New Year's season ticker Resolution

(Spoken in the manic voice of Dr Heinz Doofenschmirtz):  

 "Behold! My newly improved FPL Incorporated SeasonTickerSpreadSheet-inator!"

Key: Dark blue is best and dark red the worst. The top tables relate to expected goals scored, and the bottom ones to expected goals conceded and clean sheets.

Towards the end of last season I made the decision to try to develop my own season ticker, as I liked the concept of identifying favourable and unfavourable fixture runs.  There were many tickers out there already, but I didn't like not knowing the methodology they used or how regularly they were updated.  Clearly, I have trust issues!  I also didn't like the thought of being at the mercy of somebody else's subjective opinions, as most tickers seem to rely on somewhat arbitrary weightings.  Okay, so I'm a control freak too!

For 2015-16, I've been relying solely on my own season ticker, and the results have been promising.  I enter the New Year doing well in my mini-leagues with 1,137 points and an overall ranking of 12,301.  This is despite some missteps along the way caused by various glitches, gremlins in the works, and several instances of misentered data.

One of those missteps saw me transfer in Lens in GW5 and I very nearly captained him in GW6!  I really ought to have cottoned onto something being amiss sooner.  It turned out that data in one table from Leicester down to Swansea was one line out, so Sunderland had been inadvertently credited with Stoke's results.  Doh!

As the season has wore on, I've smoothed out many wrinkles, and found more efficient methods of keeping my season ticker up to date with accurate data.  Now halfway through the present BPL season, I found myself having yet another eureka moment this past week whilst updating my season ticker.  Sparing you all the details, I realised there was a flaw in the logic of my final formula in a series of four calculations* my spreadsheet makes to arrive at an expected scoreline for every match in every gameweek.  I'm so confident that this realisation will boost the accuracy of my algorithms that I'm gearing up to start sharing the results with the FPL Community.

Certainly, if I'd had this insight earlier, I'd not have held onto Eriksen like I did this week even when I knew his price was about to drop.  Nor would I have brought van Dijk in for Wollscheid last week.  I'm happy to go without STO DEF cover for the foreseeable future, but SWA were clearly a much better option for a replacement than SOT (see below).

What I want my spreadsheet to be is a score predicting season ticker based on recent form only.  For the time being, I'm using the last 3 home games and the last 3 away games to guage teams' home and away form.  My expectation is that this results in my season ticker being much more responsive to changes in teams' form, which hopefully allows me to be ahead of the curve in my transfer dealings. 

I'm currently working on the most helpful way to present this information, but as a taster, this is how the teams with the best attacking potential over the next 6 games might be shown:

Thus, I might comment that those not selling Vardy will be pleased by this table.  As indeed will Ighalo owners.  And, looking at the projected season ticker I always do for the following week, I might reassure Arnautovic bandwagoners that Stoke are set to rise in this table in the coming weeks.  I might even warn WBA investors that these calculations do NOT factor in such things as Rondon's unavailability for the next match.
 
Similarly, the teams with the best Clean Sheet potential might be shown like this:

Again looking ahead, I could warn potential SUN DEF investors that the Black Cats are set to disappear from this list next GW, along with WAT.

Disclaimer:  The very elusive nature of form in football and the sensitivity of my algorithms does mean that fluctuations in my season ticker tables are inevitable.  Also, I should stress that my tables are to be used alongside your own judgement and knowledge, NOT instead of them!  Getting the most from them will depend greatly on synthesising them with your own well-informed instincts.

There are numerous options for which information to share from my spreadsheets, so I will deliberate about what works best, and is visually the most simple, over the next few days, and hope to launch something soon.

Watch this space.

In the meantime, please feel free to comment or ask any questions.

And best wishes for a Happy New Year!

Coley

Appendix

If I tell you that the top line of data, shown in the first screenshot at the top of the page, is actually line 221 of my spreadsheet, you'll understand that there's a lot going on before we get to the business end of my season ticker.  What is seen there is only the fourth part of the process.

*The four calculations consist of the following:

1. Adding up the goals scored and conceded in each team's past 3 home games and likewise for each team's past 3 away games.  The number of goals scored and conceded by each team are amended according to criteria** that take into account a wide range of contributory factors, such as whether they came from deflections, penalties, or unforced errors.  For example, teams are sometimes awarded penalties in situations they were unlikely to score from, so these might be counted as only a third of a goal, or 0.33 goals.
2. Ascribing teams different coefficients for the goals they score and concede both home and away.  These are weighted according to current form, as reflected in the last 3 matches played at home or away.  This tries to reflect the simple truth that some teams are easier to score against than others.  Currently, you could make the case that it's at least twice as difficult to score against Man Utd than it is Aston Villa.
3. Reassessing the total worth of the goals scored and conceded in each team's past 3 home games and likewise for each team's past 3 away games, in light of the weightings associated with the respective opponents faced.  By this method, 6 goals scored in a team's last 3 away games, say 3 against Villa, 2 against Everton and 1 against Newcastle, might be deemed to have the same value as just 3 goals scored by a different team in their last 3 away games, say 1 in each against Chelsea, Man City and Swansea.
4. Comparing the number of goals each home team is expected to score on average with the number each away team is expected to concede on average to calculate an expected scoreline.  

**The criteria considered for amending goals:- Deflected cross/shot on/off target

Gifted chance to score

Penalty when unlikely to score

Soft penalty

Deflected shot on target

Injury time on the break vs team chasing equaliser

Intended cross Lucky rebound

Penalty when 50/50 to score

Goalkeeper/defender should have done better

Penalty when more likely than not to score

Goal vs 9 men

Penalty when very likely to score

Goal vs 10 men

Goal denied by foul play

Goal incorrectly disallowed*