Thankfully, it didn’t take long for my spreadsheet’s predictions to deliver on last week’s expectations that they will become progressively more accurate with each passing gameweek. The omens are good that after struggling to navigate the choppy waters of the first 4 gameweeks, my spreadsheet’s course is being corrected, and the weather is set fair for smoother sailing from here on.
My spreadsheet belatedly registered it’s first correct score forecast (ARS 2 SHU 1). It was fitting that the breakthrough should happen in that game as I chose that particular matchup last week to explain the rationale behind favouring the method I use for score predictions, rather than simply going by the scorelines assigned the highest probability (1 – 1 in that instance). Only 1 correct forecast from the opening 38 fixtures, however, is way down on last season’s average of 1.7 per gameweek, and highlights just how unpredictable results have been so far.
For all that my spreadsheet’s predictions are not yet performing to last season’s standards, they continue to fare better than the outcomes reckoned by bookmakers to be the most probable. In GW4, the bookies were closer to the actual number of goals scored for only 2 teams. Namely, MUN & WOL, who they had to score once rather than twice, but even there, I did flag up last week that WOL to win one nil was actually the highest probability my spreadsheet had assigned to any scoreline all season, and MUN were reduced to ten men after 28 minutes.
Unsurprisingly then, my spreadsheet convincingly beat the bookies when it came to the mean absolute error (MAE) on number of goals predicted, averaging 1.25 versus their 1.45 (the lower the better). Scorelines of MUN 1 TOT 6 and AVL 7 LIV 2 were the main reason for these MAE values being so high. By way of comparison, my spreadsheet last season was often able to record a MAE of around 0.50, which equates to being only half a goal out (on average) for each team’s score prediction.
Satisfyingly, using the scorelines with the highest probability would once again have yielded inferior results (MAE = 1.50). And, acting on last week’s tongue-in-cheek suggestion of adding ‘1’ to all the predictions (to offset for the new handball rule), would have resulted in an even worse 1.55.
With a new gameweek on the horizon, however, we should be looking forwards not backwards, so here then are the score predictions for GW5:
Disappointingly, from the FPL manager’s point of view that more goals equals more points, there are 3 fewer teams deemed more likely to score twice than once this week, and in descending order of expected goals, they occupy the top 5 places in the table below:
Ordinarily, I’d have been bracing myself for howls of protest about EVE being ranked top for goals with a Merseyside derby next on the agenda for them, but I reckon I can relax now after AVL knocked 7 past the Champions!
Azpilicueta (5) and Saiss (9) both featured in the shortlist of 18 players expected to exceed the 5 FPL points average (excluding bonus) threshold last week, but unfortunately, so did Alexander-Arnold! The first named is likely the only playing defender in the GW5 shortlist below (James bench and PVA injury), but it seems reasonable to assume Chilwell would be on this list too had he more gametime with CHE under his belt.
I should point out that recent transfers and players from newly promoted teams are still not yet eligible for inclusion. In a new development, I’ve shown what penalty takers’ expected average points would decrease to if penalty kicks were removed from the equation (see below).
Encouragingly for Kane owners, this week’s table topper doesn’t owe his score to any. Only Kane has appeared in all five of these tables so far, and it was my spreadsheet’s long range forecast that he would be that made him an ever-present in my team so far. Son, Salah, and Antonio are the only players to have featured in all but one.
Note that Salah is ranked higher than all of the Toffees’ attacking triumverate, despite EVE being predicted to outscore LIV, and the reason why gives a good insight into how my players points predictions are calculated. Salah’s share of expected goal involvement in LIV’s last 8 away games was 38% of expected goals, and 17% of expected assists. This compares favourably to Calvert-Lewin (37% / 2%) and Richarlison (27% / 22%) in EVE’s last 8 home games, especially when the extra point per goal for Salah over DCL is factored in.
Sadly, my captain picks this season have followed on from last season in terms of being unmitigated disasters! So, I will be looking to Kane, Antonio or KDB to bring the current sequence of FOUR blanks to an end.
In recognition of the fact that I have perhaps become overreliant on my spreadsheets as the sole source for my captaincy decisions, I have returned to the methods that saw me win my main money mini-league three years out of four.
Looking at My Stats Tables in the Fantasy Football Scout Members Area, it bodes well for would-be Kane captainers to see TOT leading the way in terms of Minutes Per Big Chance (see below).
Sods Law would decree, however, that when I looked at my Team Defence table to see who are worst for Minutes Per Big Chance Conceded (see below), the hope that WHU are among them was completely confounded. In an echo of the ‘irresistible force paradox‘ it turns out that the unstoppable force that is Kane will be meeting the immovable object that the WHU defence have improbably become!
A case can still be made for Kane though if we consider that of the 4 teams WHU have faced so far, NEW, ARS, and WOL have hardly been setting the stats for attacking football on fire lately! In fact, those three teams are in the bottom half of the table for other metrics in My Stats Tables: Shots – Inside Box; and, Shots On Target.
Pleasingly, the 2 teams highlighted last week as having unusually high probabilities of a clean sheet (WOL 67% and CHE 62%) lived up to the hype. The latter are the only team this week reckoned more likely than not to keep a clean sheet in GW5. Whilst the 4 teams highlighted in green (MCI, WBA, MUN and SHU) are deemed less likely to concede one goal than none, they are still more likely than not to concede, because of the added possibility of conceding two, three, four, etc.
I made reference last week to my spreadsheet’s clean sheet probability calculations historically being its strongest suit, so it is pleasing to report that they were on average 4% more accurate in GW4 than the bookies probabilities posted by @FPL_Salah (see below).
And this wasn’t because the bookmakers had a particularly bad week by the way. In fact, their mean absolute error of 34.25 was better than the MAE of 37 they averaged in the 11 weeks I monitored between GW7 and GW17 last season. As promised last week, I did take a retrospective look back at the first 2 gameweeks of the current season, and the bookies came out on top in neither, which means they have now fared better than my spreadsheets in ONLY 3 of the last 16 gameweeks compared.
Another thing I tested last season was the accuracy of my spreadsheet’s longer-term forecasts, and the results were very encouraging indeed. I compared the projections for the following 5 gameweeks with current gameweek only predictions provided by “the world’s most powerful predictive fantasy football algorithm”. And, despite that model having the informational advantage of being up-to-date prior to each of the following 5 gameweeks, my spreadsheet outperformed it in each category I ran correlation tests on (number of goals teams scored, correct score forecasts, and mean absolute error). In other words, even from 5 gameweeks earlier, my spreadsheet’s projections proved more accurate than up to the minute predictions provided elsewhere.
The possibility of a double up on WOL defence in GW6 was touted last week, and they continue to look as though they have good prospects for 3 clean sheets out of 4 thereafter (see below).
May the GW5 flop be with you!
Coley a.k.a. FPL P0ker PlAyerFollow @barCOLEYna