Massey Ratings#

Massey Ratings provide a mathematically robust method for evaluating and ranking football teams based on their match results.

The Massey Rating system considers the strength of each team’s opponents and the margins of victory or defeat, resulting in ratings that accurately reflect relative team performance.

This makes it particularly useful for predicting outcomes, comparing team quality across leagues, and informing betting decisions by identifying teams whose performance might be underrated or overrated by bookmakers.

[1]:

import penaltyblog as pb

[2]:

fbd = pb.scrapers.FootballData("ENG Premier League", "2020-2021")
df = fbd.get_fixtures()

df.head()

[2]:
date datetime season competition div time team_home team_away fthg ftag ... b365_cahh b365_caha pcahh pcaha max_cahh max_caha avg_cahh avg_caha goals_home goals_away
id
1599868800---crystal_palace---southampton 2020-09-12 2020-09-12 15:00:00 2020-2021 ENG Premier League E0 15:00 Crystal Palace Southampton 1 0 ... 1.78 2.13 1.79 2.17 1.85 2.18 1.79 2.12 1 0
1599868800---fulham---arsenal 2020-09-12 2020-09-12 12:30:00 2020-2021 ENG Premier League E0 12:30 Fulham Arsenal 0 3 ... 2.01 1.89 2.02 1.91 2.13 1.92 2.02 1.87 0 3
1599868800---liverpool---leeds 2020-09-12 2020-09-12 17:30:00 2020-2021 ENG Premier League E0 17:30 Liverpool Leeds 4 3 ... 1.85 2.05 1.85 2.08 1.90 2.16 1.84 2.04 4 3
1599868800---west_ham---newcastle 2020-09-12 2020-09-12 20:00:00 2020-2021 ENG Premier League E0 20:00 West Ham Newcastle 0 2 ... 2.03 1.87 2.04 1.88 2.09 1.91 2.02 1.86 0 2
1599955200---tottenham---everton 2020-09-13 2020-09-13 16:30:00 2020-2021 ENG Premier League E0 16:30 Tottenham Everton 0 1 ... 2.09 1.81 2.09 1.85 2.16 1.86 2.08 1.81 0 1

5 rows × 111 columns

[3]:

massey = pb.ratings.Massey(
    df["goals_home"], df["goals_away"], df["team_home"], df["team_away"]
)
massey.get_ratings()

[3]:
team rating offence defence
0 Man City 1.275 1.486184 -0.211184
1 Man United 0.725 1.238962 -0.513962
2 Liverpool 0.65 1.10424 -0.45424
3 Tottenham 0.575 1.108406 -0.533406
4 Chelsea 0.55 0.832018 -0.282018
5 Leicester 0.45 1.115351 -0.665351
6 Arsenal 0.4 0.757018 -0.357018
7 West Ham 0.375 0.952851 -0.577851
8 Aston Villa 0.225 0.76674 -0.54174
9 Leeds 0.2 0.962573 -0.762573
10 Everton -0.025 0.558406 -0.583406
11 Brighton -0.15 0.370906 -0.520906
12 Newcastle -0.4 0.551462 -0.951462
13 Wolves -0.4 0.273684 -0.673684
14 Southampton -0.525 0.586184 -1.111184
15 Burnley -0.55 0.198684 -0.748684
16 Crystal Palace -0.625 0.425073 -1.050073
17 Fulham -0.65 0.037573 -0.687573
18 West Brom -1.025 0.280629 -1.305629
19 Sheffield United -1.075 -0.13326 -0.94174 
[4]:

import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

%config InlineBackend.figure_format='retina'
plt.rcParams["figure.figsize"] = [10, 7]
sns.set_style("whitegrid")

massey = pb.ratings.Massey(
    df["goals_home"], df["goals_away"], df["team_home"], df["team_away"]
)
ratings = massey.get_ratings()
ratings["colours"] = np.where(ratings["rating"] > 0, "#33b864", "#a03623")
fig, ax = plt.subplots()
y_pos = np.arange(len(ratings))
performance = ratings["rating"]
ax.barh(y_pos, performance, align="center", color=ratings["colours"])
ax.set_yticks(y_pos)
ax.set_yticklabels(ratings["team"], fontweight="bold")
ax.invert_yaxis()
ax.set_xlabel("Massey Rating")
ax.set_title("Massey Ratings - EPL", fontweight="bold")

rects = ax.patches
for rect in rects:
    x_value = rect.get_width()
    y_value = rect.get_y() + rect.get_height() / 2
    space = 2
    ha = "left"

    if x_value < 0:
        space *= -1
        ha = "right"

    label = "{:.2f}".format(x_value)

    # Create annotation
    plt.annotate(
        label,
        (x_value, y_value),
        xytext=(space, 0),
        textcoords="offset points",
        va="center",
        ha=ha,
        fontsize=8,
        fontweight="bold",
    )
../_images/ratings_massey_ratings_4_0.png 
[5]:

import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

%config InlineBackend.figure_format='retina'
plt.rcParams["figure.figsize"] = [10, 7]
sns.set_style("whitegrid")

massey = pb.ratings.Massey(
    df["goals_home"], df["goals_away"], df["team_home"], df["team_away"]
)
ratings = massey.get_ratings()
ratings["colours"] = np.where(ratings["offence"] > 0, "#33b864", "#a03623")
ratings = ratings.sort_values("offence", ascending=False)
fig, ax = plt.subplots()
y_pos = np.arange(len(ratings))
performance = ratings["offence"]
ax.barh(y_pos, performance, align="center", color=ratings["colours"])
ax.set_yticks(y_pos)
ax.set_yticklabels(ratings["team"], fontweight="bold")
ax.invert_yaxis()
ax.set_xlabel("Massey Rating")
ax.set_title("Massey Offence Ratings - EPL", fontweight="bold")

rects = ax.patches

for rect in rects:
    x_value = rect.get_width()
    y_value = rect.get_y() + rect.get_height() / 2
    space = 2
    ha = "left"

    if x_value < 0:
        space *= -1
        ha = "right"

    label = "{:.2f}".format(x_value)

    # Create annotation
    plt.annotate(
        label,
        (x_value, y_value),
        xytext=(space, 0),
        textcoords="offset points",
        va="center",
        ha=ha,
        fontsize=8,
        fontweight="bold",
    )
../_images/ratings_massey_ratings_5_0.png 
[6]:

import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

%config InlineBackend.figure_format='retina'
plt.rcParams["figure.figsize"] = [10, 7]
sns.set_style("whitegrid")

ratings = pb.massey.ratings(
    df["goals_home"], df["goals_away"], df["team_home"], df["team_away"]
)
ratings["colours"] = np.where(ratings["defence"] > 0, "#33b864", "#a03623")
ratings = ratings.sort_values("defence", ascending=False)
fig, ax = plt.subplots()
y_pos = np.arange(len(ratings))
performance = ratings["defence"]
ax.barh(y_pos, performance, align="center", color=ratings["colours"])
ax.set_yticks(y_pos)
ax.set_yticklabels(ratings["team"], fontweight="bold")
ax.invert_yaxis()
ax.set_xlabel("Massey Rating")
ax.set_title("Massey Defence Ratings - EPL", fontweight="bold")

rects = ax.patches

for rect in rects:
    x_value = rect.get_width()
    y_value = rect.get_y() + rect.get_height() / 2
    space = 2
    ha = "left"

    if x_value < 0:
        space *= -1
        ha = "right"

    label = "{:.2f}".format(x_value)

    plt.annotate(
        label,
        (x_value, y_value),
        xytext=(space, 0),
        textcoords="offset points",
        va="center",
        ha=ha,
        fontsize=8,
        fontweight="bold",
    )

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Input In [6], in <cell line: 0>()
      6 plt.rcParams["figure.figsize"] = [10, 7]
      7 sns.set_style("whitegrid")
----> 9 ratings = pb.massey.ratings(df["goals_home"], df["goals_away"], df["team_home"], df["team_away"])
     10 ratings["colours"] = np.where(ratings["defence"] > 0, "#33b864", "#a03623")
     11 ratings = ratings.sort_values("defence", ascending=False)

AttributeError: module 'penaltyblog' has no attribute 'massey'

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