcons4Phantoms3BLBoxScore
6 - 2022-10-1538Bruins1Phantoms3BWBoxScore
8 - 2022-10-1756Phantoms1Bears3ALBoxScore
10 - 2022-10-1969Penguins0Phantoms4BWBoxScore
13 - 2022-10-2291Sound Tigers3Phantoms4BWBoxScore
15 - 2022-10-24105Phantoms2Sound Tigers1AWBoxScore
17 - 2022-10-26123Wolfpack0Phantoms1BWBoxScore
18 - 2022-10-27137Phantoms2Wolfpack3ALBoxScore
20 - 2022-10-29151Phantoms2Bruins5ALBoxScore
21 - 2022-10-30156Phantoms1Bears4ALBoxScore
24 - 2022-11-02175Bears5Phantoms1BLBoxScore
27 - 2022-11-05197Senators1Phantoms4BWBoxScore
29 - 2022-11-07215Americans6Phantoms2BLBoxScore
30 - 2022-11-08223Phantoms3Reign2AWBoxScore
32 - 2022-11-10241Phantoms2Falcons0AWBoxScore
34 - 2022-11-12254Aces4Phantoms3BLXXBoxScore
36 - 2022-11-14271Moose1Phantoms3BWBoxScore
38 - 2022-11-16281Phantoms5Senators3AWBoxScore
40 - 2022-11-18299Phantoms6Falcons4AWBoxScore
42 - 2022-11-20312Marlies1Phantoms3BWBoxScore
45 - 2022-11-23330Phantoms0Oil Kings3ALBoxScore
46 - 2022-11-24341Phantoms2Wolves3ALXBoxScore
48 - 2022-11-26354Wheat Kings2Phantoms3BWXBoxScore
50 - 2022-11-28370Phantoms1Devils4ALBoxScore
52 - 2022-11-30386Thunderbirds5Phantoms3BLBoxScore
53 - 2022-12-01394Phantoms2Penguins3ALBoxScore
56 - 2022-12-04415Crunch2Phantoms4BWBoxScore
59 - 2022-12-07435Rampage4Phantoms2BLBoxScore
61 - 2022-12-09446Phantoms4Wolfpack5ALBoxScore
63 - 2022-12-11462Phantoms2Bruins3ALBoxScore
65 - 2022-12-13473Bruins2Phantoms1BLXBoxScore
67 - 2022-12-15486Phantoms4Thunderbirds3AWXXBoxScore
69 - 2022-12-17499Phantoms3Rampage6ALBoxScore
70 - 2022-12-18508Sound Tigers4Phantoms6BWBoxScore
72 - 2022-12-20522Phantoms2Gulls3ALBoxScore
74 - 2022-12-22532Rocket3Phantoms4BWBoxScore
76 - 2022-12-24547Phantoms5Thunderbirds4AWBoxScore
77 - 2022-12-25558Phantoms7Rocket5AWBoxScore
79 - 2022-12-27567Wolves0Phantoms6BWBoxScore
82 - 2022-12-30591Phantoms4Americans3AWXXBoxScore
83 - 2022-12-31599Sound Tigers3Phantoms2BLBoxScore
86 - 2023-01-03619Phantoms3Reign5ALBoxScore
88 - 2023-01-05629Thunderbirds3Phantoms2BLBoxScore
91 - 2023-01-08654Ice Hogs6Phantoms3BLBoxScore
93 - 2023-01-10667Phantoms4Swamp Rabbits3AWXBoxScore
95 - 2023-01-12681Heat3Phantoms2BLBoxScore
97 - 2023-01-14698Phantoms6Sound Tigers5AWBoxScore
98 - 2023-01-15703Phantoms2Monsters1AWBoxScore
100 - 2023-01-17718Bruins2Phantoms4BWBoxScore
104 - 2023-01-21742Bears4Phantoms5BWBoxScore
107 - 2023-01-24766Phantoms3Wolfpack4ALXXBoxScore
108 - 2023-01-25774Griffins1Phantoms2BWXBoxScore
111 - 2023-01-28796Rocket4Phantoms3BLXBoxScore
113 - 2023-01-30809Phantoms-Oil Kings-
115 - 2023-02-01827Bears-Phantoms-
119 - 2023-02-05850Americans-Phantoms-
123 - 2023-02-09878Senators-Phantoms-
125 - 2023-02-11894Phantoms-Penguins-
126 - 2023-02-12903Phantoms-Sound Tigers-
128 - 2023-02-14913Swamp Rabbits-Phantoms-
131 - 2023-02-17936Falcons-Phantoms-
133 - 2023-02-19951Phantoms-Bears-
135 - 2023-02-21965Oil Kings-Phantoms-
138 - 2023-02-24981Phantoms-Swamp Rabbits-
140 - 2023-02-26997Swamp Rabbits-Phantoms-
142 - 2023-02-281011Phantoms-Wild-
143 - 2023-03-011025Penguins-Phantoms-
145 - 2023-03-031038Phantoms-Admirals-
147 - 2023-03-051050Phantoms-Heat-
Trade Deadline --- Trades can’t be done after this day is simulated!
149 - 2023-03-071064Falcons-Phantoms-
151 - 2023-03-091082Phantoms-Crunch-
152 - 2023-03-101091Phantoms-Bruins-
154 - 2023-03-121099Wolfpack-Phantoms-
157 - 2023-03-151123Gulls-Phantoms-
159 - 2023-03-171135Phantoms-Penguins-
162 - 2023-03-201153Penguins-Phantoms-
165 - 2023-03-231172Phantoms-Crunch-
166 - 2023-03-241181Devils-Phantoms-
167 - 2023-03-251188Phantoms-Bears-
168 - 2023-03-261195Phantoms-Devils-
171 - 2023-03-291214Phantoms-Admirals-
173 - 2023-03-311228Wolfpack-Phantoms-
178 - 2023-04-051250Barracuda-Phantoms-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price200100
Attendance35,78618,040
Attendance PCT66.27%66.81%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
15 1994 - 66.45% 414,870$11,201,500$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
1,253,295$ 1,797,500$ 1,797,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
9,986$ 1,099,116$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
6,223,056$ 69 11,375$ 784,875$




Phantoms Stat Leaders (Regular Season)

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Phantoms Goalies Stat Leaders (Regular Season)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Phantoms Career Team Stats

OverallHomeVisitor
Year 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

Phantoms Stat Leaders (Play-Off)

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Phantoms Goalies Stat Leaders (Play-Off)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA