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Premier League 2015-2016 Prediction league table based on the expected goals data model

Updated almost 9 years ago
Predicted Premier League Table
Current Premier League Table
# Club P xGF
Expected Goals For
Prediction metric
xGA
Expected Goals Against
Prediction metric
xGD
Expected Goal Difference
Prediction metric
xPts
Expected Points™
Predicted final points tally of the season
PDO
PDO
Shot accuracy metric
xPDO
Expected PDO
Shot accuracy metric based on expected goals
TSR
Total Shots Ratio
Overall dominance metric, higher is better
predRk
Prediction Rank™
Expected performance
1 1 Arsenal 38 74.29 33.57 +40.72 81 926 920 0.59 1671
2 3 Manchester City 38 70.7 38.82 +31.89 70 869 881 0.67 1516
3 5 Tottenham 38 61.72 35.97 +25.75 60 922 911 0.58 1480
4 2 Leicester 38 58.96 48.37 +10.58 64 877 889 0.53 1294
5 4 Manchester United 38 44.11 35.24 +8.87 51 902 890 0.55 1291
6 9 Liverpool 38 46.18 32.22 +13.96 54 866 912 0.61 1237
7 12 Southampton 38 50.82 40.88 +9.94 45 893 907 0.55 1226
8 6 Crystal Palace 38 45.0 46.53 -1.53 44 937 918 0.45 1202
9 7 Watford 38 36.49 37.4 -0.91 44 922 918 0.5 1187
10 10 Everton 38 47.42 49.33 -1.91 34 895 903 0.48 1105
11 8 West Ham 38 44.94 52.59 -7.64 35 919 909 0.47 1094
12 11 Stoke 38 38.66 45.98 -7.32 36 936 917 0.39 1092
13 16 Chelsea 38 44.95 44.93 +0.02 36 858 894 0.54 1062
14 17 Swansea 38 36.36 41.39 -5.03 30 886 912 0.5 1016
15 13 West Bromwich Albion 38 31.74 48.29 -16.55 27 903 909 0.37 926
16 18 Norwich 38 38.54 56.24 -17.7 23 867 884 0.46 881
17 14 Bournemouth 38 39.88 52.95 -13.08 31 812 861 0.54 875
18 15 Newcastle 38 35.52 59.1 -23.58 22 879 900 0.35 802
19 19 Sunderland 38 36.78 62.09 -25.3 13 869 890 0.41 770
20 20 Aston Villa 38 29.48 52.1 -22.62 9 859 894 0.44 758
# Club P W D L GF GA GD SF SA Pts
1 2 Leicester 17 11 5 1 37 24 +13 222 195 38
2 1 Arsenal 17 11 3 3 31 14 +17 275 189 36
3 3 Manchester City 17 10 2 5 33 19 +14 292 146 32
4 5 Tottenham 17 7 8 2 28 14 +14 249 181 29
5 4 Manchester United 17 8 5 4 22 14 +8 176 144 29
6 6 Crystal Palace 17 9 2 6 23 16 +7 206 254 29
7 7 Watford 17 8 4 5 21 16 +5 209 205 28
8 8 West Ham 17 6 7 4 25 21 +4 233 260 25
9 9 Liverpool 17 6 6 5 20 22 -2 258 165 24
10 10 Everton 17 5 8 4 31 24 +7 209 229 23
11 11 Stoke 17 6 5 6 14 16 -2 158 250 23
12 12 Southampton 17 5 6 6 21 21 +0 240 197 21
13 13 West Bromwich Albion 17 5 5 7 17 23 -6 138 239 20
14 14 Bournemouth 17 5 4 8 22 32 -10 202 171 19
15 16 Chelsea 17 5 3 9 21 27 -6 226 191 18
16 18 Norwich 17 4 5 8 20 29 -9 188 218 17
17 15 Newcastle 17 4 5 8 19 32 -13 146 266 17
18 17 Swansea 17 3 6 8 15 24 -9 211 212 15
19 19 Sunderland 17 3 3 11 18 33 -15 175 253 12
20 20 Aston Villa 17 1 4 12 14 31 -17 175 220 7

Glossary

Expected Goals (xG)

This is the number of expected goals a team will score based on shot data from previous games. Shot zones, types, attempts, accuracy and other stats are all taken into account. By calculating expected goals for (xGF) and against (xGA), we reach an expected goal difference (xGD). This is then compared to the team's current goal difference to calculate performance.

Expected Points™ (xPts)

Our own formula based on a number of factors. The team's current points-per-game is multiplied by 38 to serve as the baseline. We then boost that number using our own predRk metric (see below) and then adjust further using team performance according to xGD.

PDO

This formula originated in ice hockey and was translated into football terms by James Grayson. It gives an indication of how well a team is performing in terms of goal conversion. Higher is better.

( (goals for / shots for) + ( 1 – (goals against / shots against) ) ) * 1000

Expected PDO (xPDO)

The same formula as PDO, but with expected goals (xG) instead of current goals. The end result is a baseline number that should give an indication of form: if the xPDO is lower than the PDO, it means the team is overperforming and scoring more goals than it should.

Total Shots Ratio (TSR)

Before the emergence of expected goals (xG), the preferred prediction metric was total shots ratio (TSR). It's essentially a dominance formula, calculated by dividing the number of shots taken by the total shots overall. The closer a team is to 1.0, the more dominant the team has been in the season so far.

(shots for / (shots for + shots against)

Prediction Rank™ (predRk)

This is our own formula to score teams based on a number of different factors, including all of the above mentioned metrics. This score is then used as the basis for our league prediction.

Credit

The base numbers on this page all originate from Opta via WhoScored and Squawka. The xG and predictive models are partly opinionated, which is why our xG data is an average of several different sources:

Paul Riley (@footballfactman)

Paul's data is a great source based on his own shots model explained here. This data is regularly updated and readily available for everyone.

Michael Caley (@MC_of_A)

Despite being a Spurs fan (boo), Michael's xG model has great detail. His model is explained here.

Danny Page (@DannyPage)

Danny is a developer that has created a few interesting match prediction tools, both for the outcome of a specific game and also a long-term xG simulator. To use his tools you need data, which can be lifted from the aforementioned sources.