In the 82nd minute of their 36th game of the EPL season, Michy Batshuayi’s goal secured Chelsea’s fifth English Premier League title. Even though Chelsea won the league with relative ease, it wasn’t all roses from the start. After the first six games, Chelsea had tallied only 10 points. Things came to a head when Chelsea was easily beaten 3-0 by red-hot Arsenal in late September. After that loss, Conte went from a back 4 to a back 3 that served him well at Juventus, and the results improved immediately with Chelsea reeling off 13 straight wins to put them on firm course to win the league.
With the new tools STATS have developed using machine learning, we give three reasons on how Chelsea won the league.
Reason No. 1: Chelsea were incredibly effective in converting chances
Although Chelsea scored the most goals this season, they only ranked fifth in the league in terms of chances created (see Figure 1). To estimate the number of chances created, we use the expected goals (xG) measure, which estimates the likelihood that the average league player will score a goal based on the situation (i.e., ball position, game-context etc. – see  for more details).
Figure 1: Plot showing how many goals each team could have expected to score given the situation (Chelsea rank 5th with approximately 60 goals expected).
However, what highlights their offensive effectiveness in this year’s EPL is their xG plus-minus (xGpm), which is +22.4, meaning that Chelsea scored +22 more goals this season than expected. To put this +22.4 measure in context, when we compare Chelsea with other teams this year, we see that they are executing their chances in a much more clinical fashion (see Figure 2). Tottenham are the next-closest team in terms of plus-minus with a +15.4 (although with two games remaining the Spurs were only +7.6 – meaning the last two games where the scored 13 goals somewhat inflated this statistic), followed by Liverpool (+4.8), Bournemouth (+4.6) and Burnley (+3.1). Southamption, on the other hand, were quite the opposite, missing more than 16 goals that the average team would have converted.
Figure 2: Ranking the teams on their goals-expected goals in the 16-17 EPL. Chelsea have a +22.4, seven more than Spurs.
From a historical perspective in terms of how this team compares in xGpm across the last six seasons in which we have calculated this statistic, we see that this Chelsea team are ranked third, with only Liverpool and Manchester City in the prolific 13-14 season being more effective (see Table 1).
Table 1: Ranked list of the most effective offensive teams across the last 6 seasons.
Needless to say, scoring 22 goals more than expected goes a long way to securing a title. However, as we will see in the next section, their defense played a massive role as well.
Reason No. 2: Defensively, Chelsea did not give up many chances
Similarly to what we did in the previous section, we can use the expected goals measure to analyze how effective a team’s defense is. Although Chelsea ranked fifth in creating chances, they are first defensively (see Figure 3).
Figure 3: Expected goals against measure which estimates how many goals a team should have conceded based on game situation. Chelsea gave up the fewest chances.
In terms of goals conceded, it is clear that Tottenham were far superior in terms of defense (26 vs 33). But when we look at the expected save (xS) measure, which estimates the likelihood that a shot will end up as a goal based on the player’s position and shot location, we can see that Hugo Lloris saved more than 10 goals that the “average league goalkeeper” would not have. Chelsea’s goalkeeper performance this season, on the other hand, was -2. Figure 4 shows how the goalkeepers fared based on goals conceded minus the expected save value.
Figure 4: Comparing goalkeeping performance this year based on Saves vs Expected Saves
Reason No. 3: Chelsea went to a back 3 to provide more defensive stability
In the previous two sections, we showed quantitatively how Chelsea fared both offensively and defensively in terms of goal-scoring chances. But as noted earlier, after six games and a poor run of form, Antonio Conte changed from a back 4 to a back 3 – a move that’s been hailed as a key decision in turning things around. In this section, we show how the change in formation changed their style of play.
To do this analysis, we compared the performances of Chelsea for the first six games (until the Arsenal vs Chelsea match on Sept. 24) to the performances after. A summary of some key performance metrics are shown in Table 2. From this table, it can be seen that although Chelsea averaged more shots with a back 4 (16.8 vs 14.1 per game), they actually averaged more goals with a back 3 (2.2 vs 1.7). Defensively, they conceded the same amount of shots, but with a back 3 they conceded far fewer goals per match (0.7 vs 1.5). In terms of possession, with a back 3 they actually gave up around 4% possession per game, which indicates a change in playing style.
Table 2: Comparing offensive and defensive metrics when Chelsea had a Back-4 and Back-3.
|Back 4||Back 3||Back 4||Back 3|
|Shots per game||16.8||14.1||8.5||8.6|
|Goals per game||1.7||2.2||1.5||0.7|
|xG per game||1.6||1.5||0.9||0.7|
|Possession per game||57.3%||53.3%||42.7%||46.7%|
Using a new metric developed at STATS, we can break up all continuous play possession into a series of “style” states, which automatically assigns a portion of a game into one of these distinct game phases. These style names are quite self-descriptive (i.e., direct-play, counter-attack, maintenance, build-up, sustained-threat, fast-tempo, crossing, high-press – but for more details see ).
In Figure 5, we compare Chelsea’s playing style between when they played with a back 3 and a back 4. From viewing this plot, it can be seen that when Chelsea played with a back 3 they used a lot more direct-play and their use of maintenance, build-up and sustained threat reduced. With a back 3, they also utilized less crosses. In terms of goal-scoring efficiency, this makes sense as it has been shown previously that the most effective way of scoring is via direct-play .
Figure 5: Chart comparing Chelsea’s playing style with a back-3 (blue) compared to back-4.
In Figure 6, we show the defensive playing style of Chelsea (i.e., how opposition teams tend to attack when they have possession of the ball). What is interesting to note is that we have the opposite occurring, with Chelsea having less direct-play and more maintenance and crossing against them. As having a back 3 is thought to give a team more “defensive stability,” it also correlates with Chelsea conceding fewer good chances.
Figure 6: The defensive playing style of Chelsea (i.e,. when teams have the possession of the ball against Chelsea).
Using new analysis tools developed at STATS, we have been able to objectively measure Chelsea’s title run using expected goals, expected saves and playing styles measures.
 In our analysis, we have classified own goals down to luck, so in determining the “expected goals plus-minus” (xGpm) we exclude own goals from the goals values (i.e., xGpm = (Goals – Own goals) – xG.