Results tables.

Results tables.

These are the results between Team Test (average attribute score, 10) and Team Opposition (average attribute score, 13) in a friendly match, both teams controlled by the AI, with each scenario repeated five times. Obviously, Team Test are going to get battered almost every time, but it’s the extent of the battering which interests me. (If you want to argue that both teams should be exactly equal, that’s something I might take on board in the future.)

Later on, I’ll work out which formations actually seem to work the best against another formation, but for now, here are the raw results:

(Original image – inc. com. Effects by Lunapic.)

Table 1 – 13-attribute AI v 10-attribute AI.

MatchOppo ScoreTest ScoreOppo FormationTest FormationOppo xGTest xGOppo ShotsTest ShotsOppo Poss%Test Poss%
1304424422.080.421856832
2414424422.570.972357030
3604424422.810.462356238
42044244240.082727030
5304424423.650.42766733
6214425221 AM DM1.60.472486436
7804425221 AM DM4.890.253217723
8304425221 AM DM4.60.243447030
9304425221 AM DM3.890.222326832
10504425221 AM DM3.950.292627426
1140442541 Diamond WB2.960.42256238
1230442541 Diamond WB1.720.542146634
1340442541 Diamond WB3.3902707426
1450442541 Diamond WB3.380.682156436
1530442541 Diamond WB4.750.173236733
16404424512.30.371146238
17514424513.170.62336733
18314424515.620.53227228
19304424514.730.692957129
20704424513.120.392336436
21104425221 WB1.70.042216634
22404425221 WB3.660.582646931
23404425221 WB2.350.042526238
24314425221 WB4.660.872937327
25514425221 WB2.080.41636337
264044241311 DM AM Narrow2.810.032216634
274044241311 DM AM Narrow4.30.252826337
284044241311 DM AM Narrow4.440.882826634
293044241311 DM AM Narrow4.560.582647030
303144241311 DM AM Narrow3.310.673036931
31504424240 DM AM Wide2.520.361935941
32504424240 DM AM Wide2.280.372557723
33304424240 DM AM Wide3.530.063216733
34414424240 DM AM Wide3.60.512237723
35314424240 DM AM Wide3.811.052386040
36814424222 DM Narrow5.760.184325941
37504424222 DM Narrow3.820.082427030
38504424222 DM Narrow1.960.271937030
39404424222 DM Narrow3.8702816832
40404424222 DM Narrow1.720.452646733
4150442433 DM Narrow3.980.083326535
4250442433 DM Narrow3.550.62437327
4340442433 DM Narrow3.660.173027723
4440442433 DM Narrow4.50.22827426
4530442433 DM Narrow3.410.293266634
4680442442 Diamond Narrow3.460.283626436
4731442442 Diamond Narrow1.960.531976436
4830442442 Diamond Narrow3.210.092146337
4930442442 Diamond Narrow2.50.422746634
5030442442 Diamond Narrow5.321.012596634
5170442523WB Wide3.7503906337
5221442523WB Wide3.050.282316634
5330442523WB Wide5.130.142826535
5450442523WB Wide4.610.392756733
5540442523WB Wide4.30.512747426
561204424231 Narrow4.360.174225644
57404424231 Narrow4.680.143326436
58404424231 Narrow2.820.282337129
59504424231 Narrow2.890.132226733
60404424231 Narrow2.640.333047426
60 matches, and 60 defeats – a three-point attribute gap in every area is apparently very hard to bridge, even when it’s AI v AI. Time to rethink, and even things up?

Table 2 – 10-attribute AI v 10-attribute AI. Both clubs have only one member of coaching staff – a manager, whose attributes are all 10. How does a formation with two deep-lying central midfielders in a 442 fare against a 442 diamond? Hopefully, I’m about to find out the answer to that, and other such questions!

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