Friday 9 August 2013

A Decade of Steven Gerrard As A Liverpool Mainstay/Liability.

Much of the current internet football discussion revolves around the transfer window and the destination of big name players to pastures new. Understandably, speculation about the likely impact of a newly acquired player on the fortunes of his new  employers is rife. However, it is also entertaining to ponder about the size of the hole the departing player will leave at his former club and how reliant they were on his talents.

The most common approach uses the seemingly simple, yet powerful tool of examining the record of a side when the player was in the lineup to those matches where he was absent. Various twists on the original format are usually used and team match performance is judged either through a combination of goals scored and allowed, points accrued or a weighting of wins, losses and defeats.

A player who helps his team to a more impressive win, loss, draw record is the obvious candidate to be the causative agent for that improved record. The first player identified as a force for providing better results when he was on the pitch compared to those recorded when he was absent was Patrick Vieira in his time at Arsenal. Such was the combative nature of his play, especially when faced with natural championship rivals, such as Manchester United and Roy Keane in particular, that the connection became widely accepted and has often been used for other, high profile players such as Xavi at Barca and latterly Suarez at Liverpool.

A method that uses the relatively rare currency of goals or wins and draws to evaluate a side's performance when one certain individual is either absent or present is fraught with problems. Most obviously, quality of opposition, but also the quality of the remaining 10 or 11 players is largely ignored. Standout players and their colleagues may be rested en masse against inferior opponents or arbitrarily suspended or injured against the best.

However, by far the biggest problem in relying on this kind of with/without analysis revolves around sample size. Small game samples, especially when success or failure is decided by rare events, such as goals often lead to headline grabbing figures, usually expressed in percentages that appear to compare like with like when they do no such thing.

To use the example of Steven Gerrard, a formidable one club man with Liverpool. If we look at the season on season record of his team Liverpool when Gerrard played a part in the match and when he didn't, we find that in ten of those 15 seasons the "Gerrardless" Reds had a better season long success rate than when he played. In just five seasons was Gerrard, (apparently) a force for improved results.

So to decide if Gerrard is an undroppable icon who more often hurts Liverpool's chances, it may pay to look at the actual numbers rather than the percenatge figures.

In 2007-08, Liverpool's record when Gerrard was on the pitch during a game was 29 wins, 16 draws and 7 losses for a success rate of 0.712 compared to 4,2,1 (0.714) when he wasn't. Liverpool were marginally better without Gerrard, but we are comparing the outcome of 53 games to that from just 7.

To illustrate the potential volatility, one more or less loss added to a Liverpool with Gerrard sees their success rate fall to 70% or rise to 72.5%. The same alteration applied to Liverpool deprived of Gerrard sees the high rise to 83% and the lows fall to 62%. There is little change in the former percentage figures, but much larger swings are possible in the latter, when Stevie G is absent.

High profile players are invariably the target for such type of analysis, so they will invariably play often. So the stick we are using to beat them with or the carrot as a reward will almost always be prone to wild fluctuations as illustrated by the effect of a single altered result in the smaller sample size above. In short, the so called "player absent" yardstick should come complete with massive levels of uncertainty because they are based on very small sample sizes, yet, much like many percentage based player figures used across the web, they never do.

Even if we extend the sample size by taking in multiple years, we can still slice and dice the data to suit any narrative by manipulating the figures thrown out by the smaller sized sample.

Steven Gerrard Is An Essential Player For Liverpool.

Time Period. Success Rate with Gerrard. Success Rate without Gerrard. Were Liverpool "Better" With Steven Gerrard ?
Debut to 2012/13 0.643 0.626 Yes
Debut to 2011/12 0.646 0.627 Yes
Debut to 2010/11 0.650 0.628 Yes
Debut to 2009/10 0.657 0.628 Yes
Debut to 2008/09 0.665 0.634 Yes
Debut to 2007/08 0.653 0.628 Yes
Debut to 2006/07 0.644 0.625 Yes
Debut to 2005/06 0.645 0.624 Yes
Debut to 2004/05 0.625 0.621 Yes
Debut to 2003/04 0.634 0.619 Yes

Steven Gerrard Is A Liability For Liverpool.

Six Season Period. Success Rate with Gerrard. Success Rate without Gerrard. Were Liverpool "Better" With Steven Gerrard ?
2013-2007 0.476 0.626 No
2012-2006 0.500 0.626 No
2011-2005 0.535 0.627 No
2010-2004 0.561 0.628 No
2009-2003 0.582 0.634 No
2008-2002 0.591 0.628 No
2007-2001 0.601 0.625 No
2006-2000 0.627 0.624 Yes
2005-1999 0.625 0.621 Yes

For anyone considering using the currently flawed methodology to bolster a subjective opinion piece, feel free to use either of the two tables above. I've calculated Liverpool's success rate with or without Gerrard over differing, multiple timescales since his debut back in the 1990's. The data has been diced and expanded to cover multiple seasons (to enhance it's credibility). One table can be used to illustrate his importance to Liverpool and the second to show how much better they are without him. 

Seemingly powerful data backing diametrically opposed viewpoints for one of the most consistent, high profile and talented players of his generation. What chance for accurate or even meaningful assessment of lesser lights only partway into their careers when they are put under a similar spotlight using similar methods?

Evaluating player contribution is an obvious interest for many parties, but some current methods have the potential to greatly, and surreptitiously deceive.

Just to be clear, this is about abusing stats, not about Steven Gerrard, who is of course a magnificent player.


  1. Great post. Using top-down analysis is as prone to misinterpretation as bottom-up stats are if done carelessly. You clearly have a good point that samples sizes are too low to ignore the quality of team mates and opponents. Any stat ignoring these will have little discrimatory power. If you are interested in these kind of stats that are corrected for the quality of the 23 other players, I publish this kind of work on my blog

  2. It seems you are using weight of 0.5 for draws , 1 for win and 0 for loss. This is natural however leagues have 3 pts for win , 1 for draw and 0 for loss, when you adjust the data with that weight i think the results would be slightly different. Also it would make more sense to separate league games and cup games.

  3. Each to their own. I think a draw equating to half a win makes much more intuitive sense.


  4. thanks for the link to your site, Jorg. I look forward to reading it over the weekend.