International football is difficult to analyse. Unlike domestic league football, where vast quantities of data exist to assess team and player performance in a variety of conditions, negligible relevant data is available for international football. It is, by its nature infrequent – so tournament line-ups may bear little resemblance to those of previous matches – with often little or no data to assess how teams fare in truly competitive circumstances.

But the challenge of analysing international football is also a fascinating opportunity, because no-one else will have adequate data either – this levels the playing field for those that don’t usually have access and resources to carry out full analysis. And, for those that like to bet, international tournament football can offer some great value.

So, for Euro 2016 I’m trying to provide a variety of insight that might inform how it will unfold, and use it to estimate the likelihood of different outcomes (including the winner!) in a similar way to my Premier League projections. The building blocks for this are International team ratings, which I outline here.

As mentioned, assessing international teams is tricky. Some assessments are readily available online – e.g. FIFA and ELO ratings. But these aren’t perfect (particularly FIFA) and for my projections I need ratings in terms of attack and defence strength. So I’ve based my international ratings on my “adjusted goals” method that I use for domestic football leagues (described here). This is a simple method based on goals and shots, for and against.

The main problem is that for league football it’s easy to derive ratings using a team’s underlying data. But there’s not enough data to do this for international football team. So I’ve worked out ratings for each team by combining the “adjusted goals” rating for each player in a team’s squad (i.e. each player has his own attack and defence strength rating, which also helps in assessing the strengths of team line-ups). The steps are:

1. Broadly assume that each player’s rating is at the same level as the club they play for. i.e. to play regularly Bayern Munich or Real Madrid you need to be pretty good. However, this obviously doesn’t accurately assess players that perform better at international football than club football (or vice versa).
2. Adjust team ratings for a player’s attacking or defensive strength (where data available) e.g. goals, assists, tackles, interceptions. So e.g. Ronaldo has a high attacking strength, Sergio Ramos is strong defensively. I’ve needed to make some subjective adjustments for players from some of the more obscure leagues.
3. Adjust team/player ratings for the strength of the league they play in, for this I’ve used UEFA coefficient and Euro club index, and applied some subjectivity.
4. Each team’s overall rating is the average attack and defence rating for the best 16 players in the squad. Only one goalkeeper is included in the top 16 (and goalkeeper only contributes to a team’s defensive rating).

This produces the following ratings for the 24 Euro 2016 teams (note, I’ve not yet allowed for France’s home advantage).

Rank	Team	Adjusted goals for	Adjusted goals against	Adjusted goal difference
1	Spain	2.14	0.91	1.23
2	Germany	1.83	1.01	0.82
3	France	1.78	1.00	0.78
4	England	1.83	1.19	0.64
5	Portugal	1.64	1.16	0.48
6	Belgium	1.77	1.31	0.47
7	Italy	1.49	1.07	0.42
8	Croatia	1.50	1.18	0.32
9	Austria	1.29	1.27	0.02
10	Turkey	1.38	1.37	0.01
11	Ukraine	1.30	1.34	-0.04
12	Czech Republic	1.17	1.25	-0.08
13	Switzerland	1.27	1.36	-0.09
14	Wales	1.29	1.42	-0.13
15	Republic of Ireland	1.06	1.40	-0.34
16	Russia	1.14	1.48	-0.34
17	Poland	1.09	1.51	-0.42
18	Sweden	1.11	1.64	-0.53
19	Slovakia	1.01	1.59	-0.57
20	Albania	0.83	1.62	-0.79
21	Northern Ireland	0.77	1.61	-0.84
22	Romania	0.78	1.74	-0.96
23	Iceland	0.77	1.75	-0.98
24	Hungary	0.72	1.94	-1.22

 

I’m aware that there’s an element of subjectivity here, and that there other factors that need to be allowed for such as manager’s tactics and player fitness. But these ratings will form the basis of my projections – with adjustments, where necessary, throughout the tournament.

Next up – tournament projection and assessing the likely winner

Previous Euro 2016 articles

Euro 2016 preview 1 – how goal patterns repeat in international tournamentsEuro 2016 preview 1 – how goal patterns repeat in international tournaments

Euro 2016 – Why England’s most likely last 16 opponents are Germany.

These are the individual player ratings used for the top 100 (non-goalkeeper) tournament players.

Rank	Player	Country	Adj Goals Difference	Adj Goals For	Adj Goals Against
1	Gareth Bale	Wales	3.37	4.59	1.22
2	Cristiano Ronaldo	Portugal	2.69	4.03	1.34
3	Zlatan Ibrahimović	Sweden	2.23	3.57	1.34
4	Thomas Müller	Germany	2.10	2.87	0.76
5	Lucas Vázquez	Spain	2.06	3.19	1.13
6	Robert Lewandowski	Poland	1.99	2.84	0.85
7	Antoine Griezmann	France	1.81	2.61	0.79
8	Koke	Spain	1.73	2.43	0.70
9	Toni Kroos	Germany	1.71	2.75	1.04
10	Ivan Rakitić	Croatia	1.69	2.48	0.79
11	Thiago	Spain	1.64	2.05	0.41
12	Arda Turan	Turkey	1.62	2.71	1.09
13	Mario Götze	Germany	1.58	2.34	0.75
14	Dele Alli	England	1.51	2.52	1.02
15	Luka Modrić	Croatia	1.49	2.50	1.01
16	Kevin De Bruyne	Belgium	1.45	2.76	1.31
17	Sergio Ramos	Spain	1.43	2.05	0.62
18	Jordi Alba	Spain	1.40	2.10	0.70
19	Mesut Özil	Germany	1.39	2.88	1.48
20	Kingsley Coman	France	1.38	2.20	0.82
21	David Silva	Spain	1.33	2.61	1.28
22	Sergio Busquets	Spain	1.32	1.98	0.66
23	Gerard Piqué	Spain	1.27	1.90	0.63
24	Jérôme Boateng	Germany	1.23	1.73	0.49
25	Mateo Kovačić	Croatia	1.23	2.21	0.98
26	Dimitri Payet	France	1.22	3.06	1.84
27	Andrés Iniesta	Spain	1.21	2.10	0.89
28	Álvaro Morata	Spain	1.20	2.25	1.05
29	Pepe	Portugal	1.15	1.87	0.72
30	Harry Kane	England	1.15	2.48	1.34
31	Aritz Aduriz	Spain	1.14	2.51	1.37
32	Dries Mertens	Belgium	1.12	2.34	1.22
33	Paul Pogba	France	1.09	1.96	0.87
34	James Milner	England	1.07	2.36	1.29
35	Marc Bartra	Spain	1.07	1.89	0.82
36	Lorenzo Insigne	Italy	1.07	2.37	1.31
37	Thomas Vermaelen	Belgium	1.04	1.83	0.80
38	Jamie Vardy	England	1.01	2.58	1.56
39	Yannick Ferreira Carrasco	Belgium	0.98	1.80	0.81
40	Marek Hamšík	Slovakia	0.96	2.12	1.17
41	Blaise Matuidi	France	0.96	1.90	0.94
42	David Alaba	Austria	0.93	1.55	0.62
43	Mats Hummels	Germany	0.89	1.50	0.61
44	Olivier Giroud	France	0.88	2.31	1.43
45	Mario Mandžukić	Croatia	0.87	1.88	1.01
46	Arkadiusz Milik	Poland	0.83	2.16	1.33
47	Yevhen Konoplyanka	Ukraine	0.81	2.35	1.54
48	Nolito	Spain	0.81	2.40	1.59
49	Sami Khedira	Germany	0.80	1.78	0.99
50	Simone Zaza	Italy	0.79	1.93	1.14
51	Mousa Dembélé	Belgium	0.77	1.65	0.88
52	Hakan Çalhanoğlu	Turkey	0.75	2.12	1.37
53	Toby Alderweireld	Belgium	0.72	1.49	0.77
54	Joshua Kimmich	Germany	0.72	1.70	0.99
55	Patrice Evra	France	0.71	1.44	0.73
56	Giorgio Chiellini	Italy	0.69	1.23	0.54
57	Danny Rose	England	0.68	1.59	0.91
58	Renato Sanches	Portugal	0.68	1.66	0.98
59	Kyle Walker	England	0.67	1.49	0.82
60	Ben Davies	Wales	0.67	1.54	0.87
61	Adam Lallana	England	0.66	1.95	1.29
62	Nuri Şahin	Turkey	0.65	1.75	1.10
63	Leonardo Bonucci	Italy	0.64	1.26	0.63
64	Christian Fuchs	Austria	0.63	1.49	0.86
65	Jordan Henderson	England	0.61	1.83	1.21
66	Aaron Ramsey	Wales	0.61	1.77	1.16
67	N’Golo Kanté	France	0.61	1.35	0.74
68	Juanfran	Spain	0.61	1.29	0.69
69	Christophe Jallet	France	0.60	1.52	0.93
70	Christian Benteke	Belgium	0.60	2.28	1.69
71	Julian Weigl	Germany	0.58	1.41	0.83
72	Alessandro Florenzi	Italy	0.58	1.76	1.18
73	Tomáš Rosický	Czech Republic	0.57	1.68	1.12
74	Graziano Pellè	Italy	0.56	2.10	1.54
75	Laurent Koscielny	France	0.55	1.28	0.73
76	João Mário	Portugal	0.55	1.49	0.94
77	William Carvalho	Portugal	0.55	1.49	0.94
78	Adrien Silva	Portugal	0.55	1.49	0.94
79	Raheem Sterling	England	0.55	1.86	1.31
80	Stephan El Shaarawy	Italy	0.54	2.16	1.62
81	Thiago Motta	Italy	0.54	1.56	1.02
82	Bacary Sagna	France	0.54	1.46	0.92
83	Eric Dier	England	0.51	1.51	1.00
84	Bruno Soriano	Spain	0.51	1.31	0.81
85	Duje Čop	Croatia	0.50	1.73	1.23
86	Admir Mehmedi	Switzerland	0.49	1.99	1.50
87	Mikel San José	Spain	0.48	1.35	0.87
88	Victor Lindelöf	Sweden	0.47	1.16	0.69
89	Eliseu	Portugal	0.47	1.16	0.69
90	Cesc Fàbregas	Spain	0.47	1.97	1.50
91	Vieirinha	Portugal	0.46	1.54	1.08
92	Jan Vertonghen	Belgium	0.45	1.22	0.77
93	Shane Long	Republic of Ireland	0.43	1.95	1.52
94	Andrea Barzagli	Italy	0.42	1.15	0.73
95	Steven Davis	Northern Ireland	0.41	1.73	1.32
96	Yohan Cabaye	France	0.41	1.51	1.09
97	Vlad Chiricheș	Romania	0.41	1.32	0.92
98	Zlatko Junuzović	Austria	0.39	2.24	1.85
99	Stefano Sturaro	Italy	0.39	1.25	0.86
100	Lucas Digne	France	0.38	1.43	1.06