SAN JOSE AVACADOES

GP: 6 | W: 2 | L: 2 | OTL: 2 | P: 6
GF: 20 | GA: 23 | PP%: 21.05% | PK%: 77.78%
GM : Sean S | Morale : 46 | Team Overall : 66
Next Games #64 vs PHILADELPHIA PHANTOMS
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

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 SP
1Steve OttXX100.0099997657395878973747470629996055740
2Valentin Zykov (R)XX100.00321593888687858422797762617973048732
3Gregory CampbellXX100.00998061627489817369736982789999054730
4Brooks LaichXX100.00998345637776897584677077659999048720
5Johannes SalmonssonX100.00999746677548677349757187599696043712
6Kerby Rychel (R)X100.00705366798575857048726968547877048691
7Brock McGinn (R)XX100.00525767788080877444666855527172048672
8Artturi Lehkonen (R)XX100.00413074898580777048696361556874048672
9Anthony Duclair (R)XX100.00271798848378757039716956547376048672
10Nolan Patrick (R)X100.00492871807579826968666963607568048671
11Oskar Lindblom (R)X100.00585068787869676644656657516369048642
12John Hayden (R)XXX100.00434593767974766566605963547266049632
13Jakob Chychrun (R)X100.00581888797578776630696371447972048691
14Shane O'BrienX100.00999941568267706660575575589998043690
15Jay BouwmeesterX100.0021999608175856150654688619985049680
16Matt GreeneX100.00745964568370686750595477589794048680
17Nicolas Hague (R)X99.00766265636866646140605857446258048602
18Mike Anderson (R)X100.00686955636460575540585857485752043572
Scratches
1Zack StortiniX100.00999717728263896672676183789999044710
2Martin Frk (R)XX100.00463486798087866951675666548170044662
3Miles Wood (R)X100.00515364788766696963556164567575044642
4Drake Batherson (R)X88.92391358767078756558646357586060041622
5AJ Greer (R)X100.00605566687559706345575959586163044602
6Ryan Gropp (R)X100.00494866667766726938606356405957044602
7Jimmy Vesey (R)X100.00423374628057676544625555436670044592
8Stelio Mattheos (R)X100.00462955636562636343605862555760041582
9Will Butcher (R)X85.53726344787676706944614665566966038662
10Matt Finn (R)X100.00443982608349594648383865466763044562
11Frederic Allard (R)X100.00312480636959575845594860446358044562
TEAM AVERAGE99.0860506571777174675164616655777504665
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 SP
1Anders Lindback96.0064798683786878767570719278048740
2Jakub Škarek (R)100.0064585865596059576361605866044592
Scratches
1Antti Niemi100.0059606082677680838565609691044740
2Sami Aittokallio100.0068656676706467646758538077044662
3Christopher Gibson100.0063686680716059575753617270044632
TEAM AVERAGE99.206466677769666967696161807604567
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Mike Haviland77858081868664USA482784,000$


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 NamePOS 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
1Kerby RychelSAN JOSE AVACADOES (SAJ)LW6369400106225413.64%512120.191345150000230042.86%750001.4900000201
2Valentin ZykovSAN JOSE AVACADOES (SAJ)LW/RW6358-300192261113.64%410717.93224515000000018.18%1181001.4901000020
3Nolan PatrickSAN JOSE AVACADOES (SAJ)C6347-2409132481112.50%312721.271343150000110052.57%17531001.1000000000
4Anthony DuclairSAN JOSE AVACADOES (SAJ)LW/RW6325300281821016.67%29816.490000110000011100.00%321001.0100000100
5Drake BathersonSAN JOSE AVACADOES (SAJ)C41451205962116.67%06716.7600017000010051.92%5213001.4900000010
6Gregory CampbellSAN JOSE AVACADOES (SAJ)C/LW61230121096102310.00%27412.4800000000090065.00%2022000.8000200000
7Oskar LindblomSAN JOSE AVACADOES (SAJ)LW6112-24010392411.11%410317.2200000000090033.33%611000.3900000000
8Brock McGinnSAN JOSE AVACADOES (SAJ)LW/RW61120005362816.67%06711.20000111000010066.67%342000.6000000000
9Artturi LehkonenSAN JOSE AVACADOES (SAJ)LW/RW6022000349360.00%2488.1300000000000050.00%230000.8200000000
10Steve OttSAN JOSE AVACADOES (SAJ)C/RW6112-1531511414277.14%57612.70000130000140057.69%2623000.5200201000
11Brooks LaichSAN JOSE AVACADOES (SAJ)C/LW6112-3008645325.00%47913.31000000001140071.05%3820000.5000000000
12Jay BouwmeesterSAN JOSE AVACADOES (SAJ)D5011-200064130.00%811022.0200004000121000.00%012000.1800000000
13Matt GreeneSAN JOSE AVACADOES (SAJ)D6011-280854420.00%910317.220000000015000.00%006000.1900000000
14Will ButcherSAN JOSE AVACADOES (SAJ)D1011120102100.00%21212.900000000000000.00%000001.5500000000
15Johannes SalmonssonSAN JOSE AVACADOES (SAJ)LW2011-100213040.00%02110.530000000000000.00%000000.9500000000
16John HaydenSAN JOSE AVACADOES (SAJ)C/LW/RW6101-1551361016.67%0569.4500000000000064.29%1401000.3511001000
17Jakob ChychrunSAN JOSE AVACADOES (SAJ)D600000051016570.00%813823.0600021800001000.00%044000.0000000000
18Nicolas HagueSAN JOSE AVACADOES (SAJ)D60000401588630.00%215525.90000420000018000.00%013000.0000000000
19Mike Anderson SAN JOSE AVACADOES (SAJ)D4000020461010.00%27719.4300006000116000.00%004000.0000000000
20Shane O'BrienSAN JOSE AVACADOES (SAJ)D600012010674120.00%49716.2600001000219000.00%001000.0000011000
21Simon DespresSAN JOSE BLASPHEMERSD2000055413110.00%23718.560000200004000.00%041000.0000100000
Team Total or Average108193352-71214511911819559919.74%68178216.5148122213500061741154.90%3574336000.5812513331
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
1Jakub ŠkarekSAN JOSE AVACADOES (SAJ)42110.8933.15248001312264001.000342001
2Anders LindbackSAN JOSE AVACADOES (SAJ)20110.8595.0012000107142000.000024000
Team Total or Average62220.8813.743690023193106001.000366001


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 StatusType Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Link
AJ GreerSAN JOSE AVACADOES (SAJ)LW225/29/1997 4:06:37 AMYes196 Lbs6 ft4NoNoNo4ELCPro & Farm500,000$50,000$47,241$No
Anders LindbackSAN JOSE AVACADOES (SAJ)G311/3/1988No215 Lbs6 ft6NoNoNo1UFAPro & Farm1,012,500$101,250$95,664$No
Anthony DuclairSAN JOSE AVACADOES (SAJ)LW/RW248/26/1995 7:48:57 AMYes190 Lbs6 ft1NoNoNo2RFAPro & Farm400,000$40,000$37,793$No
Antti NiemiSAN JOSE AVACADOES (SAJ)G365/29/1983No224 Lbs6 ft2NoNoNo2UFAPro & Farm1,604,250$160,425$151,574$No
Artturi LehkonenSAN JOSE AVACADOES (SAJ)LW/RW247/4/1995 4:22:12 AMYes172 Lbs6 ft0NoNoNo1RFAPro & Farm500,000$50,000$47,241$No
Brock McGinnSAN JOSE AVACADOES (SAJ)LW/RW259/10/1994 3:14:40 AMYes224 Lbs6 ft4NoNoNo1RFAPro & Farm400,000$40,000$37,793$No
Brooks LaichSAN JOSE AVACADOES (SAJ)C/LW366/23/1983No206 Lbs6 ft2NoNoNo1UFAPro & Farm1,100,000$110,000$103,931$No
Christopher GibsonSAN JOSE AVACADOES (SAJ)G2612/27/1992 8:06:51 AMNo213 Lbs6 ft2NoNoNo2RFAPro & Farm500,000$50,000$47,241$No
Drake BathersonSAN JOSE AVACADOES (SAJ)C214/27/1998 1:25:17 AMYes191 Lbs6 ft1NoNoNo2ELCPro & Farm500,000$50,000$47,241$No
Frederic AllardSAN JOSE AVACADOES (SAJ)D216/1/1998 3:03:18 AMYes208 Lbs6 ft2NoNoNo1ELCPro & Farm300,000$30,000$28,345$No
Gregory CampbellSAN JOSE AVACADOES (SAJ)C/LW3512/17/1983No204 Lbs6 ft0NoNoNo1UFAPro & Farm1,750,250$175,025$165,368$No
Jakob ChychrunSAN JOSE AVACADOES (SAJ)D213/31/1998 1:31:39 PMYes211 Lbs6 ft2NoNoNo1ELCPro & Farm750,000$75,000$70,862$No
Jakub ŠkarekSAN JOSE AVACADOES (SAJ)G1911/10/1999 4:25:04 AMYes165 Lbs6 ft1NoNoNo3ELCPro & Farm550,000$55,000$51,966$No
Jay BouwmeesterSAN JOSE AVACADOES (SAJ)D369/27/1983No224 Lbs6 ft4NoNoNo1UFAPro & Farm1,162,500$116,250$109,836$No
Jimmy VeseySAN JOSE AVACADOES (SAJ)LW265/26/1993 6:42:21 AMYes218 Lbs6 ft5NoNoNo1RFAPro & Farm812,500$81,250$76,767$No
Johannes SalmonssonSAN JOSE AVACADOES (SAJ)LW336/21/1986 9:42:07 AMNo195 Lbs6 ft2NoNoNo3UFAPro & Farm790,300$79,030$74,670$No
John HaydenSAN JOSE AVACADOES (SAJ)C/LW/RW246/22/1995 7:36:19 AMYes198 Lbs6 ft0NoNoNo2RFAPro & Farm400,000$40,000$37,793$No
Kerby RychelSAN JOSE AVACADOES (SAJ)LW2510/7/1994 1:38:55 AMYes218 Lbs6 ft1NoNoNo3RFAPro & Farm650,000$65,000$61,414$No
Martin FrkSAN JOSE AVACADOES (SAJ)LW/RW259/10/1994 3:18:24 AMYes221 Lbs6 ft3NoNoNo2RFAPro & Farm500,000$50,000$47,241$No
Matt FinnSAN JOSE AVACADOES (SAJ)D259/10/1994 2:54:24 AMYes232 Lbs6 ft6NoNoNo1RFAPro & Farm400,000$40,000$37,793$No
Matt GreeneSAN JOSE AVACADOES (SAJ)D365/13/1983No239 Lbs6 ft3NoNoNo1UFAPro & Farm600,000$60,000$56,690$No
Mike Anderson SAN JOSE AVACADOES (SAJ)D206/1/1999 9:08:14 AMYes202 Lbs6 ft0NoNoNo3ELCPro & Farm500,000$50,000$47,241$No
Miles WoodSAN JOSE AVACADOES (SAJ)LW249/13/1995 10:06:18 AMYes195 Lbs6 ft0NoNoNo1RFAPro & Farm300,000$30,000$28,345$No
Nicolas HagueSAN JOSE AVACADOES (SAJ)D2012/5/1998 1:12:02 AMYes220 Lbs6 ft6NoNoNo2ELCPro & Farm650,000$65,000$61,414$No
Nolan PatrickSAN JOSE AVACADOES (SAJ)C219/19/1998 4:29:33 AMYes208 Lbs6 ft2NoNoNo2ELCPro & Farm750,000$75,000$70,862$No
Oskar LindblomSAN JOSE AVACADOES (SAJ)LW238/15/1996 7:20:22 AMYes204 Lbs6 ft6NoNoNo3RFAPro & Farm400,000$40,000$37,793$No
Ryan GroppSAN JOSE AVACADOES (SAJ)LW239/16/1996 4:13:34 AMYes201 Lbs6 ft3NoNoNo3RFAPro & Farm500,000$50,000$47,241$No
Sami AittokallioSAN JOSE AVACADOES (SAJ)G276/21/1992 10:25:47 AMNo192 Lbs6 ft1NoNoNo1RFAPro & Farm775,000$77,500$73,224$No
Shane O'BrienSAN JOSE AVACADOES (SAJ)D368/9/1983No238 Lbs6 ft3NoNoNo1UFAPro & Farm500,000$50,000$47,241$No
Stelio Mattheos SAN JOSE AVACADOES (SAJ)RW206/1/1999 8:06:33 AMYes182 Lbs6 ft1NoNoNo3ELCPro & Farm500,000$50,000$47,241$No
Steve OttSAN JOSE AVACADOES (SAJ)C/RW378/19/1982No197 Lbs6 ft0NoNoNo1UFAPro & Farm1,457,382$145,738$137,697$No
Valentin ZykovSAN JOSE AVACADOES (SAJ)LW/RW245/15/1995 2:43:39 AMYes220 Lbs6 ft1NoNoNo1RFAPro & Farm525,000$52,500$49,603$No
Will ButcherSAN JOSE AVACADOES (SAJ)D246/22/1995 11:59:59 AMYes193 Lbs6 ft3NoNoNo1RFAPro & Farm650,000$65,000$61,414$No
Zack StortiniSAN JOSE AVACADOES (SAJ)RW349/11/1985No227 Lbs6 ft4NoNoNo1UFAPro & Farm400,000$40,000$37,793$No
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3426.59207 Lbs6 ft21.74679,108$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Oskar LindblomNolan PatrickValentin Zykov36014
2Kerby RychelGregory CampbellAnthony Duclair30014
3Johannes SalmonssonBrooks LaichSteve Ott24041
4Artturi LehkonenJohn HaydenBrock McGinn10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Nicolas HagueJakob Chychrun40122
2Matt GreeneJay Bouwmeester32122
3Shane O'BrienMike Anderson 26131
4Jay BouwmeesterMatt Greene2122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Kerby RychelNolan PatrickValentin Zykov55005
2Anthony DuclairSteve OttBrock McGinn45113
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Nicolas HagueJakob Chychrun60014
2Mike Anderson Nicolas Hague40113
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Steve OttKerby Rychel60131
2Brooks LaichGregory Campbell40041
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Shane O'BrienMike Anderson 51050
2Nicolas HagueJay Bouwmeester49050
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Steve Ott50050Shane O'BrienMike Anderson 50050
2Brooks Laich50050Matt GreeneNicolas Hague50050
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Steve OttKerby Rychel60122
2Nolan PatrickAnthony Duclair40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Nicolas HagueMike Anderson 50122
2Jakob ChychrunJay Bouwmeester50122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Anthony DuclairNolan PatrickValentin ZykovJay BouwmeesterJakob Chychrun
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Gregory CampbellBrooks LaichSteve OttShane O'BrienMike Anderson
Extra Forwards
Normal PowerPlayPenalty Kill
Nolan Patrick, John Hayden, Anthony DuclairBrock McGinn, Artturi LehkonenKerby Rychel
Extra Defensemen
Normal PowerPlayPenalty Kill
Jakob Chychrun, Jay Bouwmeester, Matt GreeneJakob ChychrunJay Bouwmeester, Matt Greene
Penalty Shots
Valentin Zykov, John Hayden, Anthony Duclair, Nolan Patrick, Kerby Rychel
Goalie
#1 : Anders Lindback, #2 : Jakub Škarek
Custom OT Lines Forwards
John Hayden, Nolan Patrick, Anthony Duclair, Oskar Lindblom, Johannes Salmonsson, Valentin Zykov, Valentin Zykov, Brock McGinn, Kerby Rychel, Artturi Lehkonen, Steve Ott
Custom OT Lines Defensemen
Mike Anderson , Nicolas Hague, Jay Bouwmeester, Shane O'Brien, Jakob Chychrun


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
1CALGARY WRANGLERS1000010045-1000000000001000010045-110.5004812002891355770664291528246233.33%4325.00%06311554.78%7814055.71%559756.70%136791265610752
2CHICAGO UNDERTAKERS11000000321000000000001100000032121.00034700289134577066434111310100.00%40100.00%06311554.78%7814055.71%559756.70%136791265610752
3DETROIT STEELERS20100010770100000104311010000034-120.50071118002891685770664712441475120.00%7357.14%06311554.78%7814055.71%559756.70%136791265610752
4EDMONTON OILERS1010000013-21010000013-20000000000000.00012300289130577066420812154125.00%60100.00%06311554.78%7814055.71%559756.70%136791265610752
5PHILADELPHIA PHANTOMS1000010056-1000000000001000010056-110.500581300289128577066439102723300.00%60100.00%06311554.78%7814055.71%559756.70%136791265610752
Total612002102023-32010001056-1411002001517-260.50020335300289119557706641936812111919421.05%27677.78%06311554.78%7814055.71%559756.70%136791265610752
_Since Last GM Reset612002102023-32010001056-1411002001517-260.50020335300289119557706641936812111919421.05%27677.78%06311554.78%7814055.71%559756.70%136791265610752
_Vs Conference511002101920-110000010431411002001517-260.60019315000289116557706641736010910415320.00%21671.43%06311554.78%7814055.71%559756.70%136791265610752
_Vs Division511002101920-110000010431411002001517-260.60019315000289116557706641736010910415320.00%21671.43%06311554.78%7814055.71%559756.70%136791265610752

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
66OTL12033531951936812111900
All Games
GPWLOTWOTL SOWSOLGFGA
61202102023
Home Games
GPWLOTWOTL SOWSOLGFGA
201001056
Visitor Games
GPWLOTWOTL SOWSOLGFGA
41102001517
Last 10 Games
WLOTWOTL SOWSOL
220200
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
19421.05%27677.78%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
57706642891
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
6311554.78%7814055.71%559756.70%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
136791265610752


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
1 - 2019-09-055SAN JOSE AVACADOES4CALGARY WRANGLERS5LXBoxScore
2 - 2019-09-066SAN JOSE AVACADOES3CHICAGO UNDERTAKERS2WBoxScore
4 - 2019-09-0822DETROIT STEELERS3SAN JOSE AVACADOES4WXXBoxScore
6 - 2019-09-1034EDMONTON OILERS3SAN JOSE AVACADOES1LBoxScore
7 - 2019-09-1146SAN JOSE AVACADOES3DETROIT STEELERS4LBoxScore
8 - 2019-09-1254SAN JOSE AVACADOES5PHILADELPHIA PHANTOMS6LXBoxScore
10 - 2019-09-1464PHILADELPHIA PHANTOMS-SAN JOSE AVACADOES-
12 - 2019-09-1677SAN JOSE AVACADOES-CALGARY WRANGLERS-
13 - 2019-09-1785DETROIT STEELERS-SAN JOSE AVACADOES-
15 - 2019-09-1995SAN JOSE AVACADOES-COLORADO CUBS-
16 - 2019-09-20104SAN JOSE AVACADOES-CHICAGO UNDERTAKERS-
17 - 2019-09-21110NORTH VAN ROCKERS-SAN JOSE AVACADOES-
20 - 2019-09-24130CHICAGO UNDERTAKERS-SAN JOSE AVACADOES-
21 - 2019-09-25138SAN JOSE AVACADOES-COLORADO CUBS-
23 - 2019-09-27150CALGARY WRANGLERS-SAN JOSE AVACADOES-
24 - 2019-09-28161SAN JOSE AVACADOES-CHICAGO UNDERTAKERS-
26 - 2019-09-30174PHILADELPHIA PHANTOMS-SAN JOSE AVACADOES-
28 - 2019-10-02185SAN JOSE AVACADOES-CALGARY WRANGLERS-
30 - 2019-10-04195SAN JOSE AVACADOES-MANHATTAN SWEDES-
31 - 2019-10-05201DETROIT STEELERS-SAN JOSE AVACADOES-
33 - 2019-10-07216COQUITLAM EXPRESS-SAN JOSE AVACADOES-
35 - 2019-10-09228SAN JOSE AVACADOES-DETROIT STEELERS-
36 - 2019-10-10237BANGOR PUPPIES-SAN JOSE AVACADOES-
38 - 2019-10-12250SAN JOSE AVACADOES-NEWTON NIGHTHAWKS-
39 - 2019-10-13258NORTH VAN ROCKERS-SAN JOSE AVACADOES-
41 - 2019-10-15267SAN JOSE AVACADOES-CAPE BRETON LEPRECHAUNS-
43 - 2019-10-17279SAN JOSE AVACADOES-PHILADELPHIA PHANTOMS-
44 - 2019-10-18286COLORADO CUBS-SAN JOSE AVACADOES-
46 - 2019-10-20302SAN JOSE AVACADOES-CALGARY WRANGLERS-
48 - 2019-10-22308PHILADELPHIA PHANTOMS-SAN JOSE AVACADOES-
49 - 2019-10-23322NORTH VAN ROCKERS-SAN JOSE AVACADOES-
51 - 2019-10-25333SAN JOSE AVACADOES-NORTH VAN ROCKERS-
53 - 2019-10-27346SAN JOSE AVACADOES-PHILADELPHIA PHANTOMS-
54 - 2019-10-28352EDMONTON OILERS-SAN JOSE AVACADOES-
56 - 2019-10-30364SAN JOSE AVACADOES-DETROIT STEELERS-
57 - 2019-10-31374CHICAGO UNDERTAKERS-SAN JOSE AVACADOES-
60 - 2019-11-03392HALIFAX HELL-SAN JOSE AVACADOES-
61 - 2019-11-04398SAN JOSE AVACADOES-SYRACUSE BABY BULLS-
63 - 2019-11-06412VANCOUVER THOUSANDAIRES-SAN JOSE AVACADOES-
65 - 2019-11-08425SAN JOSE AVACADOES-HAWAII PUNCH-
66 - 2019-11-09430SAN JOSE AVACADOES-HALIFAX HELL-
68 - 2019-11-11438PINCHER CREEK WOLVERINES-SAN JOSE AVACADOES-
69 - 2019-11-12450SAN JOSE AVACADOES-BROOKLYN GRINDERS-
70 - 2019-11-13457SAN JOSE AVACADOES-PENSACOLA BLACK BEARS-
71 - 2019-11-14462CAPE BRETON LEPRECHAUNS-SAN JOSE AVACADOES-
73 - 2019-11-16484SYRACUSE BABY BULLS-SAN JOSE AVACADOES-
75 - 2019-11-18495SAN JOSE AVACADOES-PINCHER CREEK WOLVERINES-
77 - 2019-11-20505NEWTON NIGHTHAWKS-SAN JOSE AVACADOES-
79 - 2019-11-22520SAN JOSE AVACADOES-EDMONTON OILERS-
81 - 2019-11-24527HAWAII PUNCH-SAN JOSE AVACADOES-
83 - 2019-11-26544DETROIT STEELERS-SAN JOSE AVACADOES-
84 - 2019-11-27553SAN JOSE AVACADOES-NORTH VAN ROCKERS-
86 - 2019-11-29564SAN JOSE AVACADOES-CALGARY WRANGLERS-
87 - 2019-11-30570SAN JOSE AVACADOES-CAPE FEAR WILDCATS-
88 - 2019-12-01572CAPE BRETON LEPRECHAUNS-SAN JOSE AVACADOES-
91 - 2019-12-04594COLORADO CUBS-SAN JOSE AVACADOES-
92 - 2019-12-05601SAN JOSE AVACADOES-VANCOUVER THOUSANDAIRES-
94 - 2019-12-07614SAN JOSE AVACADOES-PENSACOLA BLACK BEARS-
95 - 2019-12-08619MANHATTAN SWEDES-SAN JOSE AVACADOES-
97 - 2019-12-10631SAN JOSE AVACADOES-LAS CRUCES MESCALEROS-
98 - 2019-12-11640EDMONTON OILERS-SAN JOSE AVACADOES-
100 - 2019-12-13658COLORADO CUBS-SAN JOSE AVACADOES-
103 - 2019-12-16676CHICAGO UNDERTAKERS-SAN JOSE AVACADOES-
105 - 2019-12-18688SAN JOSE AVACADOES-BROOKLYN GRINDERS-
107 - 2019-12-20700LAS CRUCES MESCALEROS-SAN JOSE AVACADOES-
108 - 2019-12-21709SAN JOSE AVACADOES-CAPE BRETON LEPRECHAUNS-
109 - 2019-12-22722SAN JOSE AVACADOES-CHICAGO UNDERTAKERS-
110 - 2019-12-23726BROOKLYN GRINDERS-SAN JOSE AVACADOES-
Trade Deadline --- Trades can’t be done after this day is simulated!
113 - 2019-12-26744BROOKLYN GRINDERS-SAN JOSE AVACADOES-
114 - 2019-12-27754SAN JOSE AVACADOES-VANCOUVER THOUSANDAIRES-
116 - 2019-12-29764CAPE FEAR WILDCATS-SAN JOSE AVACADOES-
118 - 2019-12-31778SAN JOSE AVACADOES-CHICAGO UNDERTAKERS-
119 - 2020-01-01785PENSACOLA BLACK BEARS-SAN JOSE AVACADOES-
121 - 2020-01-03803PENSACOLA BLACK BEARS-SAN JOSE AVACADOES-
123 - 2020-01-05815SAN JOSE AVACADOES-COLORADO CUBS-
124 - 2020-01-06820SAN JOSE AVACADOES-COQUITLAM EXPRESS-
127 - 2020-01-09832BANGOR PUPPIES-SAN JOSE AVACADOES-
128 - 2020-01-10837SAN JOSE AVACADOES-COLORADO CUBS-
131 - 2020-01-13851SAN JOSE AVACADOES-BANGOR PUPPIES-
132 - 2020-01-14857PHILADELPHIA PHANTOMS-SAN JOSE AVACADOES-
133 - 2020-01-15865SAN JOSE AVACADOES-BANGOR PUPPIES-
135 - 2020-01-17879EDMONTON OILERS-SAN JOSE AVACADOES-
139 - 2020-01-21899CALGARY WRANGLERS-SAN JOSE AVACADOES-
143 - 2020-01-25915CALGARY WRANGLERS-SAN JOSE AVACADOES-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance3,5261,934
Attendance PCT88.15%96.70%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
40 2730 - 91.00% 76,210$152,420$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
175,294$ 2,308,968$ 182,000$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
2,308,968$ 132,038$ 34 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
3,048,400$ 137 21,331$ 2,922,347$




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
Regular Season
7843733045412832632042171703221136133342201601320147130177428348576831819896142546825854840472478800240218572707527.78%4048479.21%12948177853.32%973178054.66%676127652.98%177598317698071539745
8612002102023-32010001056-1411002001517-2620335300289119557706641936812111919421.05%27677.78%06311554.78%7814055.71%559756.70%136791265610752
Total Regular Season90383504751303286174417180323114113924621170152016214715803035188213183106105152741882924906512671868252319762897927.34%4319079.12%121011189353.41%1051192054.74%731137353.24%1911106318958641647798
Playoff
7514000001324-1121100000911-230300000413-921323361025601424544530145409611933100.00%23578.26%1569857.14%5511050.00%448551.76%9956106499441
Total Playoff514000001324-1121100000911-230300000413-921323361025601424544530145409611933100.00%23578.26%1569857.14%5511050.00%448551.76%9956106499441