Home advantage, along with Sunderland, rebounded from a disappointingly lacklustre first half of the Premier League season to finish the 2015/16 campaign close to their traditional benchmark figure.
After 170 matches, home teams were winning only a few more times than away teams.
Long term trends have been downward, but it was a bold claim made by some, to declare home field advantage a thing of the past after such a relatively small number of matches.
Unequal match-ups and significant, but rare events, such as red cards may have contributed to producing a subset of games that tended towards a more equitable share of home and away wins, but the noisy nature of a low scoring sport is always likely to push outcomes temporarily in one direction or another.
We now have an entire season’s worth of shot data, through which we can examine the process of chance creation, rather than the single outcome iteration that briefly led to the exaggerated obituary for HFA after 170 matches.
59% of home teams were favoured to win in the first 170 matches based on an expected goals rating of each team, but this increased to over 61% in the remaining 210 games.
So scheduling played a small part in pressing home wins downwards up until Christmas.
But random variation is always going to be a prime contender as the “cause” of bogus “sea changes” in league-wide traits.
You may measure home field advantage in a variety of ways (and chose the one which best illustrates your particular agenda). For example, home win%, goal difference between home and away teams, points per game, success rate and so on.
Success rate, (wins + half draws)/games played, has the handy attribute of totalling one for home and away teams.
A success rate of less than 0.5 for home teams immediately tells you that away teams have been more successful over that period of games.
The plot above shows the range of success rates gained by home teams in the first 170 matches of 2015/16, based on their chance creation during each match over 10,000 simulations.
The actual success rate in late December 2015/16 fell in the bin 0.0495-0.51.
Based on expected goals, the relative parity experienced by home teams over just 170 games wasn’t that unexpected. Home sides have also experienced similar runs of results in seasons where home teams were still deemed dominant.
However, with more usual levels of “luck” home teams could have seen their first third of the season reap success rates of around 0.53 or 0.54.
There’s even around a one in 10 chance they could have hit 0.555 or above and sent “home field strikes back” narratives into overdrive.
We may also simulate the entire season from the perspective of the success rate of home teams, mindful of the 210 additional games that were likely to feature proportionally more numerous dominant home team match-ups.
Home teams had an actual success rate of just over 0.55 over the entire season. So the actual outcome lies at the top end of the most likely bin in this plot of shot based simulations.
There’s also around a 10% chance that the probabilistic shot profile of all 380 games could have produced a home success rate at least as good as the previous three “unexceptional” home seasons.
But any pretence that luck alone could have sent a reasonably normal, if declining season for home field advantage down to levels of near parity all but disappears in the increased sample size and more equitable schedule.
….if home success rate was around 0.5 now, we may have a case to answer re zero HFA, but the levels of parity in December was always likely to be sample size related.
Small sample narrative makes “home and away specialists” of individual teams before they subsequently melt away.
And the gradual decline of home field advantage may make “HFA is dead” posts even more frequent and probably erroneous in the future.