# Euro 2020 Predictive Model based on FIFA Ranking System

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In a previous post, we built a Predictive Model based on FIFA Ranking and making the assumption that the points follow a normal distribution. If we look closer at FIFA’s Ranking Model we will see that it is based on the ELO System where the expected result of the game can be extracted from the following formula:

## Simulate the Final-16 Phase Based on the Expected Result

Let’s run 10000 simulations to estimate the probability of the Euro 2020 Winner.

# get the UEFA Ranking ranking<-list(bel=1783, fra=1757, eng=1687, por=1666, esp=1648, ita=1642, den=1632, ger=1609, sui=1606, cro=1606, net=1598, wal=1570, swe=1570, aus=1523, ukr=1515, cze=1459) win_prob<-function(a,b) { w_prob<-1/(1+10^(-(a-b)/600)) outcome<-sample(c(TRUE,FALSE), 1, prob=c(w_prob, 1-w_prob)) return(outcome) } sim_champion<-c() for (i in 1:10000) { ####################### #### Final 16 ####################### # game bel vs por teams_game1<-c("bel","por") game1<-win_prob(ranking[[teams_game1[1]]], ranking[[teams_game1[2]]]) if (game1) { qualified_game1<-teams_game1[1] } else { qualified_game1<-teams_game1[2]} qualified_game1 # game ita vs aus teams_game2<-c("ita","aus") game2<-win_prob(ranking[[teams_game2[1]]], ranking[[teams_game2[2]]]) if (game2) { qualified_game2<-teams_game2[1] } else { qualified_game2<-teams_game2[2]} qualified_game2 # game fra vs sui teams_game3<-c("fra","sui") game3<-win_prob(ranking[[teams_game3[1]]], ranking[[teams_game3[2]]]) if (game3) { qualified_game3<-teams_game3[1] } else { qualified_game3<-teams_game3[2]} qualified_game3 # game cro vs esp teams_game4<-c("cro","esp") game4<-win_prob(ranking[[teams_game4[1]]], ranking[[teams_game4[2]]]) if (game4) { qualified_game4<-teams_game4[1] } else { qualified_game4<-teams_game4[2]} qualified_game4 # game swe vs ukr teams_game5<-c("swe","ukr") game5<-win_prob(ranking[[teams_game5[1]]], ranking[[teams_game5[2]]]) if (game5) { qualified_game5<-teams_game5[1] } else { qualified_game5<-teams_game5[2]} qualified_game5 # game eng vs ger teams_game6<-c("eng","ger") game6<-win_prob(ranking[[teams_game6[1]]], ranking[[teams_game6[2]]]) if (game6) { qualified_game6<-teams_game6[1] } else { qualified_game6<-teams_game6[2]} qualified_game6 # game net vs cze teams_game7<-c("net","cze") game7<-win_prob(ranking[[teams_game7[1]]], ranking[[teams_game7[2]]]) if (game7) { qualified_game7<-teams_game7[1] } else { qualified_game7<-teams_game7[2]} qualified_game7 # game wal vs den teams_game8<-c("wal","den") game8<-win_prob(ranking[[teams_game8[1]]], ranking[[teams_game8[2]]]) if (game8) { qualified_game8<-teams_game8[1] } else { qualified_game8<-teams_game8[2]} qualified_game8 ####################### #### Final 8 ####################### teams_f8_1<-c(qualified_game1,qualified_game2) game_f8_1<-win_prob(ranking[[teams_f8_1[1]]], ranking[[teams_f8_1[2]]]) if (game_f8_1) { qualified_f8_1<-teams_f8_1[1] } else { qualified_f8_1<-teams_f8_1[2]} qualified_f8_1 teams_f8_2<-c(qualified_game3,qualified_game4) game_f8_2<-win_prob(ranking[[teams_f8_2[1]]], ranking[[teams_f8_2[2]]]) if (game_f8_2) { qualified_f8_2<-teams_f8_2[1] } else { qualified_f8_2<-teams_f8_2[2]} qualified_f8_2 teams_f8_3<-c(qualified_game5,qualified_game6) game_f8_3<-win_prob(ranking[[teams_f8_3[1]]], ranking[[teams_f8_3[2]]]) if (game_f8_3) { qualified_f8_3<-teams_f8_3[1] } else { qualified_f8_3<-teams_f8_3[2]} qualified_f8_3 teams_f8_4<-c(qualified_game7,qualified_game8) game_f8_4<-win_prob(ranking[[teams_f8_4[1]]], ranking[[teams_f8_4[2]]]) if (game_f8_4) { qualified_f8_4<-teams_f8_4[1] } else { qualified_f8_4<-teams_f8_4[2]} qualified_f8_4 ####################### #### Final 4 ####################### teams_f4_1<-c(qualified_f8_1,qualified_f8_2) game_f4_1<-win_prob(ranking[[teams_f4_1[1]]], ranking[[teams_f4_1[2]]]) if (game_f4_1) { qualified_f4_1<-teams_f4_1[1] } else { qualified_f4_1<-teams_f4_1[2]} qualified_f4_1 teams_f4_2<-c(qualified_f8_3,qualified_f8_4) game_f4_2<-win_prob(ranking[[teams_f4_2[1]]], ranking[[teams_f4_2[2]]]) if (game_f4_2) { qualified_f4_2<-teams_f4_2[1] } else { qualified_f4_2<-teams_f4_2[2]} qualified_f4_2 ####################### #### Final ####################### teams_f<-c(qualified_f4_1,qualified_f4_2) game_f<-win_prob(ranking[[teams_f[1]]], ranking[[teams_f[2]]]) if (game_f) { champion<-teams_f[1] } else { champion<-teams_f[2]} sim_champion<-c(sim_champion,champion) } prop.table(table(sim_champion))*100

**Outcome:**

sim_champion aus bel cro cze den eng esp fra ger ita net por sui swe ukr wal 1.68 16.22 3.74 1.33 7.64 10.17 6.53 14.70 4.75 6.83 5.99 6.21 3.38 4.37 2.28 4.18

As we can see, **Belgium has 16.22%** to win the Euro 2020 and it is the favorite according to this approach.

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