Posts Tagged ‘from play’

Early Conversion Rates are poor – why?

November 10, 2016

Early Conversion Rates

Whilst uploading the 2016 data into the database I was noodling around in the numbers and produced a simple chart for production on Twitter.

graph-1-overview

Something was quite obviously happening in the first 10 minutes that saw the cumulative Conversion Rates much lower than the average. There were two initial thoughts

1. a number of “lower level” teams were dragging the average down early in games (either through just poor shooting or an inability to get “quality” shots off against better teams early on when the scoreboard was close)
2. shooting types, and where shots were being taken from, were so different in the frantic opening periods of games that the early Conversion Rates were being skewed

Upon doing some more superficial digging it appears that neither were the case

1. Conversion Rates by teams

graph-2-by-team

The phenomenon (of Conversion Rates being lower early on) was observed in three of the four semi-finalists (NOTE1) whilst all other teams followed the overall trend to a tee. The only outliers – unsurprisingly – were Dublin.

2. Expected Points over time

graph-3-expt-pts

The above is a replica of the Conversion Rate chart but replacing Conversion Rates with Expected Points (Expt Pts). Although the shape of the chart is different than the original the occurrence of poor early returns is still evident. And by using Expt Pts we remove the shooting types as an issue as Expt Pts bakes in the difficulty of a shot (NOTE2). All shots are being converted at a lower rate than expected until around the 30th minute but teams are noticeably struggling in the first 15 minutes.

Conversion Rates by shot type

So the phenomenon is real but cannot be attributed to a specific team type nor to shot selection/execution. It is across the board except for Dublin. Three shots types – free kicks, point & goal attempts from play – make up ~97% of all shots. Is there anything we can determine from investigating these shot types independently to explain this poor shooting in those early exchanges? And is there anything therein that explains how Dublin are managing to avoid this poor shooting early on?

Free kicks

graph-4-by-free

This is probably the most surprising, and hardest to attribute, of all the results. When the very first chart was produced on Twitter I mischievously suggested that whatever all the back-up teams were doing to get teams warmed up they needed to change it. There were some good responses re the intensity of teams, especially in the pressure applied to shots, being higher early on. Or that teams were defensively more conservative early on leaving less space for clear shots. All plausible and probably have a grain of truth. However none applicable to free kicks – and the phenomenon of poor conversion rates early on is noticeable here too.

Now by slicing the volumes into the first 10 minutes of one season’s games we are running in to sample size issues. Specifically for this segment the volume is 47 so this comes with a rather large health warning.

Assuming games are now 80 minutes the first 10 minutes make up 12.5% of the game; the 47 frees in the first 10 minutes make up 13% of all frees. On top of that the two main free takers – D Rock & C O’Connor – make up 21% of all frees in the first 10 minutes whereas they make up 25% of all frees in the database for 2016. So the first 10 minutes, low sample size and all, are representative of the whole year. So what happens in those opening 10 minutes?

Shots Scores Expt Pts Conversion % v Expt Pts
All frees 47 29 32.8 62% -3.8
Rock & O’Connor 10 9 7.8 90% +1.2
Others 37 20 25.0 54% -5.0

What the above table shows is that Rock & O’Connor were on point from the get go. Overall for the year they combined for an 86% Conversion Rate and in the first 10 minutes they were 90%.

If the two main protagonists were on point the rest of the free takers must be dragging the averages down from 71% overall to 62% in the first 10 minutes. And as the table shows this is the case. Indeed they were very poor returning a paltry 54% (the 80 minute average for all free takers outside Rock & O’Connor was 66%).

And this somewhat negates the argument for lower Conversion Rates early on being affected by what the opposition’s defence is doing. The opposition can’t really affect free taking. Outside of Rock & O’Connor it looks like free takers were just not ready early on (NOTE3).

Points from play

graph-5-from-play

The Conversion Rate for 2016 was 44.2% and for the five years from 2012 was 45.8%. For the first 10 minutes of 2016 games the conversion rate was 36% and only rose to a cumulative 38% by 20 minutes. Again the Expt Pts was lower in the first 10 minutes (-15.70) as against the remainder of the game (+5.84).

I do track whether a shot was taken under pressure however have only used it anecdotally to date as it is a simple “Y/N” flag and is probably not nuanced enough for any concrete use. Having said that however there is only one person applying the flag so we would expect a certain degree of consistency of application across the ~1,000 shots tracked here.

In the first 10 minutes I charted 53.6% of all point attempts occurring whilst under pressure. The remainder of the time it was 54.2%. Near enough as makes no difference.

So the poor shooting for points from play is real, is not linked to poorer shot types (as evidenced by the Expt Pts return) and from the empirical data we have is not linked to greater pressure applied earlier on in the game. I am completely open to the intensity of the pressure being different early on (NOTE4) but if this was the case you would expect some uptick early on in the percentage of shots marked as taken under some/any pressure in this timeframe. There is none.

There may be other non measurable factors such as nerves (these are amateurs after all) but as of now I can’t come up with anything other than the aforementioned “mischievous” reason that players are just not at peak performance early on. Maybe this is to be expected?

So what of Dublin? We saw that their early conversion Rates outperformed everyone else. This is in part due to the fact that Dean Rock went 5 from 5 on his frees but how was their shooting from play?

Shots Scores Expt Pts Conversion % v Expt Pts
Dublin 23 9 10.2 39% -1.2
Mayo 28 8 12.0 29% -4.0
Tyrone 19 8 8.7 42% -0.7
Donegal 17 4 7.4 24% -3.4
Tipperary 13 5 6.8 38% -1.8
All first 10 179 65 80.7 36% -15.7

Again volumes are low (NOTE5) but Dublin were no great shakes early on. Yes they were above the average for the first 10 minutes but they still underperformed when compared to the whole game average and their Expt Pts – like all the teams above – was below 0.00.

Perhaps the most striking return here is Mayo. From the 10th minute onwards they were exactly in line with Dublin (Mayo 49% on 126 shots with an Expt Pts of +5.59; Dublin 49% on 132 shots with an Expt Pts of +5.54) but for those first 10 minutes they were much poorer.

Another theory for the poor start was not where teams were shooting from but who was shooting – less pressure on returns early on so midfielders/defenders were more inclined to “have a pop”. So I had a look at Mayo’s shot distribution. In the first 10 minutes 64% of their shots came from what I would state are obvious offensive players (A Moran, A O’Shea, J Doherty, A Dillon and the two O’Connor’s). From the 10th minute onwards, and adding E Regan, C O’Shea and A Freeman to this mix who didn’t have a shot in the first 10, these forwards accounted for 60% of point attempts (NOTE6).

It is difficult to attribute offensive/defensive tags to all players in today’s game but if there was a decisive split in who was shooting for teams you would expect it to show up in the team with perhaps the worst split. But it doesn’t.

Goal Attempts

graph-6-goal-attempts

To be honest I am just including the above for consistency and to help explain Dublin’s apparent ability to start faster than others. Whilst I have consistently cautioned against low sample sizes it is an overarching feature of this shot type and can explain a lot of the variance within the five minute groupings above. In total there were 137 goal attempts with just 15 in the first 10 minutes and 36 within the first 20.

Having said all that …. the Conversion Rate for goal attempts was 53% in 2016 and only crawled up to 40% after 15 minutes. With the evidence we have teams again were not converting on goal attempts early on in games.

Dublin? They had six goal attempts in the first 10 minutes scoring 3-00. 50%. And there is their apparent early start in a nutshell. They were 50% on goal attempts, 100% on deadballs (as well as Rock’s aforementioned frees he was 2 from 2 on 45s as well) and slightly below average at 39% on point attempts – giving them the aggregate of ~52% early doors.

Overview

This is based on one year’s data (NOTE7) but poor early conversion rates were definitley a “thing” that year

There is no evidence that shot selection (through Expt Pts), opposition pressure (through the simple “Y/N” flag) nor type of shooter (using Mayo as an example) is any different in the first 10 minutes to the rest of the game

It is also evident in early free taking, except for the very best in Rock & O’Connor who were on point from the very start, which somewhat nullifies the theory that it is something the opposition is doing to affect the shooting.

There are undoubtedly other factors at play. Some can be measured; first shot in the game, effect of new surroundings, debutants vs more experienced players, intensity of pressure. Some we may never be able to measure – nerves, mentality of players early on versus later in the game, etc.

But as of now, and taking all of the above into account, I cannot escape the initial gut reaction that players are just not ready – for whatever reason – early on

NOTE1 – we need to be careful with any segmentation. There are only 1,640 shots in total being reviewed here with 249 in the first 10 minutes. Segment that further by team and you get some ridiculous numbers; Kerry just have the 7 shots across two 2016 games; similarly Tipperary only have 16 shots in the same timeframe. You can’t make any judgements on those numbers. In truth I would not normally use a chart with such low volumes but I include it here as it was the chart that sparked me into looking deeper into the issue.

NOTE2 – for more on why this is so please see here

NOTE3 – I had a further look at the non Rock & O’Connor frees to see if any one player was having an effect. There was none really. 34 of the 37 were a player’s first attempt in the game which makes sense as it is uncommon for a team to have two shots at goal from a free in the opening 10 minutes.

This leads to a further corroboration that could be investigated – across the year’s how does a player’s very first free kick equate to the rest of their results?

NOTE4 – I started to grade pressure on a sliding 0 – 3 scale for the two All Ireland finals. It feels a lot more robust as having to apply a grade makes you stop and think. It will be very instructive from here on in but as of now I’m not inclined to go back over the entire season to retrospectively apply the grade(s)!

NOTE5 – This table lists all the teams with >10 shots from play in the first ten minutes. Again we are running into sample size issues.

NOTE6 – the non offensive players with a shot in the first 10 minutes were B Moran, D Vaughan, K McLoughlin, L Keegan, P Durcan & T Parsons. Other defensive players with shots post the 10th minute were C Boyle, K Higgins, S O’Shea, S Coen, B Harrison & K Keane

Note that whilst some of these could be moved into the “offensive” pot their individual shot volumes are such that it wouldn’t make a material difference to the overall point.

NOTE7 – why one year? Because for some unknown reason I didn’t track the time (outside of 1st half/2nd half) for previous years. Hell of an oversight in retrospect! The only reason I started in 2016 was I was so bored of looking at kickouts so decided to look at the rest of the game. I have one or two other pieces I newly gathered in 2016 so hoping to get another long form piece out on those

2016 Shooting review

November 2, 2016

Time for the annual review of how the season’s shooting went.

All shots Frees Point attempts Goal Attempts
2012 51.7% 70.6% 47.3% 39.8%
2013 50.5% 70.6% 44.7% 41.9%
2014 51.3% 76.8% 44.8% 47.9%
2015 53.8% 70.9% 48.5% 51.2%
2016 51.5% 71.1% 44.2% 52.9%

In truth 2016 was an average year. The three shot types listed above account for 96.4% of all shots and whilst there is some movement in each category there is nothing that really warrants further investigation.

Frees

This has been *the* most stable metric since the inception of the blog and 2016 was no different. Slight uptick but nothing exceptional. We looked at the 2014 increase here and, at the time, attributed it to better accuracy for closer in frees.

Point attempts

2015 saw an increase in accuracy for point attempts however this was a blip rather than the beginning of any trend as 2016 returns slipped back to 2013 & 2014 levels.

Goal attempts

The step up in accuracy observed in 2014 & 2015 was maintained in 2016. Teams have definitely become better at getting a return from their goal chances but not necessarily at their finishing. The above table includes any goal shot that returned a goal or a point. If we strip out the points then the goal conversion rate is 35%, 32%, 36%, 41% & 40% respectively. The step up in 2014 & 2015 is evidenced again however was maintained, rather than built upon, in 2016.

2015 Season Review – Part II

November 10, 2015

In Part I it was observed how the volume of shots dropped from the 2014 high of 30.9 a game back to 27.8 in 2015 (in line with previous averages from 2012 & 2013). With the quantity down was the quality affected? Yes – but in a positive manner.

The overall accuracy on all shots increased. Between 2012 and 2014 (3 years, 74 games and 4,246 shots) 51.2% of shots were converted with little year-on-year variance; 51.7% in 2012, 50.5% in 2013 and 51.3% in 2014.

2015 saw a 5.2% increase on this three year average to 53.8% (26 games & 1,446 shots). Like the deadball increase observed in 2014 (more on that below) I would be loath to read too much into one year’s worth of data however it is a noteworthy movement given (a) the size of the jump and (b) the fact that there was a jump at all after the steadiness of the previous three years.

So how was this increase achieved? Shots are broken down into three main constituent parts; deadballs account for 26% of all shots, goal attempts account for 9% with the remaining 65% coming from attempts for a point from play. The 2015 returns for all three are reviewed below.
 
Deadballs
 

Shots Scores Success Rate
2012 347 232 66.9%
2013 389 259 66.6%
2014 328 239 72.9%
2015 347 240 69.2%

One of the main findings from the 2014 review – expanded upon here – was the fact that deadball accuracy jumped after three years of remarkable consistency (although not shown in the above table the 2010 season had a Success Rate of 66.3%).

Whilst that increase was not sustained in 2015 the overall returns were still very good in a historical context. To be of an average intercounty standard your team needs to convert 70% of deadballs assuming a normal spread of distances & type.

So how is this 70% achieved?

Shots Scores Success Rate
Frees 304 215 70.7%
45s 34 19 55.9%
Penalties 7 6 85.7%
Sidelines 2 0 0%

 

Only 47 penalty & sideline attempts have been charted since 2012; much too low a number to make any concrete conclusions on. [As an aside 83% of the penalties were converted and 28% of sideline attempts]

The number of 45s converted continues on its upward curve (40% Success Rate in 2012, 50% in 2013, 52% in 2014 and now 56%) to give an overall average of 49.4% over the four years. This increase has little effect on the overall deadball Success Rates however as 45s only account for ~12% of all deadballs.

So that leaves free kicks. As ever with deadballs it is free kicks where the real movement happens. They account for ~85% of all deadball attempts (and 21% of all shots in total).

In 2014 the Success Rate for free kicks jumped to 76% from 70% & 71% the two previous years. There was no real trend as to why this was except to say that accuracy improved across the park. This year? That accuracy dropped back to 70% – bang in line with previous norms. Hello regression to the mean.
 
From play – for a point
 
Two thirds of all shots are attempts at a point for play. Though the Success Rates in the other shot types are important a team’s bread and butter can be found here.

Shots Scores Success Rate per game
2012 887 419 47.2% 17.74
2013 888 397 44.7% 17.76
2014 1012 453 44.8% 21.08
2015 963 468 48.6% 18.52

 

2015 saw a drop of ~2.5 shots per game which, though dramatic, is still ~0.75 shots higher than observed in 2012 & 2013. This lower volume did produce a higher quality however with a Success Rate of 48.6%. That is a ~8% increase on the previous two years.

Although there was a similar return in 2012 I had a look at where the shots originated to see if there was any discernible change in pattern (more shots from easier sectors). There wasn’t – if anything there were less shots from the easiest sector – Sector8 – just in front of goal.

Sector Outside 45 4 5 6 7 8 9
’12 – ’14 2% 23% 24% 17% 12& 13% 9%
2015 1% 24% 24% 18% 13% 11% 9%

 
Seeing as the ease of shot hasn’t changed the conclusion is that the quality haS increased. Ignoring shots taken from outside the 45 – which only account for ~2% of all shots – the Success Rate increased for all sectors bar Sector5 which remained stable.

Sector Outside 45 4 5 6 7 8 9
’12 – ’14 37% 37% 50% 35% 42& 71% 46%
2015 27% 43% 49% 41% 47% 75% 52%

 
 
From play – for a goal
 
The first thing to note is that the prevalence of goal attempts has not changed in any real sense. In 2015 goal attempts made up 9.4% of all shots; it was 9.6% the two previous years.

What has changed, and in truth has been a noticeable trend since 2012, is the accuracy of these goal attempts. In 2012 a score (a goal or a point) was returned from 39% of goal attempts. This has risen year on year to 52% in 2015. When we only include goals as a score (probably a more accurate measure of goal attempts!) there is still a noticeable upward trend.

Shots Scores Success Rate per game
2012 117 40 34.2% 2.34
2013 136 44 32.4% 2.72
2014 142 52 36.6% 2.96
2015 136 56 41.2% 2.62

 

Teams are getting more scores, and more goals, from their goal attempts.

So there you have it. An overall increase fuelled by better accuracy from play – both in point & goal attempts – though the increase was somewhat dampened by a drop in free kick accuracy.
 
Dublin
 
Do Dublin, given the volumes they achieved during the year, have an overbearing affect?

The answer is probably in the question – of course they do. Taking goals only Dublin scored 16 on 32 attempts in 2015 meaning that the remainder of teams converted at a 38.5% clip. In 2014 Dublin only converted 28% (9 from 32) with the remainder returning 39%. Whilst not wholly reliant on Dublin’s returns (Mayo put 6 past Sligo whilst Kerry put 7 past Kildare) the fact that they have been responsible for 24% of all goal attempts means that the year on year increase has followed their outcomes.

Similarly when going for a point Dublin converted 57.3% on 17% of all attempts recorded with all other teams converting 46.8%. It is not just Dublin here however as Mayo converted 56.7%.

We use averages as a starting point as, with a large enough sample size, these “outliers” will be subsumed by the whole. However when viewing the Grade A teams (Dublin, Mayo, Kerry) a premium needs to be added to the average when reviewing their play whilst Grade B teams – those trying to break through (Cork, Tyrone, Galway) – need to aim far higher than the average.

Colm McFadden – a review

May 15, 2015

The last time we saw Donegal was in the league semi-final against Cork which was fairly unremarkable apart from both teams’ ability to get shots off at a high rate – in the mid 80% against an average of 77%. It is only one metric but a fairly large indicator of a game lacking intensity.

One thing that did peak my interest however was the performance of Colm McFadden. In a high scoring open game he only managed 0-02 from play and did not attempt any frees. I had a vague recollection of noting a declining performance throughout 2014 so decided to have a look. Thanks to the BBC’s coverage of the Ulster Championship we have all bar one of Donegal’s game over the past three years and below are McFadden’s returns over that span.

Attempts Scores Success Rate Weighting
Deadball 53 40 75% +3.499
Play 52 23 44% -0.196
Total 105 63 60% +3.303

Not bad. His shooting from play is bang on average but given the volume of shots he takes that’s ok. Average does not equal bad! His deadball accuracy however is very good – perhaps only below Cluxton and O’Connor in terms of per kick weighting. In truth there’s nothing to see here but the more you do this the more you understand that averages can hide a lot.

Attempts Scores Success Rate Weighting
Deadball
2012 27 22 81% +4.566
2013 13 8 62% -0.770
2014 13 10 77% -0.297
From play
2012 24 13 54% +2.226
2013 11 6 55% +1.987
2014 17 4 24% -4.409

McFadden was stupendous, both from deadballs & from play, in Donegal’s march towards Sam in 2012. But he was so good on that run that when we take the average from the last three years it is masking a very big drop off in both categories.

McFadden’s deadball accuracy has dropped from the unsustainable highs of 2012 to just below average over the last two years. Although his combined Success Rate for 2013 & 2014 is high at 77% the negative weighting shows you that he is taking easy, or at least easier, frees – he should actually be converting closer to 80% (similarly the high weighting in 2012 shows you that he was converting more difficult frees more often).

The real drop off has occurred with his shooting from play however.

Attempts Scores Success Rate Weighting
Point attempts
2012 21 11 52% +1.240
2013 8 4 50% +1.001
2014 14 3 21% -4.395
Goal attempts
2012 3 2 67% +0.986
2013 3 2 67% +0.986
2014 3 1 33% -0.014

McFadden was never prolific from play but he was always above average in his returns. That was until last year. During the six 2014 games McFadden had 14 attempts at a point – and only converted three. And all three were simple attempts from around the penalty spot. He did not convert one point attempt from outside the 20m line in six games.

McFadden’s 2014 point attempts
McFadden 2014

It was not as if he was trying harder shots in 2014 – the opposite actually. Of his 14 point attempts in 2014 ten, or 71%, were in the optimal shooting zones of 5 & 8 (see the shot chart above). In 2012 & 2013, when he was converting at ~50%, only 35% of his shots were coming from these central areas. There was nothing in terms of pressure to explain the drop off. Last year 57% of his shots were taken under pressure – in 2012 & 2013 that figure was 66%.

The data on file begins in 2012 which is unfortunate for McFadden. It was, as Ciaran McMonagle of the samsforthehill blog pointed out to me, a career year for McFadden when Donegal were purring and they were playing to his strengths. 2013 was a bit of a washout for Donegal but in this case was instructive as to how easily Drew Wylie handled McFadden in the Ulster Final. Monaghan were on the lookout for McFadden’s favourite play – the loop inside from the right hand side curving the ball over with the left – and completely snuffed it out.

2014 was a down year but was that McFadden or the way Donegal set up? The loop play disappeared but a lot of that was due to the fact that Murphy spent considerable chunks of time in the middle allowing closer attention on McFadden. Alongside that we saw the further emergence of two left footers in MacNiallais & McBrearty. McFadden’s space narrowed, his foil was missing and he’s not blessed with speed. Not a great mixture.

What does 2015 hold? Usually when you have big swings in data like this you’ll get a regression to the mean but will McFadden be given the space, and as importantly the game time, to rack up the shots? Interesting year ahead.

Dropping shots into the goalkeeper’s hands – is it that bad?

May 13, 2015

Something that appears to drive both coaches and fans nuts is a forward dropping a shot into the opposition goalkeeper’s hands. The apparent calamity of a missed opportunity is enhanced by enabling the opposition to attack you when your defense isn’t set and you are vulnerable. It’s a double blow.
But is it really that bad?

Firstly just how often does it happen? In 23 Championship games last year I recorded a shot dropping into the goalkeeper’s hands on 80 occasions. That is less than two shots per team per game – 1.74 to be exact (80/(23*2))) – not exactly huge.

In total the opposition received the ball from a turnover inside their own 20m line on 428 occasions. These turnovers are broken into three types for the purposes of this piece

• Shots
(a) that drop into the goalkeeper’s hands
(b) that somehow end up with an opposition player other than the goalkeeper (a block picked up, a shot dropping short & the opposition picking the ball up, off the post etc.)
• other turnovers (tackle, pass) where the opposition picks up the ball

The outcome of the possessions from these specific turnovers are outlined below

# Turnovers Return Pts per t/over
Shots – into goalkeeper’s hands 80 0-22 0.28
Shots – other turnovers 94 3-23 0.34
Other T/overs inside 20m 254 2-60 0.26

Ignoring all other factors a ball kicked into the goalkeeper’s hands is no more dangerous than any other shot type that the opposition gets their hands on – and is only on a par with all other turnover types received inside the 20m line. Somewhat surprising. Averages hide a lot – and we are dealing with small volumes – but perhaps this is more of a reflection on goalkeepers than the attacking potential of the turnover. Goalkeeper’s, in the main, are not springboards for attacks but rather keepers (pun intended) of the flame whose primary job is to hand pass the hot potato to the first back that looks for the ball.

Of course there is an element to dropping a shot short that the above does not cover and that is the foregoing of a kickout. When a shot is dropped short you cannot gain any benefit from the possession that immediately ensues. This is most definitely not the case from a kickout.

Now we know that there are ways and means of controlling the kickout however at a macro level below are how teams fared in the above 23 games

# kickouts won Return Pts per t/over
Kickout team 760 10-214 0.32
Opposition 371 14-107 0.40

The kicking team wins 67% of the kickouts scoring 0.32 points per kickout. The opposition wins 33% of all kickouts with a scoring rate of 0.40 points. If you drop a shot short it is this element that you are giving up.

Taking it all together; if a team drops 100 shots into the opposition goalkeeper’s hands they will give up 28 points (100 * 0.28). If they kick it wide they will give up a net ((67*0.32) – (33*0.40)) 8 points. That’s a rather large gap.

So there is a drawback – not necessarily from dropping a ball into the goalkeeper’s hands but giving up a turnover from a shot as a whole. It is not that you are giving a springboard for a counter attack when your defence is not ready but instead you are foregoing the ability to score off the subsequent kickout.

So the question now becomes do you change a player’s shooting mind-set to ensure all shots go dead so that you gain, on average, 0.35 (1.74 * (0.28-0.08)) points in a game? Or is the gain so marginal as to not be worth the risk of changing your player’s style?