EA FC 25 Squad Builder
Create EA FC 25 Squads
Add Tactics
Sort by
• Platform/Gen
• Formations
• Build Up Style
• Defensive Approach
User Tactics name Formation Build Up Style D
4-1-2-1-2 Inverted Fullback
+ Wide Midfielder
Defends in a 5-3-2 and
attacks in a 2-3-3-2.
G Fullbacks moves inverted
to create a midfield 3
Guest Balanced Ba
infront of the cbs, while 2 4-1-2-1-2
13.09.2024 of the midfielders move
wide to establish wide
options. cam moves freely
onto each side as support
with 2 strikers (1 tall and
one fast) to score both
crosses and through balls
Updated FC Barcelona
2014/15
Short Passing Ag
This tactic aims to mimic 4-3-3(2)
the treble-winning Barca
Cheesy42 side from the 14/15
Season. You can play
User Tactics name Formation Build Up Style D
20.10.2024 around with a 343 for a
more attacking approach
or a 433(5) with Messi as
the false 9 and Suarez on
the right for a defensive
variant.
41212 > 21232 Tiki Taka
Kinda converts into a
really attacking 352 with
the middle CB stepping in Balanced Ba
when you're on the ball. 4-1-2-1-2(2)
MattFUTTrading Tonnes of options through
20.09.2024 the middle and always
options out wide for
passes.
G pep guardiola at man city
Guest based on short passing. Short Passing Hi
falseback becomes cdm 4-3-3
14.09.2024
and other full back stays
back to form a back three
G
4141- ingame 325
Guest Short Passing Ba
pep-like build up play with 4-1-4-1
14.09.2024 lots of attackers and
inverted fullback
Hansi Flick's Barcelona Balanced Hi
4-2-3-1(2)
tactics
User Tactics name Formation Build Up Style D
Veljas A very high line, a Cubarsi-
like RCB to break the
18.09.2024
lines, a playmaker CAM
that rotates between the
CAM and RCM position
based on necessity.
Tucked in wingers provide
central overloads for
dangerous attacks while
overlapping fullbacks
provide width. Suffocate
the opposition and
outscore your opponent.
4-3-3(4) into 3-4-3 Counter Ag
4-3-3(4)
Diamond
AGhostJedi
16.09.2024
NepentheZ Arsenal RTG
The tactic Nep used to get Counter Ag
Rank 3 in WL and D2 in 4-1-3-2
NepentheZ Champs with an Arsenal
22.10.2024 only team!
442 into 3223
Counter Hi
442 balanced set up that 4-4-2
childishjp potentially attacks in a
modern 3223. (WIP)
03.10.2024
User Tactics name Formation Build Up Style D
Total Football
Inspired by the original
Balanced Hi
Cruyffian total football 3-4-1-2
Brandyboy777 philosophy - high line,
heavy press , everyone
18.09.2024 contributes everywhere.
G
Wochenendliga
Guest Balanced Ba
Mein bestes Team für die 4-3-2-1
14.09.2024 erste WL (zweites System
im 4-2-3-1).
4231 - Pretty basic
This is my take on 4231
with a second striker
behind your striker who
runs behind while your
half wingers get wide.
Balanced Hi
You're not limited to make 4-2-3-1
AndreFlaten the same play each time. -
Can use higher
17.09.2024 wingbacks, can also try
the dms on deep lying
playmaker and roaming
and get falsebacks. We'll
see how they work.
G Arteta and Arsenal's IRL
Guest tactic Short Passing Hi
4-3-3(2)
18.09.2024 This tactic mirrors Arteta's
real-life approach at
Arsenal, focusing on a
User Tactics name Formation Build Up Style D
fluid, possession-based 4-
3-3 system. Like Arteta, it
emphasizes high pressing,
building from the back,
and versatile attacking
play, reflecting his
philosophy of tactical
flexibility, control, and
quick transitions.
Potential replacement for
fc24 4321
wingers set to inside
forward allows them to
G cut in potentially getting
them to act as cfs. One
Guest Counter Ba
set to attack so he stays 4-3-3
16.09.2024 forward and one on
balanced so they come
back and defend in a 442
just like the 4321 in fc24,
with one fullback
attacking and one staying
back
great tactic
Short Passing Hi
my personaal best for fun 4-2-1-3
dias4ever
and efficiency
19.09.2024
DIRTY DOMINANCE Counter Hi
4-3-3(2)
idk use this on FM and
batter everyone in my
User Tactics name Formation Build Up Style D
path even with lower level
teams.
fleeyBoi
16.09.2024
Manager
+
+
{https://proceedings.mlr.press/v36/li14.html}, abstract = {The accuracy and effectiveness
of matrix factorization technique were well demonstrated in the Netflix movie
recommendation contest. Among the numerous solutions for matrix factorization,
Stochastic Gradient Descent (SGD) is one of the most widely used algorithms. However,
as a sequential approach, SGD algorithm cannot directly be used in the Distributed
Cluster Environment (DCE). In this paper, we propose a fast distributed SGD algorithm
named FDSGD for matrix factorization, which can run efficiently in DCE. This algorithm
solves data sharing problem based on independent storage system to avoid data
synchronization which may cause a big influence to algorithm performance, and
synchronous operation problem in DCE using a distributed synchronization tool so that
distributed cooperation threads can perform in a harmonious environment.} }
Copy to Clipboard Download
Endnote
%0 Conference Paper %T A Fast Distributed Stochastic Gradient Descent Algorithm for
Matrix Factorization %A Fanglin Li %A Bin Wu %A Liutong Xu %A Chuan Shi %A Jing Shi %B
Proceedings of the 3rd International Workshop on Big Data, Streams and Heterogeneous
Source Mining: Algorithms, Systems, Programming Models and Applications %C
Proceedings of Machine Learning Research %D 2014 %E Wei Fan %E Albert Bifet %E Qiang
Yang %E Philip S. Yu %F pmlr-v36-li14 %I PMLR %P 77--87 %U
https://proceedings.mlr.press/v36/li14.html %V 36 %X The accuracy and effectiveness of
matrix factorization technique were well demonstrated in the Netflix movie
recommendation contest. Among the numerous solutions for matrix factorization,
Stochastic Gradient Descent (SGD) is one of the most widely used algorithms. However,
as a sequential approach, SGD algorithm cannot directly be used in the Distributed
Cluster Environment (DCE). In this paper, we propose a fast distributed SGD algorithm
named FDSGD for matrix factorization, which can run efficiently in DCE. This algorithm
solves data sharing problem based on independent storage system to avoid data
synchronization which may cause a big influence to algorithm performance, and
synchronous operation problem in DCE using a distributed synchronization tool so that
distributed cooperation threads can perform in a harmonious environment.
Copy to Clipboard Download
RIS
TY - CPAPER TI - A Fast Distributed Stochastic Gradient Descent Algorithm for Matrix
Factorization AU - Fanglin Li AU - Bin Wu AU - Liutong Xu AU - Chuan Shi AU - Jing Shi BT -
Proceedings of the 3rd International Workshop on Big Data, Streams and Heterogeneous
Source Mining: Algorithms, Systems, Programming Models and Applications DA -
2014/08/13 ED - Wei Fan ED - Albert Bifet ED - Qiang Yang ED - Philip S. Yu ID - pmlr-v36-
li14 PB - PMLR DP - Proceedings of Machine Learning Research VL - 36 SP - 77 EP - 87 L1 -
http://proceedings.mlr.press/v36/li14.pdf UR -
https://proceedings.mlr.press/v36/li14.html AB - The accuracy and effectiveness of matrix
factorization technique were well demonstrated in the Netflix movie recommendation
contest. Among the numerous solutions for matrix factorization, Stochastic Gradient
Descent (SGD) is one of the most widely used algorithms. However, as a sequential
approach, SGD algorithm cannot directly be used in the Distributed Cluster Environment
(DCE). In this paper, we propose a fast distributed SGD algorithm named FDSGD for matrix
factorization, which can run efficiently in DCE. This algorithm solves data sharing problem
based on independent storage system to avoid data synchronization which may cause a
big influence to algorithm performance, and synchronous operation problem in DCE using
a distributed synchronization tool so that distributed cooperation threads can perform in a
harmonious environment. ER -
Copy to Clipboard Download
APA
Li, F., Wu, B., Xu, L., Shi, C. & Shi, J.. (2014). A Fast Distributed Stochastic Gradient
Descent Algorithm for Matrix Factorization. Proceedings of the 3rd International Workshop
on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems,
Programming Models and Applications, in Proceedings of Machine Learning
Research 36:77-87 Available from https://proceedings.mlr.press/v36/li14.html.
Copy to Clipboard Download
Related Material
• Download PDF
