Development goals for 4 to 5 year olds

Published

1. Main facts and figures

  • 71% of 4 to 5 year olds met the expected standard in development by the end of the 2018 to 2019 school year
  • 76% of pupils from the Chinese ethnic group met the expected standard (the highest percentage out of the 6 aggregated ethnic groups)
  • 78% of pupils from the Indian ethnic group met the standard (the highest percentage out of all 18 ethnic groups)
  • in every ethnic group, pupils eligible for free school meals were less likely to meet the standard than non-eligible pupils
  • in every ethnic group, girls were more likely to meet the expected standard than boys
Things you need to know

In the 2018 to 2019 school year, there were 638,946 pupils at the end of the early years foundation stage in England.

The ethnic group was known for 616,459 (97%) of them. Of those:

  • 72% were White
  • 11% were Asian
  • 7% had Mixed ethnicity
  • 5% were Black
  • 2% were from the Other ethnic group
  • 0.5% were from the Chinese ethnic group

The results include pupils at both:

  • state-funded schools (including academies)
  • private, voluntary and independent settings

Schools complete each child's early years foundation stage profile during the summer term of the academic year in which the child reaches 5 years old. This is usually the child's 'reception year' at primary school.

Some pupils aren’t included, for example if they:

  • have an exemption from the Secretary of State for Education
  • are continuing in EYFS provision beyond the year in which they turn 5 years old
  • have recently arrived from abroad and so the school can't carry out an accurate assessment
  • have spent a long time away from school, for example because of illness

The percentages shown here don't include pupils who were exempt.

Figures for some ethnic groups at the local authority level are very small. Please use caution when you're interpreting them.

What the data measures

This data measures the percentage of pupils who met the expected standard in development at the end of the early years foundation stage in England.

Teachers assess their pupils' development at the end of the school year in which the children turn 5 years old. (Usually the reception year of primary school.)

Children are assessed against ‘early learning goals’ in 7 areas of learning.

This data covers the academic year 2018/19 (September 2018 to July 2019).

Data was collected for 638,946 pupils.

The ethnic categories used in this data

This data uses categories from the Department for Education’s (DfE) school census. This is based on the 2001 Census of England and Wales, with 3 exceptions:

  • Travellers of Irish Heritage and Gypsy/Roma pupils have been separated into 2 categories
  • Sri Lankan has been added to the Asian/Asian British group but is not reported separately
  • Chinese pupils have been assigned a separate category

These changes were made after consultations with local authorities and lobby groups.

Information is provided for both individual and aggregated ethnic groups categories where possible and when the data is available. The 6 aggregated ethnic groups are:

  • Asian
  • Black
  • Chinese
  • Mixed/Multiple ethnic groups
  • White
  • Other ethnic group

The Other ethnic group isn’t included in data analysed by local authority area, because DfE does not publish this data.

2. By ethnicity

Percentage of 4 to 5 year olds who met the expected standard in development, and total number of eligible pupils, by ethnicity
Ethnicity % All pupils
All 71 638,946
Asian 69 69,185
Bangladeshi 67 10,212
Indian 78 20,363
Pakistani 64 27,141
Asian other 69 11,469
Black 68 31,136
Black African 68 21,432
Black Caribbean 68 5,270
Black other 66 4,434
Chinese 76 3,002
Mixed 72 41,685
Mixed White/Asian 75 10,305
Mixed White/Black African 71 5,777
Mixed White/Black Caribbean 69 9,814
Mixed other 73 15,789
White 72 459,403
White British 73 409,675
White Irish 74 1,551
Gypsy/Roma 34 2,151
Irish Traveller 39 665
White other 66 45,361
Other 63 12,048

Download table data for ‘By ethnicity’ (CSV) Source data for ‘By ethnicity’ (CSV)

Summary of Development goals for 4 to 5 year olds By ethnicity Summary

This data shows that, in the 2018 to 2019 school year:

  • 71% of pupils met the expected standard in development in the early years foundation stage (when they are usually 5 years old)
  • 78% of pupils from the Indian ethnic group met the expected standard, the highest percentage out of all ethnic groups
  • the figures for the Chinese (76%), Mixed White and Asian (75%), White Irish (74%), White British (73%), and Mixed Other (73%) ethnic groups were also higher than the national average
  • Gypsy/Roma pupils were least likely to meet the expected standard, with 34% doing so

3. By ethnicity and eligibility for free school meals

Percentage of 4 to 5 year olds who met the expected standard in development, and total number of pupils, by ethnicity and eligibility for free school meals (FSM)
All other pupils FSM eligible
Ethnicity All other pupils % All other pupils Pupils FSM eligible % FSM eligible Pupils
All 73 549,204 55 89,742
Asian
Bangladeshi 68 8,564 62 1,648
Indian 78 19,646 66 717
Pakistani 65 23,627 60 3,514
Asian other 70 10,210 58 1,259
Black
Black African 69 17,016 64 4,416
Black Caribbean 70 3,730 61 1,540
Black other 67 3,382 61 1,052
Chinese 77 2,789 67 213
Mixed
Mixed White/Asian 78 8,943 59 1,362
Mixed White/Black African 73 4,592 60 1,185
Mixed White/Black Caribbean 73 6,874 59 2,940
Mixed other 75 13,072 60 2,717
White
White British 76 350,353 53 59,322
White Irish 78 1,354 49 197
Gypsy/Roma 35 1,521 33 630
Irish Traveller 47 360 29 305
White other 66 42,489 55 2,872
Other 65 9,646 56 2,402

Download table data for ‘By ethnicity and eligibility for free school meals’ (CSV) Source data for ‘By ethnicity and eligibility for free school meals’ (CSV)

Summary of Development goals for 4 to 5 year olds By ethnicity and eligibility for free school meals Summary

Eligibility for free school meals (FSM) is used as an indicator of deprivation by the Department for Education.

This data shows that, in the 2018 to 2019 school year:

  • 55% of FSM-eligible pupils met the expected standard, compared with 73% of non-FSM pupils
  • in every ethnic group, FSM-eligible pupils were less likely to meet the expected standard than non-FSM pupils
  • among FSM-eligible pupils, those from the Chinese ethnic group were the most likely out of all ethnic groups to meet the expected standard (at 67%)
  • Traveller of Irish Heritage pupils were the least likely out of all ethnic groups to meet the expected standard (at 29%)
  • the figures for the White British (53%), White Irish (49%), and Gypsy and Roma (33%) ethnic groups were also lower than the national average
  • White Irish pupils had the biggest attainment gap between FSM-eligible (49%) and non-FSM pupils (78%)
  • Gypsy and Roma pupils had the smallest attainment gap between FSM-eligible (33%) and non-FSM pupils (35%)

4. By ethnicity and area

Percentage of 4 to 5 year olds who met the expected standard in development, by ethnicity and local authority
Local authority All Asian Black Chinese Mixed White
% % % % % %
All England 71 69 68 76 72 72
Barking and Dagenham 70 70 73 67 70 69
Barnet 73 76 71 80 74 76
Barnsley 69 64 83 withheld because a small sample size makes it unreliable 77 69
Bath and North East Somerset 73 67 50 63 68 74
Bedford Borough 68 64 64 withheld because a small sample size makes it unreliable 69 69
Bexley 75 76 74 88 78 76
Birmingham 66 67 67 75 69 67
Blackburn with Darwen 66 67 75 withheld because a small sample size makes it unreliable 62 67
Blackpool 67 44 71 60 83 67
Bolton 66 66 56 68 68 67
Bournemouth Christchurch and Poole 73 78 74 67 69 75
Bracknell Forest 76 74 78 64 83 76
Bradford 67 66 61 71 68 68
Brent 71 76 68 90 76 72
Brighton and Hove 71 63 65 53 75 72
Bristol City of 70 65 59 82 71 72
Bromley 77 81 67 89 79 79
Buckinghamshire 74 66 64 73 75 76
Bury 70 64 57 75 69 73
Calderdale 69 58 56 43 75 72
Cambridgeshire 70 67 64 76 72 70
Camden 72 72 69 78 77 73
Central Bedfordshire 72 73 58 93 68 72
Cheshire East 71 73 57 63 68 72
Cheshire West and Chester 71 74 57 43 70 71
City of London 85 86 N/A* N/A* withheld because a small sample size makes it unreliable 91
Cornwall 69 58 100 64 79 69
Coventry 69 71 69 84 69 68
Croydon 73 74 71 100 76 74
Cumbria 70 55 71 71 66 70
Darlington 70 63 89 withheld because a small sample size makes it unreliable 61 71
Derby 70 74 68 73 75 69
Derbyshire 69 62 64 81 67 70
Devon 72 69 85 50 71 73
Doncaster 71 75 58 50 75 72
Dorset 71 52 57 withheld because a small sample size makes it unreliable 72 72
Dudley 65 60 68 73 65 66
Durham 71 68 73 90 71 71
Ealing 70 74 67 75 72 73
East Riding of Yorkshire 73 58 75 N/A* 68 73
East Sussex 76 72 55 80 77 76
Enfield 69 81 66 76 76 68
Essex 73 73 67 80 74 74
Gateshead 72 74 59 69 75 73
Gloucestershire 71 57 56 65 71 72
Greenwich 78 77 76 88 82 78
Hackney 68 81 71 94 76 79
Halton 65 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable N/A* 68 65
Hammersmith and Fulham 72 74 64 78 68 77
Hampshire 76 75 72 77 73 77
Haringey 74 76 69 76 77 77
Harrow 74 78 64 75 77 73
Hartlepool 71 65 57 withheld because a small sample size makes it unreliable 78 72
Havering 71 73 69 76 76 71
Herefordshire 75 70 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 83 76
Hertfordshire 72 69 64 78 71 73
Hillingdon 74 78 73 85 78 71
Hounslow 72 76 69 81 76 70
Isle of Wight 70 50 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 77 70
Isles of Scilly 79 N/A* N/A* N/A* withheld because a small sample size makes it unreliable 81
Islington 68 66 61 75 75 69
Kensington and Chelsea 68 60 61 100 74 75
Kent 73 77 73 71 76 74
Kingston Upon Hull City of 63 73 62 withheld because a small sample size makes it unreliable 67 64
Kingston upon Thames 75 70 74 83 74 78
Kirklees 69 64 61 67 67 72
Knowsley 66 89 43 withheld because a small sample size makes it unreliable 62 66
Lambeth 70 60 66 82 69 77
Lancashire 67 57 62 69 69 69
Leeds 66 62 59 82 66 68
Leicester 66 71 61 64 68 63
Leicestershire 71 72 65 79 70 71
Lewisham 76 74 70 76 77 82
Lincludingolnshire 69 73 67 86 69 69
Liverpool 64 61 59 64 62 65
Luton 67 68 73 80 69 66
Manchester 64 64 67 59 67 66
Medway 73 70 73 57 76 73
Merton 75 72 72 87 78 77
Middlesbrough 61 62 73 50 57 62
Milton Keynes 73 80 66 84 77 72
Newcastle upon Tyne 70 66 60 88 74 72
Newham 74 77 72 85 79 73
Norfolk 72 66 76 89 78 72
North East Lincludingolnshire 70 71 60 withheld because a small sample size makes it unreliable 73 71
North Lincludingolnshire 70 69 45 withheld because a small sample size makes it unreliable 69 72
North Somerset 74 61 77 withheld because a small sample size makes it unreliable 74 75
North Tyneside 71 67 60 69 71 71
North Yorkshire 72 56 72 44 76 72
Northamptonshire 70 71 72 70 66 70
Northumberland 74 67 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 70 75
Nottingham 65 67 68 73 67 64
Nottinghamshire 69 63 67 61 68 70
Oldham 66 60 69 54 67 71
Oxfordshire 73 66 64 79 72 74
Peterborough 65 61 63 76 72 65
Plymouth 68 71 82 56 69 68
Portsmouth 69 59 69 82 72 70
Reading 67 72 60 87 72 69
Redbridge 75 79 70 84 78 70
Redcar and Cleveland 70 75 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 74 70
Richmond upon Thames 80 78 64 89 80 82
Rochdale 64 61 58 77 63 67
Rotherham 69 66 64 81 67 70
Rutland 78 withheld because a small sample size makes it unreliable 67 N/A* 81 78
Salford 66 66 62 90 66 69
Sandwell 65 68 65 72 67 65
Sefton 68 53 46 67 73 68
Sheffield 70 68 69 79 67 72
Shropshire 72 58 88 withheld because a small sample size makes it unreliable 86 72
Slough 73 77 72 withheld because a small sample size makes it unreliable 74 68
Solihull 70 74 49 73 63 72
Somerset 71 68 63 78 69 72
South Gloucestershire 76 75 73 84 73 77
South Tyneside 72 63 42 60 68 73
Southampton 70 69 74 81 74 70
Southend-on-Sea 73 65 67 92 75 75
Southwark 73 71 70 77 78 79
St. Helens 68 50 67 withheld because a small sample size makes it unreliable 69 69
Staffordshire 73 68 66 74 73 74
Stockport 69 62 52 61 63 71
Stockton-on-Tees 73 64 74 63 72 74
Stoke-on-Trent 65 61 65 63 63 68
Suffolk 69 65 61 86 69 71
Sunderland 72 65 58 71 66 73
Surrey 78 74 72 89 81 78
Sutton 72 76 66 81 70 72
Swindon 70 73 75 75 73 70
Tameside 65 57 48 67 66 68
Telford and Wrekin 70 60 72 withheld because a small sample size makes it unreliable 77 70
Thurrock 72 69 76 50 77 72
Torbay 70 46 0 withheld because a small sample size makes it unreliable 79 71
Tower Hamlets 69 69 73 72 69 69
Trafford 74 68 60 78 69 77
Wakefield 70 61 56 70 69 71
Walsall 66 66 61 85 65 67
Waltham Forest 76 74 71 78 80 78
Wandsworth 76 72 66 77 73 81
Warrington 73 67 63 71 71 73
Warwickshire 71 73 61 93 72 71
West Berkshire 74 78 65 withheld because a small sample size makes it unreliable 76 75
West Sussex 71 64 61 54 73 72
Westminster 70 77 70 86 68 76
Wigan 66 51 57 75 67 67
Wiltshire 71 71 67 75 68 72
Windsor and Maidenhead 74 68 86 withheld because a small sample size makes it unreliable 74 76
Wirral 67 59 83 63 75 68
Wokingham 76 78 77 87 77 76
Wolverhampton 67 67 64 73 70 67
Worcestershire 71 66 62 80 72 72
York 74 55 85 90 69 75

Download table data for ‘By ethnicity and area’ (CSV) Source data for ‘By ethnicity and area’ (CSV)

Summary of Development goals for 4 to 5 year olds By ethnicity and area Summary

The summary below only includes figures based on enough pupils to make reliable generalisations.

This data shows that, in the 2018 to 2019 school year:

  • out of all local authorities, Asian pupils were most likely to meet the expected standard in Knowsley (89%) and least likely to in Blackpool (44%)
  • Black pupils were most likely to meet the expected standard in Cornwall (100%) and least likely to in Torbay (0%)
  • 100% of Chinese pupils met the expected standard in Croydon and Kensington and Chelsea – they were least likely to meet the standard in Calderdale, and Cheshire West and Chester (both 43%)
  • pupils with Mixed ethnicity were most likely to meet the expected standard in Shropshire (86%) and least likely to in Middlesbrough (57%)
  • White pupils were most likely to meet the expected standard in the City of London (91%) and least likely to in Middlesbrough (62%)

5. By ethnicity and gender

Percentage of 4 to 5 year olds who met the expected standard in development, and total number of pupils, by ethnicity and gender
Boys Girls
Ethnicity Boys % Boys All pupils Girls % Girls All pupils
All 64 327,425 78 311,521
Asian
Bangladeshi 60 5,219 75 4,993
Indian 72 10,461 84 9,902
Pakistani 57 13,957 72 13,184
Asian other 61 5,900 77 5,569
Black
Black African 60 10,958 77 10,474
Black Caribbean 60 2,716 75 2,554
Black other 58 2,262 74 2,172
Chinese 72 1,589 81 1,413
Mixed
Mixed White/Asian 69 5,281 82 5,024
Mixed White/Black African 64 2,970 78 2,807
Mixed White/Black Caribbean 61 4,913 77 4,901
Mixed other 66 8,186 79 7,603
White
White British 66 209,870 79 199,805
White Irish 67 774 81 777
Gypsy/Roma 27 1,070 41 1,081
Irish Traveller 31 330 47 335
White other 59 23,296 73 22,065
Other 56 6,159 70 5,889

Download table data for ‘By ethnicity and gender’ (CSV) Source data for ‘By ethnicity and gender’ (CSV)

Summary of Development goals for 4 to 5 year olds By ethnicity and gender Summary

This data shows that, in the 2018 to 2019 school year:

  • 78% of girls and 64% of boys met the expected standard in development
  • in every ethnic group, girls were more likely than boys to meet the expected standard
  • girls from the Indian ethnic group were the most likely to meet the expected standard (84%)
  • Gypsy/Roma boys were the least likely to (27%)
  • the biggest gap between girls and boys was in the Black African ethnic group, where 77% of girls and 60% of boys met the standard
  • the smallest gap between girls and boys was in the Chinese ethnic group, where 81% of girls and 72% of boys met the standard
  • among White British pupils, 79% of girls and 66% of boys met the expected standard

6. By ethnicity, gender and eligibility for free school meals

Percentage of 4 to 5 year olds who met the expected standard in development by ethnicity, gender and eligibility for free school meals (FSM)
Boys Girls
Ethnicity Boys FSM Boys Non- FSM Girls FSM Girls Non- FSM
All 47 67 63 80
Asian 53 64 70 78
Bangladeshi 53 61 72 76
Indian 59 72 73 84
Pakistani 52 58 69 73
Asian other 50 63 67 78
Black 55 61 71 78
Black African 55 61 72 78
Black Caribbean 53 63 69 78
Black other 54 59 68 76
Chinese 67 73 66 82
Mixed 52 69 68 82
Mixed White/Asian 52 72 67 84
Mixed White/Black African 54 66 67 81
Mixed White/Black Caribbean 51 65 67 81
Mixed other 53 69 69 82
White 45 68 61 81
White British 45 70 62 82
White Irish 33 72 68 83
Gypsy/Roma 27 26 38 43
Irish Traveller 21 40 38 53
White other 47 60 63 73
Other 49 58 63 72

Download table data for ‘By ethnicity, gender and eligibility for free school meals’ (CSV) Source data for ‘By ethnicity, gender and eligibility for free school meals’ (CSV)

Summary of Development goals for 4 to 5 year olds By ethnicity, gender and eligibility for free school meals Summary

Eligibility for free school meals (FSM) is used as an indicator of deprivation by the Department for Education.

This data shows that:

  • 63% of FSM-eligible girls and 47% of boys met the expected standard, compared with 80% of non-FSM girls and 67% of boys
  • in every ethnic group, FSM-eligible girls were less likely to meet the expected standard than non-FSM girls
  • in every ethnic group except Gypsy and Roma, FSM-eligible boys were less likely to meet the expected standard than non-FSM boys
  • in every ethnic group except Chinese, FSM-eligible girls were more likely than FSM-eligible boys to meet the standard
  • among FSM-eligible pupils, girls from the Indian ethnic group were the most likely to meet the expected standard (73%)
  • White Irish Traveller FSM-eligible boys were the least likely to meet the expected standard (21%)
  • the White Irish ethnic group had the biggest gap between FSM-eligible girls (68%) and boys (33%), at 35 percentage points
  • the White Irish ethnic group also had the biggest gap between FSM-eligible boys (33%) and non-FSM boys (72%), at 39 percentage points
  • the White British ethnic group had the biggest gap between FSM-eligible girls (62%) and non-FSM girls (82%), at 20 percentage points

7. By ethnicity, gender and area

Percentage of 4 to 5 year olds who met the expected standard in development, by ethnicity, gender and local authority
All Asian Black Chinese Mixed White
Local Authority All Girls All Boys Asian Girls Asian Boys Black Girls Black Boys Chinese Girls Chinese Boys Mixed Girls Mixed Boys White Girls White Boys
Barking and Dagenham 78 62 77 65 80 66 100 50 81 60 78 60
Barnet 80 67 83 70 78 66 89 72 83 66 82 70
Barnsley 78 60 50 75 89 78 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 90 66 78 60
Bath and North East Somerset 78 68 67 67 67 withheld because a small sample size makes it unreliable 50 withheld because a small sample size makes it unreliable 75 61 79 69
Bedford Borough 75 61 70 57 76 55 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 77 63 75 63
Bexley 82 69 84 68 80 69 88 87 85 70 82 70
Birmingham 74 59 75 59 75 58 70 79 76 62 74 60
Blackburn with Darwen 75 58 78 57 71 78 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 76 50 74 60
Blackpool 73 61 56 39 100 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 76 88 73 61
Bolton 74 57 76 57 69 45 71 60 73 64 76 59
Bournemouth Christchurch and Poole 81 66 83 73 94 56 withheld because a small sample size makes it unreliable 100 76 64 83 67
Bracknell Forest 82 70 81 67 81 75 withheld because a small sample size makes it unreliable 63 92 68 82 71
Bradford 74 60 73 58 66 57 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 76 58 75 62
Brent 77 65 81 72 74 62 83 withheld because a small sample size makes it unreliable 85 66 80 66
Brighton and Hove 77 66 58 67 68 61 75 29 82 69 79 66
Bristol City of 76 63 75 55 66 51 100 70 78 65 79 65
Bromley 84 71 87 75 78 55 93 85 85 73 86 73
Buckinghamshire 80 67 71 60 73 55 70 75 82 69 83 69
Bury 77 65 79 50 71 44 withheld because a small sample size makes it unreliable 75 78 62 78 68
Calderdale 77 61 68 49 57 55 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 82 68 80 65
Cambridgeshire 77 63 76 57 73 57 80 73 79 67 78 63
Camden 80 65 80 66 76 62 86 withheld because a small sample size makes it unreliable 85 70 80 66
Central Bedfordshire 79 65 79 65 70 49 100 89 81 55 79 66
Cheshire East 78 65 81 64 69 47 withheld because a small sample size makes it unreliable 60 69 68 79 66
Cheshire West and Chester 78 64 81 69 75 46 withheld because a small sample size makes it unreliable 20 76 64 78 64
City of London 95 78 100 78 N/A* N/A* N/A* N/A* withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 100 83
Cornwall 77 61 73 36 100 withheld because a small sample size makes it unreliable 60 67 83 75 77 61
Coventry 74 63 78 65 76 63 91 75 71 67 74 63
Croydon 79 68 79 69 79 64 100 100 82 71 79 70
Cumbria 77 62 53 60 withheld because a small sample size makes it unreliable 67 withheld because a small sample size makes it unreliable 67 63 69 78 62
Darlington 77 64 78 48 100 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable N/A* 67 57 77 65
Derby 77 62 80 67 77 59 50 89 85 63 77 62
Derbyshire 76 62 66 58 71 50 67 90 76 58 77 63
Devon 78 66 65 75 100 71 67 33 75 67 79 67
Doncaster 78 64 81 67 70 48 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 80 70 79 65
Dorset 77 65 63 41 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 83 63 78 66
Dudley 73 57 69 51 73 64 withheld because a small sample size makes it unreliable 63 74 57 75 57
Durham 78 64 61 73 75 71 withheld because a small sample size makes it unreliable 100 86 56 78 64
Ealing 77 64 81 67 76 58 86 67 84 62 78 69
East Riding of Yorkshire 81 66 71 40 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable N/A* N/A* 79 59 81 66
East Sussex 83 68 84 62 68 42 withheld because a small sample size makes it unreliable 88 84 69 83 69
Enfield 76 62 86 75 74 57 80 75 78 74 76 60
Essex 80 67 82 65 73 60 76 84 80 67 80 68
Gateshead 79 66 72 75 62 58 69 70 72 77 80 66
Gloucestershire 78 64 67 48 56 56 75 56 76 67 79 65
Greenwich 84 72 88 68 83 69 90 86 88 76 83 73
Hackney 76 61 86 74 80 62 100 86 83 70 82 75
Halton 75 56 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable N/A* N/A* 85 52 75 57
Hammersmith and Fulham 80 65 86 58 75 55 100 withheld because a small sample size makes it unreliable 70 66 83 72
Hampshire 83 70 85 64 79 65 74 79 80 67 83 71
Haringey 81 67 86 66 78 60 93 60 81 74 83 71
Harrow 80 68 83 72 74 54 69 withheld because a small sample size makes it unreliable 83 71 79 67
Hartlepool 79 64 73 60 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable N/A* 100 64 79 64
Havering 78 64 83 65 77 59 70 86 80 72 78 64
Herefordshire 80 71 77 57 N/A* withheld because a small sample size makes it unreliable N/A* withheld because a small sample size makes it unreliable 89 77 81 72
Hertfordshire 78 66 73 64 73 55 76 79 79 64 80 67
Hillingdon 80 68 85 72 80 67 75 100 83 74 78 65
Hounslow 78 67 84 69 72 66 75 88 80 73 76 65
Isle of Wight 76 64 withheld because a small sample size makes it unreliable 33 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 100 61 76 64
Isles of Scilly 73 85 N/A* N/A* N/A* N/A* N/A* N/A* N/A* withheld because a small sample size makes it unreliable 73 92
Islington 76 61 80 52 68 54 80 71 82 69 78 61
Kensington and Chelsea 76 61 60 60 71 53 100 N/A* 84 67 81 69
Kent 80 67 88 67 83 64 93 62 84 69 80 68
Kingston Upon Hull City of 71 56 76 71 74 53 withheld because a small sample size makes it unreliable N/A* 75 58 72 57
Kingston upon Thames 83 68 80 61 89 63 84 83 84 64 83 73
Kirklees 76 62 72 58 66 57 withheld because a small sample size makes it unreliable 67 72 63 79 65
Knowsley 74 58 100 82 50 33 withheld because a small sample size makes it unreliable N/A* 64 58 75 58
Lambeth 76 65 59 61 73 58 100 60 78 60 82 72
Lancashire 74 60 64 49 69 57 64 75 77 62 76 62
Leeds 73 59 69 54 64 54 100 71 73 58 75 61
Leicester 72 60 79 64 66 57 62 67 74 61 69 57
Leicestershire 78 64 81 62 88 49 91 72 78 62 78 65
Lewisham 82 70 83 67 78 63 87 71 83 71 86 78
Lincludingolnshire 76 62 80 67 75 60 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 72 66 77 62
Liverpool 71 57 70 52 68 52 84 47 73 51 72 59
Luton 75 60 76 60 80 66 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 75 63 74 59
Manchester 72 57 71 58 74 60 58 60 75 59 74 58
Medway 78 67 69 71 81 64 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 77 76 79 67
Merton 81 69 80 65 77 68 92 83 89 67 82 72
Middlesbrough 67 56 63 61 76 70 60 40 56 59 70 55
Milton Keynes 80 66 84 76 75 57 100 71 86 67 79 66
Newcastle upon Tyne 76 64 71 62 70 51 81 92 76 73 78 65
Newham 81 68 82 71 82 62 80 89 87 71 83 65
Norfolk 79 65 71 62 90 63 100 79 82 75 79 65
North East Lincludingolnshire 78 63 100 20 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 82 66 78 63
North Lincludingolnshire 77 64 75 65 withheld because a small sample size makes it unreliable 44 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 71 67 78 65
North Somerset 80 69 78 44 80 75 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 77 70 80 69
North Tyneside 77 66 89 55 80 50 40 88 74 68 77 66
North Yorkshire 79 65 63 48 71 72 withheld because a small sample size makes it unreliable 33 83 69 79 66
Northamptonshire 76 63 75 67 84 61 88 60 75 59 77 64
Northumberland 82 67 82 50 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 70 69 82 68
Nottingham 73 57 74 59 79 60 90 63 72 61 73 56
Nottinghamshire 77 63 68 58 65 69 74 52 79 57 78 64
Oldham 74 58 68 52 82 55 50 60 78 55 78 63
Oxfordshire 80 66 74 59 78 49 75 82 81 63 81 68
Peterborough 72 58 69 53 73 55 90 57 87 59 72 59
Plymouth 74 62 78 63 94 67 withheld because a small sample size makes it unreliable 40 73 66 74 63
Portsmouth 75 63 70 50 73 64 88 78 78 67 77 63
Reading 74 60 81 61 68 53 90 80 81 64 73 64
Redbridge 81 69 85 72 77 64 83 85 84 74 76 65
Redcar and Cleveland 75 64 withheld because a small sample size makes it unreliable 86 N/A* withheld because a small sample size makes it unreliable N/A* withheld because a small sample size makes it unreliable 68 82 76 64
Richmond upon Thames 85 76 84 72 77 47 93 86 85 76 88 77
Rochdale 71 57 67 56 65 53 67 86 81 46 73 61
Rotherham 77 61 75 57 92 40 82 80 74 59 77 63
Rutland 81 75 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable N/A* N/A* 67 100 82 75
Salford 74 58 71 62 75 49 100 withheld because a small sample size makes it unreliable 78 55 77 62
Sandwell 72 58 73 63 74 57 100 59 75 60 73 57
Sefton 75 61 64 36 80 25 86 40 69 77 76 61
Sheffield 76 63 76 60 74 63 75 81 76 59 79 65
Shropshire 80 65 71 50 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 91 81 80 65
Slough 80 66 85 70 85 63 N/A* withheld because a small sample size makes it unreliable 79 69 74 63
Solihull 76 65 83 66 58 39 80 70 74 53 76 67
Somerset 78 64 86 55 86 44 withheld because a small sample size makes it unreliable 67 72 66 79 65
South Gloucestershire 82 70 78 72 95 50 100 67 83 62 83 71
South Tyneside 81 65 75 54 67 17 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 71 67 81 66
Southampton 79 62 77 63 91 59 89 75 85 63 79 63
Southend-on-Sea 79 68 74 56 77 59 100 80 77 74 80 69
Southwark 80 67 88 57 79 61 71 83 83 74 85 72
St. Helens 76 61 40 56 57 75 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 67 71 77 61
Staffordshire 80 67 76 61 73 59 79 71 78 69 81 67
Stockport 75 64 71 55 64 40 82 42 70 56 76 66
Stockton-on-Tees 80 67 75 54 92 61 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 73 71 81 68
Stoke-on-Trent 73 58 71 52 71 58 79 20 70 57 75 61
Suffolk 78 61 82 47 77 46 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 78 61 79 62
Sunderland 80 65 77 55 83 46 withheld because a small sample size makes it unreliable 67 66 66 81 65
Surrey 84 72 82 67 81 60 97 83 86 75 85 72
Sutton 79 65 78 73 75 58 81 82 79 62 80 64
Swindon 76 64 80 66 87 57 83 67 81 61 75 65
Tameside 75 56 66 47 66 31 67 67 75 57 77 59
Telford and Wrekin 76 63 63 57 85 55 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 83 71 76 64
Thurrock 79 65 82 58 84 69 57 withheld because a small sample size makes it unreliable 79 75 79 65
Torbay 77 63 63 20 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 78 82 78 64
Tower Hamlets 77 61 77 60 81 64 86 61 78 60 78 60
Trafford 81 68 77 59 69 52 85 72 76 62 84 72
Wakefield 78 62 69 53 69 46 71 withheld because a small sample size makes it unreliable 84 59 79 63
Walsall 74 57 74 58 77 50 89 withheld because a small sample size makes it unreliable 75 55 75 58
Waltham Forest 80 71 79 69 78 64 100 56 84 77 83 75
Wandsworth 82 70 83 63 71 62 100 57 78 67 86 77
Warrington 79 67 69 65 62 67 88 50 75 67 80 67
Warwickshire 79 64 81 66 74 50 100 88 80 63 79 64
West Berkshire 80 69 94 67 67 64 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 80 71 80 69
West Sussex 78 64 70 59 65 57 55 53 80 67 79 65
Westminster 77 63 80 74 86 55 89 80 79 58 80 72
Wigan 74 60 59 44 69 47 78 withheld because a small sample size makes it unreliable 75 61 74 60
Wiltshire 78 65 87 57 70 63 80 withheld because a small sample size makes it unreliable 77 58 79 66
Windsor and Maidenhead 78 70 74 63 83 88 withheld because a small sample size makes it unreliable N/A* 84 63 79 74
Wirral 74 61 60 58 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 40 73 84 65 75 61
Wokingham 81 71 84 73 79 76 86 88 84 72 82 70
Wolverhampton 73 61 74 62 73 56 80 70 75 66 73 61
Worcestershire 77 65 73 59 71 50 80 80 75 70 78 66
York 79 69 54 56 83 86 withheld because a small sample size makes it unreliable 83 72 64 81 70

Download table data for ‘By ethnicity, gender and area’ (CSV) Source data for ‘By ethnicity, gender and area’ (CSV)

Summary of Development goals for 4 to 5 year olds By ethnicity, gender and area Summary

Figures for the Asian, Black and Chinese ethnic groups are based on small numbers of pupils. Because of this, they're more likely to change from year to year.

The summary below only includes figures based on enough pupils to make reliable generalisations.

This data shows that:

  • girls were more likely to meet the expected standard than boys in every local authority apart from Isles of Scilly
  • among Asian pupils, girls were more likely than boys to meet the expected standard in 134 out of 146 local authorities where data was available
  • the biggest gap was in North East Lincolnshire, where 100% of Asian girls and 20% of Asian boys met the standard
  • among Black pupils, girls were more likely than boys to meet the expected standard in 122 out of 130 local authorities where data was available
  • the biggest gap was in Sefton, where 80% of Black girls and 25% of Black boys met the standard
  • among pupils from the Chinese ethnic group, girls were more likely than boys to meet the expected standard in 57 out of 87 local authorities where data was available
  • the biggest gap was in Stoke-on-Trent, where 79% of girls and 20% of boys from the Chinese ethnic group met the standard
  • among pupils with Mixed ethnicity, girls were more likely than boys to meet the expected standard in 139 out of 149 local authorities where data was available
  • the biggest gap was in Isle of Wight, where 100% of girls and 61% of boys with Mixed ethnicity met the standard
  • among White pupils, girls were more likely than boys to meet the expected standard in all local authorities except the Isles of Scilly
  • the biggest gap between White girls and boys (18 percentage points) was found in 7 local authorities: Halton, Tameside, Barnsley, Dudley, Newham, Tower Hamlets and Barking and Dagenham

8. Methodology

The early years foundation stage profile is an assessment by teachers of their pupils’ development. Teachers assess their pupils at the end of the school year in which the children turn 5 years old.

The dataset is a statutory annual collection of data from all local authorities in England, which runs from June to the beginning of September.

The dataset for the 2018 to 2019 school year includes valid results for 638,946 pupils.

Ethnicity isn’t collected as part of the early years foundation stage profile. So early years data is matched to data on the national pupil database to get information broken down by ethnic group.

Ethnicity data on the national pupil database comes from the school census.

There were some discrepancies between the 2 sets of data. Of the 638,995 pupils with valid early years results, 638,946 were found in the national pupil database.

Of these 638,946 pupils, ethnicity was not found for 22,487 pupils (4%).

Free school meals (FSM):

Pupils are included in the figures for free school meals if their families claimed eligibility for FSM at the time of the annual spring school census. This definition includes all pupils who were eligible to receive free school meals, not only those who actually received free school meals.

Pupils not eligible for free school meals or unclassified pupils are described as ‘Non-FSM’ or ‘All other pupils’.

Parents are able to claim FSM if they receive a qualifying benefit like Jobseeker’s Allowance.

FSM is used as an indicator of disadvantage. Not all eligible parents apply for FSM, and families who don’t quite reach the eligibility threshold for FSM may still be suffering deprivation.

There were 89,742 pupils eligible for FSM in early years foundation stage (14% of all pupils).

Rounding

Percentages are rounded to the nearest whole number.

Related publications

Statistics: early years foundation stage profile – includes previous years' data.

Quality and methodology information

9. Data sources

Source

Type of data

Administrative data

Type of statistic

National Statistics

Publisher

Department for Education

Note on corrections or updates

A revised version of the data, which added breakdowns for pupil characteristics, has been used. The original publication was released on 17/10/2019.

Publication frequency

Yearly

Purpose of data source

The early years foundation stage profile aims to:

  • support pupils' transition to key stage 1 (which they take from 5 to 7 years old)
  • help teachers to plan an effective, responsive and appropriate curriculum for all pupils
  • inform parents and carers about their child’s development against early learning goals

10. Download the data

Early Learning Goals 2019 -- Local Authority - Spreadsheet (csv) 577 KB

This file contains the following: measure, time, time_type, ethnicity, ethnicity_type, geography, geography_type, geography_name, gender, gender_type, value, denominator, value note and geography name

Early Learning Goals 2019 -- National - Spreadsheet (csv) 30 KB

This file contains the following: measure, time, time type, ethnicity, gender, FSM eligible, percentage value, denominator