A Closer Look At Carries / Passes In Rugby Union

1 Introduction

I have been coaching in the AIL for 11 years and over the last four season I have pushed my teams to get 1.3 passes per carry (PPC). I never researched this number as to be a game winning metric, it was more to aling with my coaching philosophy. More established game winning metrics are how many visits to the opposition 22 you have, how few visits you give them, low penalty against count, linebreaks created and kicking distance. This post is my own personal deep dive into PPC and how it affects the game.

2 Winners and Losers

Table 1
	Carries	Metres Gained	Linebreaks	Gainlines	Passes	Passes / Carry	M Per Carry
Winner	317	660	14	175	355	1.12	2.08
Loser	376	807	17	213	498	1.32	2.15

What we see in the table above is that the wining team had less overall carries therefore had less metres gained, less passes and created less linebreaks. This alings with professional rugby data that suggests having less of the ball and kicking more leads to winning more. Sam Larner goes into super detail on this in his new book Attacking The Space. I am more interested in what is happening when teams do have the ball and want to keep it.

3 Home and Away

Table 2
	Carries	Metres Gained	Linebreaks	Gainlines	Passes	Passes / Carry	M Per Carry
Home Team	364	856	19	212	466	1.28	2.35
Away Team	329	611	12	176	387	1.18	1.86

There is a clear link to team performance and home advantage with the home team coming out on top of all the stats above. The home had 35 more carries or attacks, gaining an extra 245 more metres which is just on average 62 extra metres a game and creating 7 more linebreaks. The difference between PPC is 1.28 for the home team and 1.18 for the away team. This suggests that the away teams passed the ball less per phases and this is connected to less linebreaks.

4 How Do The Games Look?

Table 3
	Carries	Metres Gained	Linebreaks	Gainlines	Passes	Passes / Carry	M Per Carry
Old Crescent v Ballymena	165	192	3	86	220	1.33	1.16
Cashel v Old Crescent	210	355	10	117	258	1.23	1.69
Old Crescent v Greystones	187	509	11	114	225	1.20	2.72
Barnhall v Old Crescent	131	411	7	71	150	1.15	3.14

What stands out here is the game with highest number of PPC is Old Crescent V Ballymena which also had the lowest number of linebreaks, I believe this is an outlier. The PPC in that game was 1.33 and there was a linebreak every 66 passes. Where as the other three games grouped together had an average PPC of 1.19, with a linebreak every 22.6 passes. The two games with the highest volume of carries had the same PPC of 1.2 and most linebreaks of 10 and 11.

5 A Closer Look At Linebreaks

Table 4
Pass Count	Attacks Leading to Linebreaks	Metres Gained	Metres / Carry	Number of Attacks / Pass Number	% of Attacks Laeding to Linebreaks
0	5	110	22.00	158	3.2%
1	9	126	14.00	333	2.7%
2	8	170	21.25	123	6.5%
3	2	23	11.50	51	3.9%
4	4	107	26.75	21	19.0%
5	1	24	24.00	5	20.0%
6	2	39	19.50	2	100.0%

The connection between % of linebreaks and the higher pass count a team has between carries or phase is hugely strong here. 5 linebreaks from attacks with zero passes looks very high when most 0 pass attacks would be pick and goes but when we divide it by the over volume of 158 attacks with 0 passes its only 3.2%. Where as attacks with 4 and 5 passes in them had a linebreak 19% and 20% of the time, with a huge just to 100% on attacks with 6 passes.

5.1 PPC and Linebreaks to Outcomes

The plot above show that a linebreak had an average of 2 PPC which suggest a higher PPC results in linebreaks, but turnovers against being the next highest at 1.75 shows the risk reward element of higher a PPC rate. There was 27 linebreaks in the 4 games and a total of 80 turnsovers against from all attacks. Again this would suggest a more cautious style of rugby is more rewarding. Penalties won and Gainline carries are the other positive outcomes and both were the on the lower end of the PPC scale. A key match winning stat has always been linebreaks created and there is a clear link from table 4 and scatterplot 1 that linebreaks happen with more phases between phases.

5.2 Defenders Beaten

Table 5
Defenders Beaten	Number of Attacks	Metres Gained	Total Passes	Metres / Carry	Passes / Carry
1	56	496	88	8.86	1.57
2	23	319	44	13.87	1.91
3	3	113	4	37.67	1.33

Looking at Table 5 we can see again like linebreaks there is a connection between higher PPC and beating defenders. 56 times an attack lead to one defender beaten gaining on average 8.86 Metres each carry, when an attack lead to two defenders beaten the metres / carry jumps to 13.87 which happen 13 times across the 4 games with an average PPC of 1.91. Three times three defenders were beaten leading to 37.67 metres gained on average.

6 How Does the First Reciver Affect PPC

Here we see that backrow forwards get on the ball most and have the greatest volume of passes output, outhalves are the 2nd most first receivers but have the biggest passing output. If we look at the plot below where we only look at phase play and not kick returns or starter plays we still see backrows and outhalves highest for both figures. What stands out for me is how high prop forwards are as first receivers.

6.1 First Receivers and Metres Gained

When we look at metres gained as an output we see that props drop right to the bottom, This suggests that a team should avoid having props at first receivers. This graph also suggests the more often wingers and fullbacks are on the ball the better. To further this point the data also showed when examined that props gained on averaged 1.6 m/carry on 0 passes. Zero passes would occur on pick and goes forwards and mostly kick returns. The rest of the forwards averaged 1.09 m/carry on 0 passes while centres had a big 5.12 m/carry and back three (wingers and fullbacks) players were up to 6.85. This shows props huge power in the pick and go area. However when we look at it for 1 pass, now the scrumhalf has passed to a first receiver and that player has carried, props m/carry drops to 0.21, the other forwards averaged 0.72, centers 0.82 and back three 4.56. To further the point when we examined 2 passes, this would be the first receiver passing to the next player and that player carried, these attacks gained for props as first receiver 0.28 m/carry, the rest of the pack gained 3.31, centres averaged 2.00 and the back three had averaged 5.25 m /carry. This really does suggest that once props are the first player receiving a pass the teams ability to gain metres drops sharply.

7 Where Does The Action Happen

Below we look at very simple rugby pitch maps to examine where the action starts from and the volume of action in that zone. I broke the pitch up into 12 zones. Left, Middle and Right. Goal Line to 22, 22 to 50, 50 to 22 and 22 to Try Line.

7.1 Zone Analysis Comparison For Total Passes Made

The above pitch are broken into three groups, all teams data, winning only and losing only data. We can see that the main action zone is the middle of 50 to 22. The zones from each teams goal line to halfway is very similar but in the other half teams that lost had more passes.

7.2 Zone Analysis Comparison For Passes / Carry

We see here that the losing teams really had a much higher volume of Passes / Carries.

7.3 Zone Analysis Comparison For Total Carries

Again, the losing teams continues to be darker suggesting they are playing more with the ball. Here we see them having more carries. We also see that th main pitch zone is still middle 50 to 22.

7.4 Zone Analysis Comparison To Compare Linebreak Pitch Source

The bulk of the linebreaks started from the middle of the pitch, this would make sense as teams find it much easier to defend from an edge.

8 Conclusion

There is a clear trend in these AIL games that connects with professional rugby where winning teams have less of the ball, carry less, pass less and play only in the high value pitch areas. This study was more for me to look deeper at passes / carry and if I should continue to push this as a key match data point and how it blends in my coaching philosophy, I don’t mind admitting I was very disappointed with the first dataset I produced that showed winning teams with a lower passes / carry rate. However looking closer at the data we can see that a higher passes / carry rate is very strongly connected to linebreaks and defenders beaten. The higher the pass number the higher the probability of a linebreak. We also looked at who needs to be at first receiver to help the teams attack and the data point towards outhalves and back three should be getting on the ball more but also that prop forwards hurt the teams metres gained once a pass occurrs but props had huge value in the pick and go area. I also see big gains in the teams attack the more often centres get on the ball either with 0 pass attacks or when at first receiver. Lastly, the middle zone from 50 to 22 is where teams come to play. Defence teams still need to hold two in the back field and attacking teams are more willing to hold the ball more and push the pass count higher leading to a higher passes /carry rate right across the the 50 to 22 three zones and this lead to a higher concentration of linebreaks too, but we have seen in the first scatterplot a higher passes / carry rate leads to more linebreaks but also more turnovers. There is a clear risk reward element to a higher passess / carry rate.