*This is the latest in a series of posts looking at which team level metrics are repeatable from season-to-season in the Premiership.*

As I’ve said before, it’s all well and good knowing that team ‘x’ took 20 shots in the first half against team ‘y’, but unless we know whether the number of shots a team takes is repeatable over time then trying to put that number into context is essentially useless (a point that is made far more eloquently by Richard Whittall in this column).

Ultimately, determining how repeatable a metric is allows it to be broken down into a ‘skill’ component – something that teams can control – and a ‘luck’ component – something teams have no control over. (For the story so far see I’ve placed a summary table at the bottom of this post, which I’ll continue to update in the future). Whilst those that are dominated by luck are wonderful insofar as it’s funny to watch the media play out narratives that can be explained very simply by regression towards the mean over time, those that are dominated by skill tell us something useful about the team posting the numbers, which will be repeated season after season, and thus are the metrics we should truly be interested in.

The theory here in this series is pretty simple. I take a big group of teams and compare how well the value they record for a given metric in one season correlates to the same metric the following season, and determining the correlation coefficient (R value) of a plot with year ‘n’ on the x axis and year ‘n+1’ on the y axis allows the breakdown of a metric into skill and luck components to be established. The sample comprises of the 204 pairs of ‘back-to-back’ team Premiership seasons that have occurred since the beginning of the ’00-01 Premiership season (17 non-relegated teams per season x 12 back-to-back seasons).

This time out I’m looking at the proportion of shots that teams take that go on target. It’s something I’ve tracked for a while with little interest, as I assume there’s a lot of noise in there (TSR wouldn’t be a reliable metric otherwise). However it appears to be picking up steam elsewhere as something worth looking at – so it’s probably a good idea to get the groundwork in before it’s roundly dismissed/lauded.

First up, the % of shots that a team takes that are on target (%TSOT for).

(I’ve seen the common notation for this metric to be SOTCON%. To me that logically suggests it’s measuring the percentage of shots on target that are converted, i.e., sh%. I’m not particularly one to go against convention but the choice of SOTCON seems really strange to me.)

This one splits up as 53% skill, and 47% luck.

Secondly, the % of shots taken against a given team that are on target (%TSOT against).

A bit more random – this time we’re at 44% skill and 56% luck.

Finally I’ve done something a bit more creative. What happens if we sum the percentage of shots a team takes that are on target with the percentage of it’s opponents shots that are on target, (%TSOT for + against).

So at 52% skill and 48% luck we’re basically back to the values for %TSOT for. In short all three of these are split pretty much down the middle into luck and skill components. Teams have some control over the proportion of their shots that go on target, as well as some control over the proportion of shots taken by their opposition that go on target.

But is it something I’d rely on, or be particularly interested in? Well some back of the envelope maths tells me that if you record the best %TSOT in the league, then that system is probably worth about four goals above average the next season, or 2-3 points. I’m not dismissing that as nothing, but in reality my interest is much more likely to be piqued by a change in a teams TSR (where predictively the gap between the best in the league and league average is worth roughly 20 points next season) than it is by a change in %TSOT.

Finally, below is a table summarising this series so far, with each metric broken down into its skill and luck components. Skill and luck are defined therein in the context of ‘the repeatability of metric ‘x’ is ‘y%’ skill driven, and ‘z%’ luck driven at the team level over the course of a Premiership season. Click on the names of any of the metrics to be taken to the post with the relevant plots posted.

Metric | % skill | % luck |

% of total shots that are on target (%TSOT) for | 53 | 47 |

%TSOT for + %TSOT against | 52 | 48 |

PDO (penalties excluded) (1) | 46 | 54 |

% of total shots that are on target (%TSOT) against | 44 | 56 |

PDO | 44 | 56 |

sh% | 43 | 57 |

sv% | 38 | 62 |

sh% on shots from inside the box (2) | 37 | 63 |

sh% (penalties excluded) (1) | 36 | 64 |

sv% (penalties excluded) (1) | 32 | 68 |

sv% on shots from inside the box (2) | 24 | 76 |

sv% on shots from outside the box (2) | 23 | 77 |

Penalties awarded differential (penalties awarded for minus penalties awarded against) (1) |
9 | 91 |

Having penalties awarded against (1) | 9 | 91 |

Penalty differential (penalty goals for minus penalty goals against) (1) |
8 | 92 |

sh% on shots from outside the box (2) | 8 | 92 |

Being awarded penalties (1) | 4 | 96 |

Penalty goals conceded (1) | 3 | 97 |

Penalty goals scored (1) | <1 | >99 |

*(1) = A special thanks to Infostrada for the data that made the original post possible*

*(2) = A special thanks to Dan Kennett for the data that made the original post possible*