How EPL Teams Cope with Injury.

One of the more heart stopping moments during a football match is when your star player is slow to rise after a particularly hefty challenge.Teams invest heavily in their on field talent,so the prospect of a prolonged injury lay off can have season long implications for fans,managers and owners.When Stoke took long throw specialist,Rory Delap on loan from Sunderland,their thoughts were geared towards how his unique talent could help The Potters promotion push.Instead they lost him for the season just two game into his Stoke career following a double leg fracture,ironically against his parent club,Sunderland.Shorn of Delap's longthrows,Stoke finished two points shy of the playoff positions in 2006/07,but with the Irish International signed up and fit for duty in 2007/08 they grabbed automatic promotion partly on the back of eight goals directly from Delap assists.

Had Delap avoided a season ending injury on a cold October night at the Brit,he may well have made the difference that propelled Stoke into the playoffs,but his absence in 2006/07 and contribution in 2007/08 does highlight how teams can suffer when forced to play without their more productive players.Delap is a unique case,but more generally teams can be shown to underperform when either a leading goalscorer or their first choice keeper is missing.Sample sizes for individual sides are small and unrepresentative,but when pooled together teams score slightly less goals when without their top striker and concede slightly more goals when they play their second choice keeper.When translated into win probabilities,either absentee reduces his team's figures by about  five percentage points.

Canaries Fans hold their breath as top scorer,Grant Holt struggles to his feet.

 These kind of facts are interesting,especially as Premiership sides often rest their star player for less prioritized cupties,but they neglect the more common situation where teams have to deal with numerous,long and short term injuries to multiple squad members.NFL teams are obliged to provide a weekly injury report that details the likelihood of each roster player appearing in that weekend's game and increasingly football and rugby clubs are releasing accurate injury information.Sites such as the physioroom are particularly good at recording how many players days each club looses to injury each year.

I've taken four years of injury reports for the Premiership clubs during the 2000's and plotted the number of player days lost through injury for one season against the numbers for the next.This is to see if there appears to be any tendency for teams to be injury prone from one year to the next or if teams can stay consistently free of problems.

 The average number of days lost to injury by EPL teams who enjoyed successive seasons in the EPL over the period was just under 1100 days.Although some teams such as Newcastle and ManC breach this number in multiple seasons and teams such as Bolton were consistently under the figure,overall there appears to be very little correlation between injury rates across years.I've no doubt that some players become more injury prone,especially if we were to concentrate on certain types of injuries such as pulls or strains,but individual teams in general appear able or lucky in avoiding stocking their rosters with such players.However,the ability or otherwise of a team's medical staff to keep players on the field and the risks associated with buying talented,but possibly injury prone players will have to wait for more detailed data.

Of more immediate interest is how a heavy injury load impacts on a team's performance.Simply regressing a team's seasonal success rate against it's injury burden is unlikely to produce any useful results.Team talent is such an overwhelming factor in determining season on season success that it is unlikely that the injury effect will be apparent over just four seasons of data.Instead I have run a multiple regression using a team's injury burden and success rate in year N and it's injury rate in year N+1 to see if these variables correlate to that team's success rate in year N+1 and if so how it is affected.

Over the sample all three variables are significant indicators of success rate in the following year.The presence of multiple variables means I can't plot correlation curves,but I'll use the regression equation to illustrate how a change in injury rate in terms of playing days lost can impact on the number of games a team can expect to win or draw over multiple seasons.

How Different Injury Burdens can Alter a Team's Success Rate in Subsequent Years.

Success Rate. Year N.	Injury Burden. Year N.	Injury Burden. Year N+1.	Predicted Success Rate. Year N+1.
0.50	Heavy	Light	0.61
0.50	Light	Heavy	0.38
0.50	Light	Light	0.52
0.50	Heavy	Heavy	0.47
0.40	Heavy	Light	0.53
0.40	Light	Heavy	0.30
0.40	Light	Light	0.43
0.40	Heavy	Heavy	0.39
0.76	Heavy	Light	0.83
0.76	Light	Heavy	0.62
0.76	Light	Light	0.74
0.76	Heavy	Heavy	0.69

I'm keen to avoid too many data heavy posts,so I've defined the injury burden as either light or heavy.The average days lost per season per club was around 1100 days and ranged into the 2000's and down to just over 200 for the more fortunate teams.Heavy and light were therefore pitched towards these two extremes.

0.5 teams are usually comfortably mid table teams,but if they achieve these numbers with a relatively injury free squad and their luck changes in the next season,they can find themselves pitched in with the relegation fodder.By comparison team's with success rates of 0.4 who manage to escape the drop can improve markedly if they stay fit in their next year.It also appears that consecutive seasons where injuries are less frequent can allow the majority of teams to prosper slightly from year to year,while heavy injury loads over seasons can be lead to a drop in results.

For those interested in more specific examples,Arsenal's success rate fell and rose in tune with their injury record from 2004 through to 2007.Liverpool had to contend with just 600 player days lost to injury in 2005/06 in recording a success rate of 0.75,but when those days nearly doubled in 2006/07 their success rate fell to 0.63.While Birmingham can possibly consider themselves unlucky to be relegated in 2005/06,having survived the previous year by 12 points,their days lost jumped from 900 to over 1500 in their relegation year.

These results are based on four seasons of data,so it's perfectly possible for teams to buck each trend because of factors that aren't accounted for here.The data is also very broad as no account has been taken about the number or position of players who comprise the injury days.But if as seems likely,injury rates are partly out of a side's control,they can contribute to a season of either toil or triumph where the final league position owes something to fortune,be it good or bad.