Football Forecast

Football Forecast: How GxG and GAxGA Shape Match Analysis

Data and Core Metrics

The Football Forecast relies on Opta data via fbref as its foundation, focusing on two core metrics: GxG and GAxGA . These figures blend actual performance with underlying expected values, including xG and npxG (non-penalty expected goals). For more information regarding Expected Goals, check out my blog post: xG Explained: What Are Expected Goals?

This approach means that even when a team appears to lose “undeservedly” its strength rating can still rise and therefore improving its projected position in the table.  After each match the home and away team get assigned an initial GxG and GAxGA value purely based on raw stats, ignoring key factors like opponent strength and home advantage. In the next step, these values are adjusted, by the leagues typical home advantage and by the opponent’s strength.

These adjustments drastically influence how analysts interpret results. They transform a raw GxG value of 1 away at Arsenal’s Emirates Stadium into an adjusted value of 1.82, while scoring 1 GxG against Southampton at home reduces the adjusted figure to about 0.6. This highlights how much easier it becomes to score against weaker defenses.

Refining the Numbers

After the calculation of the GxG and GAxGA values, an exponential moving average (EMA) is applied to produce trailing values. So, all the games are being considered for each team, with the most recent games having the highest weight. This ensures, that the model stays up to date with a team’s current form.

The latest values are taken from each team and are getting normalized around 1. For example, a team with a GxG ratio of 0.9 and a GAxGA ratio of 0.9 means that the team scores 10% less than the current league average, however, also concedes 10% fewer goals than the current league average. Union Berlin provides an interesting case study: with a GxG ratio of around 0.59, they are dead last in the Bundesliga, however they have the 4th best defense, balancing things out to create a stable mid-table projection.

With the final ratio values in place, simulations for the remaining league games can begin.

Simulation Process

Once the final offensive and defensive values are assigned to each team, they are plugged into a Monte Carlo simulation. Each league is simulated 20,000 times using a Poisson distribution. The number 20,000 provides a solid balance, generating reliable projections without excessive computing times.

The image below illustrates how a Poisson distribution appears in practice, showing how different probabilities are assigned to potential goal outcomes based on a given scoring rate.

After running the simulations, results are compiled for every team. This makes it possible to determine probabilities of winning the title, qualifying for the UEFA Champions League, or facing relegation. At the beginning of the season, everything is still possible, with multiple contenders for every scenario. As the season progresses and matchdays unfold, these probabilities become more and more precise.

Football League Forecast & Prediction | StatsUltra

Premier League Forecast

Updated on 11/10/2024
Team Strength Win Premier League UCL Qualification Relegation Points xGD
Liverpool Logo Liverpool Liverpool LIV
88.6
>99%
100%
88 52
Arsenal Logo Arsenal Arsenal ARS
87.9
<1%
>99%
76 37
Nott'ham Forest Logo Nott’ham Forest Nottingham Forest NFO
78.5
73%
68 17
Manchester City Logo Manchester City Manchester City MCI
84.9
58%
66 24
Newcastle Utd Logo Newcastle Utd Newcastle NEW
80.7
29%
64 14
Chelsea Logo Chelsea Chelsea CHE
80.6
26%
63 19
Brighton Logo Brighton Brighton BHA
79.6
9%
61 9
Bournemouth Logo Bournemouth Bournemouth BOU
80.8
4%
59 16
Fulham Logo Fulham Fulham FUL
77.1
<1%
56 4
Aston Villa Logo Aston Villa Aston Villa AVL
74.3
<1%
56 -6
Crystal Palace Logo Crystal Palace Crystal Palace CRY
80.5
<1%
53 4
Brentford Logo Brentford Brentford BRE
75.4
<1%
53 4
Manchester Utd Logo Manchester Utd Manchester United MUN
72.3
47 -7
Tottenham Logo Tottenham Tottenham TOT
76.8
46 12
Everton Logo Everton Everton EVE
75.8
45 -6
West Ham Logo West Ham West Ham WHU
71.4
45 -18
Wolves Logo Wolves Wolves WOL
70.3
<1%
37 -20
Ipswich Town Logo Ipswich Town Ipswich IPS
61.5
>99%
24 -43
Leicester City Logo Leicester City Leicester LEI
58.9
>99%
23 -51
Southampton Logo Southampton Southampton SOU
56.6
100%
15 -61