How many defensive contributions do you need for a point in FPL?

Defenders need ten defensive actions in a match and midfielders and forwards need twelve. Hitting the threshold is worth two points, not one, and the points do not scale: a defender with ten actions and a defender with twenty both score the same two points. Goalkeepers do not score defensive contribution points; they are rewarded through saves instead.

Which actions count as defensive contributions?

For defenders, clearances, blocks, interceptions and tackles count. For midfielders and forwards the same four count and ball recoveries are added, which is why their threshold is higher at twelve. Saves, aerial duels and fouls won do not count toward defensive contributions.

Which players get the most defensive contributions in FPL?

Ball-winning midfielders at possession-light clubs and centre-backs who defend a deep line record the most. Because the points are a threshold rather than a rate, the number that matters is how often a player clears their own bar rather than what they average. This page ranks every Premier League outfielder by exactly that, and lets you filter by position, price and reliability.

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Defensive Contributions 2026/27

FPL Defensive Contributions

Q: What are defensive contributions in FPL?

Defensive contributions, usually shortened to DefCon, are the defensive actions Fantasy Premier League awards points for. A defender scores two points in any match where their clearances, blocks, interceptions and tackles add up to ten or more. Midfielders and forwards need twelve, and ball recoveries count toward their total as well as those four actions. The two points are awarded once per match no matter how far past the threshold a player goes.

Every outfielder ranked by how often they clear their own DefCon threshold, which is what the two points are paid on.

DEF 10 actions in a match

Clearances, blocks, interceptions and tackles.

MID FWD 12 actions in a match

The same four, plus ball recoveries.

2 points, once per match

Ten actions and twenty actions pay exactly the same.

Most reliable DEF Bobby Thomas DEF COV · £4.0m · 8.9% owned Mostly clearances · 7.9 a game

66% of his last 8 starts

Most reliable MID Exequiel Palacios MID IPS · £5.0m · 0.1% owned Mostly recoveries · 9.0 a game

81% of his last 5 starts

Most reliable FWD Brandon Thomas-Asante FWD COV · £5.0m · 1.1% owned Mostly recoveries · 2.8 a game

18% of his last 5 starts

Leaderboard 80 players

Premier League outfield players ranked by the share of matches in which they clear their Fantasy Premier League defensive contribution threshold, 2026/27 season. Defenders need 10 defensive actions, midfielders and forwards need 12. Minimum 360 minutes played.
#	Player	Price	Owned	Mins	Actions per 90 vs threshold	Hit rate	Where the actions come from	Pts/90	Per £m
1	Exequiel Palacios MID IPS	£5.0m	0.1%	482	16.2	81% 4 of 5 starts	60% recoveries	1.61	0.32
2	Mamadou Sangaré MID BRE	£5.4m	6.4%	494	16.4	78% 4 of 5 starts	47% recoveries	1.56	0.29
3	Bobby Thomas DEF COV	£4.0m	8.9%	676	11.7	66% 5 of 8 starts	55% clearances	1.31	0.33
4	Ethan Pinnock DEF COV	£4.5m	0.1%	552	11.6	65% 6 of 10 starts	52% clearances	1.30	0.29
5	James Hill DEF BOU	£5.5m	2.2%	720	11.5	63% 20 of 30 starts	48% clearances	1.26	0.23
6	John Egan DEF HUL	£4.1m	7.3%	707	11.1	61% 5 of 8 starts	54% clearances	1.22	0.30
7	Elliot Anderson MID MCI	£6.3m	3.7%	606	11.6	60% 25 of 38 starts	58% recoveries	1.21	0.19
8	Tarik Muharemović DEF LEE	£5.1m	6.0%	720	10.8	59% 4 of 8 starts	56% clearances	1.17	0.23
9	António João Pereira de Albuquerque Tavares da Silva DEF BOU	£5.0m	1.6%	720	10.5	57% 6 of 8 starts	52% clearances	1.15	0.23
10	Maxence Lacroix DEF CHE	£5.9m	6.0%	634	10.4	57% 22 of 38 starts	54% clearances	1.14	0.19
11	Chris Richards DEF CRY	£4.9m	0.6%	720	11.3	57% 22 of 38 starts	51% clearances	1.14	0.23
12	Rodrigo Bentancur MID TOT	£5.4m	0.1%	381	14.7	57% 15 of 27 starts	45% recoveries	1.14	0.21
13	Sven Botman DEF NEW	£5.0m	0.8%	630	11.3	57% 16 of 28 starts	48% clearances	1.13	0.23
14	Xaver Schlager MID NFO	£5.0m	0.1%	621	12.5	54% 4 of 7 starts	46% recoveries	1.08	0.22
15	James Tarkowski DEF EVE	£6.2m	18.7%	720	10.6	54% 21 of 38 starts	49% clearances	1.07	0.17
16	James Garner MID EVE	£6.0m	0.2%	598	11.7	52% 21 of 38 starts	43% recoveries	1.04	0.17
17	David Affengruber DEF FUL	£4.5m	0.6%	450	10.0	52% 3 of 5 starts	52% clearances	1.03	0.23
18	Kobbie Mainoo MID MUN	£5.5m	1.1%	444	14.8	52% 11 of 21 starts	57% recoveries	1.03	0.19
19	Jarrad Branthwaite DEF EVE	£5.5m	2.3%	630	10.3	49% 7 of 14 starts	43% clearances	0.97	0.18
20	Daniel Ballard DEF SUN	£4.8m	1.1%	450	9.8	48% 17 of 29 starts	54% clearances	0.97	0.20
21	Shea Charles MID FUL	£5.0m	0.1%	553	11.9	48% 2 of 6 starts	46% recoveries	0.96	0.19
22	Dara O'Shea DEF IPS	£4.0m	2.9%	720	9.8	48% 3 of 8 starts	40% clearances	0.96	0.24
23	Ethan Ampadu MID LEE	£5.3m	0.8%	720	11.0	47% 19 of 38 starts	43% recoveries	0.95	0.18
24	Jaydee Canvot DEF CRY	£4.8m	0.2%	630	8.6	47% 11 of 21 starts	41% clearances	0.94	0.20
25	Nordi Mukiele DEF SUN	£5.4m	1.8%	591	12.2	47% 16 of 38 starts	38% clearances	0.94	0.17
26	Vitaly Janelt MID BRE	£5.0m	1.7%	630	12.7	47% 10 of 22 starts	41% recoveries	0.94	0.19
27	Alex Scott MID BOU	£5.9m	2.3%	446	12.1	47% 18 of 38 starts	51% recoveries	0.94	0.16
28	Luka Vušković DEF BHA	£5.2m	6.7%	707	9.7	46% 4 of 8 starts	51% clearances	0.92	0.18
29	Kristoffer Ajer DEF BRE	£4.5m	4.3%	720	10.0	45% 12 of 28 starts	49% clearances	0.89	0.20
30	Jeremy Jacquet DEF LIV	£5.1m	4.3%	682	9.4	43% 4 of 8 starts	28% clearances	0.86	0.17
31	Murillo Costa dos Santos DEF NFO	£5.5m	2.1%	719	9.5	42% 15 of 33 starts	40% clearances	0.85	0.15
32	Virgil van Dijk DEF LIV	£6.4m	15.0%	720	9.8	42% 16 of 38 starts	60% clearances	0.83	0.13
33	Gabriel dos Santos Magalhães DEF ARS	£7.9m	23.6%	720	9.0	41% 15 of 38 starts	51% clearances	0.82	0.10
34	Joao Gomes MID AVL	£5.5m	0.1%	366	9.3	40% 16 of 37 starts	47% recoveries	0.81	0.15
35	Kevin Danso DEF SUN	£5.0m	0.2%	376	6.2	40% 13 of 22 starts	53% clearances	0.80	0.16
36	Granit Xhaka MID SUN	£5.4m	2.9%	720	10.1	40% 15 of 38 starts	51% recoveries	0.80	0.15
37	Tyler Adams MID BOU	£5.0m	0.3%	547	11.7	39% 11 of 27 starts	45% recoveries	0.78	0.16
38	Nikola Milenković DEF NFO	£5.4m	0.8%	360	9.3	39% 15 of 38 starts	49% clearances	0.78	0.15
39	Jan Paul van Hecke DEF TOT	£4.9m	9.1%	720	9.1	38% 12 of 38 starts	41% clearances	0.77	0.16
40	Anan Khalaili DEF CRY	£5.0m	0.3%	649	9.2	38% 2 of 7 starts	39% recoveries	0.75	0.15
41	James McAtee MID NFO	£5.5m	0.1%	680	11.3	38% 2 of 10 starts	58% recoveries	0.75	0.14
42	Malick Thiaw DEF NEW	£5.0m	1.7%	631	8.8	37% 13 of 38 starts	47% clearances	0.73	0.15
43	Declan Rice MID ARS	£7.4m	12.1%	670	8.7	34% 13 of 38 starts	45% recoveries	0.68	0.09
44	Adrien Truffert DEF BOU	£5.4m	3.1%	713	7.6	33% 13 of 38 starts	37% recoveries	0.65	0.12
45	Lewis Miley MID NEW	£5.5m	0.1%	544	11.4	32% 7 of 22 starts	46% recoveries	0.64	0.12
46	Issa Diop DEF IPS	£3.9m	10.5%	720	8.6	32% 5 of 16 starts	40% clearances	0.64	0.16
47	James Justin DEF LEE	£4.5m	2.3%	708	7.9	30% 7 of 29 starts	34% clearances	0.60	0.13
48	Levi Samuels Colwill DEF CHE	£4.8m	0.9%	611	7.5	30% 3 of 9 starts	47% clearances	0.60	0.12
49	Quinten Timber MID CRY	£5.0m	0.0%	388	10.2	29% 2 of 5 starts	50% recoveries	0.58	0.12
50	Anton Stach MID LEE	£6.0m	2.0%	651	10.0	29% 12 of 35 starts	43% recoveries	0.58	0.10
51	Nico González Iglesias MID NEW	£5.5m	0.2%	434	10.0	29% 9 of 23 starts	47% recoveries	0.58	0.10
52	Abdukodir Khusanov DEF MCI	£5.3m	1.2%	372	8.2	28% 6 of 19 starts	37% recoveries	0.57	0.11
53	Mohamed Belloumi MID HUL	£5.2m	10.1%	595	10.0	28% 2 of 7 starts	38% recoveries	0.57	0.11
54	Milan van Ewijk DEF COV	£3.9m	7.2%	630	7.7	27% 2 of 7 starts	36% clearances	0.55	0.14
55	Antonee Robinson DEF FUL	£4.4m	1.3%	609	7.4	26% 6 of 24 starts	38% recoveries	0.53	0.12
56	Boubacar Kamara MID AVL	£5.0m	0.4%	713	10.4	26% 6 of 25 starts	42% recoveries	0.52	0.10
57	Harry Maguire DEF MUN	£4.7m	5.9%	720	7.0	25% 10 of 27 starts	44% clearances	0.50	0.11
58	Jacob Greaves DEF IPS	£3.9m	1.1%	447	7.5	25% 1 of 5 starts	41% clearances	0.49	0.13
59	Lewis Hall DEF NEW	£5.3m	20.5%	719	8.8	24% 10 of 32 starts	45% recoveries	0.49	0.09
60	Adam Wharton MID CRY	£5.4m	0.7%	706	7.5	24% 10 of 37 starts	50% recoveries	0.48	0.09
61	Tyrone Mings DEF AVL	£4.5m	0.4%	441	8.0	24% 5 of 19 starts	55% clearances	0.47	0.11
62	Calvin Bassey DEF FUL	£4.5m	1.3%	720	7.8	24% 11 of 36 starts	36% recoveries	0.47	0.10
63	Dominik Szoboszlai MID LIV	£6.7m	14.1%	471	9.0	24% 10 of 38 starts	57% recoveries	0.47	0.07
64	Youri Tielemans MID MUN	£5.7m	1.3%	588	10.4	24% 5 of 29 starts	50% recoveries	0.47	0.08
65	Lewis Dunk DEF BHA	£4.5m	1.4%	569	7.0	23% 9 of 37 starts	39% clearances	0.46	0.10
66	Reinildo Mandava DEF SUN	£4.4m	0.3%	612	7.7	23% 4 of 30 starts	34% recoveries	0.46	0.10
67	Marc Guéhi DEF MCI	£6.0m	16.7%	675	5.3	23% 10 of 38 starts	40% clearances	0.45	0.08
68	Ronald Araujo DEF LIV	£5.4m	3.7%	493	7.9	22% 2 of 6 starts	38% clearances	0.45	0.08
69	Vitalii Mykolenko DEF EVE	£4.6m	2.4%	613	7.2	22% 9 of 38 starts	38% clearances	0.44	0.10
70	Ola Aina DEF NFO	£4.3m	1.6%	388	7.2	21% 2 of 23 starts	38% recoveries	0.42	0.10
71	Nico Elvedi DEF LEE	£4.5m	0.1%	501	7.2	21% 1 of 5 starts	50% clearances	0.42	0.09
72	Sandro Tonali MID TOT	£5.3m	2.0%	697	10.1	21% 7 of 38 starts	55% recoveries	0.42	0.08
73	Harrison Armstrong MID EVE	£5.0m	0.3%	697	9.3	20% 3 of 14 starts	45% recoveries	0.40	0.08
74	Iliman Ndiaye MID MCI	£5.8m	5.5%	598	8.6	20% 8 of 38 starts	62% recoveries	0.39	0.07
75	Diego Gómez Amarilla MID BHA	£5.0m	3.9%	700	9.1	19% 5 of 34 starts	48% recoveries	0.39	0.08
76	Frank Onyeka MID COV	£4.8m	0.1%	379	9.3	19% 0 of 4 starts	50% recoveries	0.38	0.08
77	Daichi Kamada MID CRY	£5.0m	0.7%	700	8.0	19% 6 of 30 starts	54% recoveries	0.38	0.08
78	Semi Ajayi DEF HUL	£4.2m	12.9%	693	6.9	18% 1 of 8 starts	36% clearances	0.37	0.09
79	Lisandro Martínez DEF MUN	£4.8m	1.1%	520	6.4	18% 6 of 19 starts	38% clearances	0.36	0.08
80	Caleb Yirenkyi MID COV	£4.8m	0.1%	467	9.3	18% 1 of 6 starts	53% recoveries	0.36	0.08

clears the threshold on average within 15% of it short of it the player's own threshold
clearances recoveries tackles interceptions blocks
Minimum 360 minutes played. Hit rate is the modelled chance of clearing the threshold in a start, using the match to match spread measured from our own data rather than assuming actions arrive at a steady tempo. That is what puts a defender on 9.5 actions and a midfielder on 11 on the same scale. Underneath it is what actually happened, and the final column is what those actions are made of, which the official data does not break down at all.

Where the actions come from Average defensive actions per 90 by club.

Average defensive actions per 90 across every qualifying outfielder at each club. Sides that spend the game without the ball generate the actions, so this is really a map of where to shop — and a warning, because the same clubs tend to concede the clean sheets you also want.

Brentford 9.2 1 over 50%
Bournemouth 8.4 2 over 50%
Coventry City 8.3 2 over 50%
Everton 8.2 2 over 50%
Spurs 8.1 1 over 50%
Newcastle 8.1 1 over 50%
Crystal Palace 8.0 1 over 50%
Ipswich Town 7.8 1 over 50%
Aston Villa 7.7 0 over 50%
Man Utd 7.5 1 over 50%
Liverpool 7.5 0 over 50%
Nott'm Forest 7.4 1 over 50%
Leeds 7.2 1 over 50%
Fulham 7.2 1 over 50%
Sunderland 7.1 0 over 50%
Hull City 7.0 1 over 50%
Chelsea 7.0 1 over 50%
Man City 6.4 1 over 50%
Brighton 6.4 0 over 50%
Arsenal 5.9 0 over 50%

What are defensive contributions in FPL?

Defensive contributions, shortened to DefCon by most managers, are the defensive actions Fantasy Premier League awards points for. A defender scores two points in any match where their clearances, blocks, interceptions and tackles add up to ten or more. A midfielder or forward needs twelve, and ball recoveries count toward their total as well as those four actions. Goalkeepers are not scored this way at all; they are rewarded through saves.

The critical detail is that this is a threshold, not a rate. The two points are awarded once per match, so a defender who records ten actions and a defender who records twenty score exactly the same. That single fact changes how you should shop for the statistic, and it is where most defensive contribution content goes wrong.

Why the table above is not sorted on the average

Because the points are a threshold, what you are buying is not a player's average but how often they cross the line. The hit rate column converts each player's rate into the chance of clearing their own bar in a full match, and that is what the board is ranked on by default. It matters most when comparing positions: a defender averaging 9.5 actions is a far better bet for two points than a midfielder averaging 11, because the defender needs ten and the midfielder needs twelve. Sorted on the raw average, the midfielder looks the better player. Sorted on hit rate, the truth shows up.

FPL publishes a season total and nothing finer, so every tool built on it has to work backwards from an average and guess how those actions were spread across the season. The usual guess is that they arrive at a steady tempo. They do not. We hold the matches themselves, and across last season defensive actions varied about one and a half times as much as a steady tempo allows, because they depend on how much of the game a team spends without the ball. The same player records four one week and sixteen the next.

Feeding that measured spread into the model changes the answer in both directions: a player averaging below his threshold clears it more often than the steady assumption credits, and one averaging comfortably above it misses more often. The averages themselves come from starts only, so a substitute who made one tackle in one minute of football does not appear as a 90-actions-per-90 player. Only players past 360 minutes appear here at all.

Worth saying what we did not do, because it is the obvious move and it is wrong. Having the matches, the tempting thing is to rank players on how often they actually cleared the bar. Tested properly, by fitting on the first part of each player's season and predicting the rest, that turns out to be the worst of the options, worse even than the steady-tempo assumption. A threshold throws away almost everything: a nine-action game and a two-action game both count only as a miss. The count is shown beside each player because it is a fact worth seeing, but the ranking uses the full distribution.

What the actions are made of

The last column of the table is the part FPL cannot show you at all. Two players can clear the threshold just as often as each other and be nothing alike underneath. Last season Kevin Danso cleared it in 81% of his starts, almost entirely on clearances, averaging 7.8 a game. Elliot Anderson cleared it in 70%, and did it on ball recoveries, averaging 8.2.

Those two returns behave very differently. Clearances come from defending your own box, so a clearance-heavy defender is being paid for his team being under pressure, and a run of kind fixtures quietly takes his points away with it. Recoveries follow where a midfielder is asked to stand, which is a decision his manager makes rather than something the opposition does to him, so they hold up far better against a soft run. If you are buying defensive contributions to survive a good set of fixtures, the split is what tells you which players will still be scoring them.

How to actually use this

Defensive contributions are worth roughly two points a week to a player who reliably clears the threshold, which over a season is comparable to a handful of goals. That makes them most valuable in cheap defenders and mid-priced midfielders, where two points a week is a large share of what you are paying for, and close to irrelevant in premium attackers you own for goals. The per £m column is that argument in a number: filter to £5.0m and under and sort on it to find the budget picks doing the work.

The trap is buying the statistic in isolation. A midfielder at a club that concedes possession will rack up actions precisely because his team is defending, which usually means fewer attacking returns and fewer clean sheets. That tension is visible in the club table above: the sides at the top generate the most actions and are rarely the sides you want for clean sheets. The players worth owning are the ones who clear the threshold at clubs that also keep the ball out of their own net, and the fixture ticker is where you check the second half of that.

To weigh defensive contributions against everything else a player does, the player explorer has actions per 90 as a sortable column alongside price, minutes and every attacking metric, and the team rater prices the threshold into every projection it makes.

More FPL tools

Player Explorer Every player, projected and filterable. Open Rate My Team Your captain, transfers and weak links. Open Team Builder Draft a legal fifteen within £100m. Open Fixture Ticker Difficulty priced from the betting market. Open League Rankings The OddAlerts FPL league top 50. Open

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