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How Do Newly Promoted Clubs Survive In The EPL?

Part 2: The Four Survival KPIs

The first part of this two-part consideration of the prospects of newly promoted clubs surviving in the English Premier League (EPL) concluded that the lower survival rate in recent seasons was due to poorer defensive records rather than any systematic reduction in wage expenditure relative to other EPL clubs. It was also suggested that there might be a Moneyball-type inefficiency with newly promoted teams possibly allocating too large a proportion of their wage budget to over-valued strikers when more priority should be given to improving defensive effectiveness. In this post, the focus is on identifying four key performance indicators (KPIs) for newly promoted clubs that I will call the “survival KPIs”. These survival KPIs are then combined using a logistic regression model to determine the current survival probabilities of Burnley, Leeds United and Sunderland in the EPL this season.

The Four Survival KPIs

The four survival KPIs are based on four requirements for a newly promoted club:

Squad quality measured as wage expenditure relative to the EPL median
Impetus created by a strong start to the season measured by points per game in the first half of the season
Attacking effectiveness measured by goals scored per game
Defensive effectiveness measured by goals conceded per game

Using data on the 89 newly promoted clubs in the EPL from seasons 1995/96 – 2024/25, these clubs have been allocated to four quartiles for each survival KPI. Table 1 sets out the range of values for each quartile, with Q1 as the quartile most likely to survive through to Q4 as the quartile most likely to be relegated. Table 2 reports the relegation probabilities for each quartile for each KPI. So, for example, as regards squad quality, Table 1 shows that the top quartile (Q1) of newly promoted clubs had wage costs at least 79.5% of the EPL median that season. Table 2 shows that only 22.7% of these clubs were relegated. In contrast, the clubs in the lowest quartile (Q4) had wage costs less than 55% of the EPL median that season and 77.3% of these clubs were relegated.

Table 1: Survival KPIs, Newly Promoted Clubs in the EPL, 1995/96 – 2024/25

Table 2: Relegation Probabilities, Newly Promoted Clubs in the EPL, 1995/96 – 2024/25

The standout result is the low relegation probability for newly promoted clubs in Q1 for the Impetus KPI. Only 8% of newly promoted clubs with an average of 1.21 points per game or better in the first half of the season have been relegated. This equates to 23+ points after 19 games. Only 17 newly promoted clubs have achieved 23+ points by mid-season in the 30 seasons since 1995 and only two have done so in the last five seasons – Fulham in 2022/23 with 31 points and the Bielsa-led Leeds United with 26 points in 2020/21.

It should be noted that there is little difference in the relegation probabilities between Q2 and Q3, the mid-range values for both Squad Quality and Attacking Effectiveness, suggesting that marginal improvements in both of these KPIs have little impact for most clubs. As regards defensive effectiveness, both Q1 and Q2 have low relegation quartiles suggesting that the crucial benchmark is limiting goals conceded to under 1.61 goals per game (or 62 goals conceded over the entire season). Of the 43 newly promoted clubs that have done so since 1995, only seven have been relegated, a relegation probability of 16.3%. Reinforcing the main conclusion from the previous post that the main reason that for the poor performance of newly promoted clubs in recent seasons, only four clubs have conceded fewer than 62 goals in the last five seasons – Fulham (53 goals conceded, 2020/21), Leeds United (54 goals conceded, 2020/21); Brentford (56 goals conceded, 2021/22) and Fulham (53 goals conceded, 2022/23) – with of these four clubs, only Fulham being relegated in 2020/21 (primarily due to their poor attacking effectiveness).

Where Did The Newly Promoted Clubs Go Wrong Last Season?

Just as in the previous season 2023/24, so too last season, all three newly promoted clubs – Ipswich Town, Leicester City and Southampton – were relegated. Table 3 reports the survival KPIs for these clubs. In the case of Ipswich Town, their Squad Quality was low with relative expenditure under 50% of the EPL median. In contrast Leicester City spent close to the EPL median and Southampton were just marginally under the Q1 threshold. The Achilles Heel for all three clubs was their very poor defensive effectiveness, conceding goals at a rate of over two goals per game. Only 11 newly promoted clubs have conceded 80+ goals since 1995; all have been relegated.

Table 3: Survival KPIs, Newly Promoted Clubs in the EPL, 2024/25

*Calculated using estimated squad salary costs sourced from Capology (www.capology.com)

What About This Season?

As I write, seven rounds of games have been completed in the EPL. Of the three newly promoted clubs, the most impressive start has been by Sunderland who are currently 9^th in the EPL with 11 points which puts them in Q1 in terms of Impetus as does their Squad Quality with wage expenditure estimated at 83% of the EPL median, and their defensive effectiveness with only six goals conceded in their first seven games. Leeds United have also made a solid if somewhat less spectacular start with 8 points and ranking in Q2 for all four survival KPIs. Both Sunderland and Leeds United are better placed at this stage of the season than all three newly promoted clubs last season when Leicester City had 6 points, Ipswich Town 4 points and Southampton 1 point. Burnley have made the poorest start of the newly promoted clubs this season with only 4 points, matching Ipswich Town’s start last season but, unlike Ipswich Town, Burnley rank Q2 in both Squad Quality and Attack. Worryingly Burnley’s defensive effectiveness which was so crucial to their promotion from the Championship has been poor so far this season and, at over two goals conceded per game, on a par with Ipswich Town, Leicester City and Southampton last season.

Table 4: Survival KPIs and Survival Probabilities, Newly Promoted Clubs in the EPL, 2025/26, After Round 7

*Calculated using estimated squad salary costs sourced from Capology (www.capology.com)

Using the survival KPIs for all 86 newly promoted clubs 1995 – 2024, a logistic regression model has been estimated for the survival probabilities of newly promoted clubs in the EPL. This model combines the four survival KPIs and weights their relative importance based on their ability to jointly identify correctly those newly promoted clubs that will survival. The model has a success rate of 82.6% predicting which newly promoted clubs will survive and which will be relegated. Based on the first seven games, Sunderland have a survival probability of 99.9%, Leeds United 72.9% and Burnley 1.6%. These figures are extreme and merely highlight that Sunderland have made an exceptional start, Leeds United a good start and Burnley have struggled defensively. It is still early days and crucially the survival probabilities do not control for the quality of the opposition. Sunderland have yet to play a team in the top five whereas Leeds United and Burnley have both played three teams in the top five. I will update these survival probabilities regularly as the season progresses. They are likely to be quite volatile in the coming weeks but should become more stable and robust by late December.

How Do Newly Promoted Clubs Survive In The EPL? Part One: What Do The Numbers Say?

The English Premier League (EPL) started its 34^th season last weekend with most of the pundits focusing on the top of the table and whether Arne Slot’s Liverpool can retain the title in the face of a rejuvenated challenge by Pep Guardiola’s Manchester City. Relatively little attention has been given to the chances of the newly promoted clubs – Leeds United, Burnley and Sunderland – avoiding relegation with most pundits tipping all three to follow their predecessors in the last two seasons in being immediately relegated back to the Championship. The opening weekend of the EPL season went somewhat against the doom merchants with two of the three newly promoted clubs, Sunderland and Leeds United, winning. This is the first time that two newly promoted clubs have won their first game since Brentford and Watford in 2021/22 with the only other instance of this rare feat being Bolton Wanderers and Crystal Palace in 1997/98 although it should be noted that only Brentford then went on to avoid relegation. I must of course in the interests of objectivity declare my allegiances – I have lived and worked in Leeds for over 40 years and, as a Scot growing up in the 1960s, my “English” team was always Leeds United, then packed with Scottish internationals with Billy Bremner and Eddie Gray my particular favourites. So with Leeds United returning to the EPL after two seasons in the Championship, what are the chances that Leeds United and the other two promoted clubs can defy conventional wisdom and avoid relegation? What do the numbers say?

The Dataset

The dataset used in the analysis covers 30 years of the EPL from season 1995/96 to season 2025/26. The analysis has begun in 1995/96 which was the first season that the EPL adopted its current structure of 20 clubs with three clubs relegated. Note that there were only two teams promoted from the Championship in 1995/96. League performance has been measured by Wins, Draws, Losses, Goals For, Goals Against and League Points. In order to focus on sporting performance, League Points are calculated solely on the basis of games won and drawn, and exclude any points deductions for regulatory breaches. There is no case of any club being relegated solely because of regulatory breaches. Survival Rate is defined as the percentage of newly promoted clubs that were not relegated in their first season in the EPL. Relative Wages has been calculated as the total wage expenditure of clubs as reported in their company accounts relative to the median wage expenditure of all EPL clubs that season (indexed such that 100 = median wage expenditure). This allows comparisons to be drawn across seasons despite the underlying upward trend in wage expenditure. Company accounts are not yet available for 2024/25 so there is no analysis of wage expenditure and sporting efficiency in the most recent EPL season. Total wage expenditure includes all wage expenditure not just player wages. Estimates of individual player wages and total squad costs are available but their accuracy is unknown and limited to recent seasons only. A comparison of one such set of estimated squad wage costs and the wage expenditures reported in company accounts for the period 2014 – 2024 yielded a correlation coefficient of 0.933 which suggests that the “official” wage expenditures provide a very good proxy for player wage costs. Sporting Efficiency is defined as League Points divided by Relative Wages (and multiplied by 100). Sporting Efficiency is a standardised measured of league points per unit of wage expenditure across seasons that attempts to capture the ability of clubs to transform financial expenditure into sporting performance which, when all is said and done, is the fundamental transformation in professional team sports and at the heart of the Moneyball story as to how teams can attempt to offset limited financial resources by greater sporting efficiency.

League Performance of Newly Promoted Clubs

Table 1 summarises the average league performance of newly promoted clubs over the last 30 seasons of the EPL, broken down into 5-year sub-periods in order to detect any long-term trends over time. In addition, the proposition that the average league performance has deteriorated in the last five seasons compared to the previous 25 seasons has been formally tested statistically using a t-test with instances of strong evidence (i.e. statistical significance) of this deterioration indicated by asterisks (or a question mark when is marginally weaker). The key points to emerge are:

There is no clear trend in wins, draws and losses by newly promoted clubs between 1995/96 and 2019/20 but thereafter there is strong evidence that newly promoted clubs are winning and drawing fewer games and, by implication, losing more games.
Newly promoted clubs averaged 4 more losses since 2020 compared to previous seasons with an average of 22.5 losses in the last five seasons as opposed to an average of 18.7 losses in previous 25 seasons.
The poorer league performance in recent seasons represents a reduction in average league points from 39.0 (1995/96 – 2019/20) to 30.5 points (2020/21 – 2024/25).
Given that the acknowledged benchmark to avoid relegation is 40 points, not surprisingly the survival rate of newly promoted clubs has declined in the last five seasons to only a one-in-three chance of survival (33.3%) compared to a slightly better than one-in-two chance (56.8%) in the previous 25 seasons.
The data suggests strongly that the primary reason for the decline in league performance and survival rates of newly promoted clubs in the last five seasons has been weaker defensive play, not weaker attacking play. Newly promoted clubs averaged 61.1 goals against in seasons 1995/96 – 2019/20 but this rose to 73.8 goals against in the last five seasons which represents very strong evidence of a systematic change in the defensive effectiveness of newly promoted clubs. In stark contrast, the change in goals for has been negligible with a decline from 40.5 (1995/96 – 2019/20) to 38.8 (2020/21 – 2024/25) which is more likely to be accounted for by season-to-season fluctuation rather than any underlying systematic decline in attacking effectiveness.

Wage Costs and Sporting Efficiency of Newly Promoted Clubs

It has been frequently argued that the recent decline in the league performance and survival rates of newly promoted clubs is due to an increasing gap in financial resources between established EPL clubs and the newly promoted clubs. Table 2 addresses this issue. There is absolutely no support for newly promoted clubs being more financially disadvantaged relatively compared to their predecessors. There has been virtually no change in the relative wage expenditure of newly promoted clubs in the last five seasons which has averaged 67.1 compared to 66.3 in the previous 25 seasons. The lower survival rate in recent seasons is NOT due to newly promoted clubs spending proportionately less on playing talent.

There is a very simply equation that holds by definition:

League Performance = Relative Wages X Sporting Efficiency

Since their league performance has declined but the relative wage expenditure of newly promoted clubs has stayed more or less constant, then their sporting efficiency MUST have declined. Table 2 suggests that there may have been a downward trend in the sporting efficiency in newly promoted clubs in the last 15 seasons. In addition, there is strong evidence that there has been a systematic downward shift in the sporting efficiency in the last five seasons to 51.4 compared to the previous average of 63.2 (1995/96 – 2019/20). On its own, this is merely a statement of the obvious dressed up in mathematical and statistical formalism. Newly promoted clubs are performing worse on the pitch as a result of spending less effectively. The crucial question is why league performance and sporting efficiency have declined. The answer may lie in reflecting on the fact that, as we discovered in Table 1, the reason for the poorer league performance is primarily due to poorer defensive effectiveness not poorer attacking effectiveness. Newly promoted clubs seem to be buying the same number of goals scored with the same relative wage budget as in previous seasons but at the cost of buying less defensive effectiveness and conceding more goals. This is consistent with a Moneyball-type distortion in the EPL player market with a premium paid for strikers that may not be fully warranted by current tactical developments in the game. The numbers would support newly promoted clubs giving a higher priority to defensive effectiveness in their recruitment and retention policy and avoiding spending excessively on expensive strikers, particularly those with little experience of playing and scoring in the top leagues.

Competitive Balance Part 3: North American Major Leagues

As discussed in the two previous posts on competitive balance, there is no agreed single definition of competitive balance beyond a general statement that a competitively balanced league is characterised by all teams having a relatively equal chance of winning individual games and the league championship. The lack of agreement on a specific definition of competitive balance combined with the wide variety of league structures and the statistical problems of inferring ex ante (i.e. pre-event) success probabilities from ex post (i.e. actual) league outcomes has led to a multiplicity of competitive balance metrics. Morten Kringstad and I have argued in several published journal articles and book chapters that it is useful to categorise competitive balance metrics as either measures of win dispersion or performance persistence. Win dispersion measures the dispersion in league performance across teams in a particular season. Performance persistence measures the degree to which the league performance of individual teams is replicated across seasons – do teams tend to finish in the same league position in consecutive seasons? These are two quite different aspects of competitive balance and multiple metrics have been proposed for both. However, when it comes to discussions as to what leagues should do, if anything, to maintain or improve of competitive balance, there is a general (often implicit) presumption that all competitive balance metrics tend to move in the same direction. Morten and I have sought to discover if this is indeed the case. And, as reported in my previous post on the subject, the evidence from European football is quite mixed and, at the very least, casts doubt on the general presumption that there is a strong positive relationship between win dispersion and persistence. Indeed, we found that in the period 2008 – 2017 win dispersion and performance persistence tended to move in opposite directions in the English Premier League.

In this post, I am going to discuss the evidence from a study on win dispersion and performance persistence in the four North American Major Leagues (NAMLs) that Morten and I published recently in Sport, Business, Management: An International Journal (vol 13 no. 5, 2023). Our dataset covered the four NAMLs – MLB (baseball), NFL (American football), NBA (basketball) and NHL (ice hockey) – seven different competitive balance metrics, and 60 seasons, 1960 – 2019 (thereby avoiding the impact of the Covid pandemic). In this post I am only focusing on the ASD* measure of win dispersion, the SRCC measure of performance persistence, and the correlation between these measures to test whether or not win dispersion and performance persistence move together in the same direction. I have reported these three measures as 10-year averages in order to identify possible trends over time. It is agreed that the ASD* metric provides better comparability of win dispersion between leagues with very different lengths of game schedules in the regular season. At one extreme the MLB has a 162-game schedule whereas for most of the period the NFL had a 16-game regular season schedule (recently increased to 17 games). The ASD* uses the actual standard deviation of team win percentages relative to the theoretical standard deviation of a perfectly dominated league with the same number of teams and games in which every team loses against the teams ranked above it so the top team wins every game, the second best team only loses against the top team, the 3^rd-placed team only loses against the top two and so on. (Formally, this is called a “cascade” distribution.) The SRCC measure of performance persistence is just the Spearman rank correlation coefficient of league standings in two consecutive seasons.

One important contextual change in most leagues since the 1960s has been the move away from a very restricted player labour market in which a player’s current team had priority in retaining a player. Instead player labour markets have become a very competitive auction-type market in which players have the right to move to another team at the end of their current contract (what is known as “free agency”). The NAML’s led the way in pro team sports in introducing some form of free agency in the 1970s/80s. European leagues lagged behind until the Bosman ruling in 1995 which effectively created free agency by abolishing transfer fees for out-of-contract players. So in some ways it should be expected that the general trend in the NAMLs has been towards greater competitive imbalance as the big-market teams have taken advantage of free agency to acquire the best players. However, there has been another general tendency with leagues becoming much more interventionist by introducing regulatory mechanisms especially salary caps which, in part, has been motivated by an attempt to offset the potential negative effect on competitive balance of free agency. Which effect has been stronger? Let’s look at the numbers.

Table 1 below reports the 10-year averages for win dispersion for the four NAMLs. Broadly speaking, the pattern in win dispersion in the NAMLs over the last 60 years has been for win dispersion to decrease from the 1960s though to the 1990s (i.e. improved competitive balance) but for win dispersion to increase since the 1990s (i.e. reduced competitive balance). Both the MLB and NFL follow this pattern, suggesting that the league intervention effect may have initially dominated the free agency effect but in recent years the resource-richer teams may have adapted to the more regulated environment and found other ways to exert their financial advantage (while remaining compliant with league regulations) such as higher expenditures on technology and data analytics. I used to argue that the Oakland A’s and the Moneyball phenomenon is an example of data analytics being used as a “David” strategy for resource-poorer teams to compete more effectively. And it is true that in the early days of sports analytics it was often the resource-poorer teams that led the way in operationalising data analytics as a source of competitive advantage. But these days most teams recognise the potential gains from analytics and some very resource-rich teams are investing heavily in data analytics.

The trends in win dispersion are much less clear in both the NBA and NHL. There has been some underlying trend from the 1960s onwards for competitive balance to worsen in the NBA as win dispersion has increased. In contrast, the NHL has tended to experience an improvement in competitive balance with lower win dispersion since the turn of the century.

When win dispersion across the four NAMLs are compared, there is a rather surprising result that the NFL has the highest degree of win dispersion over the whole period (i.e. low competitive balance) whereas the MLB has the lowest win dispersion (i.e. high competitive balance) with the NBA and NHL in the mid-range. I say surprising since conventional wisdom is that NFL has been one of the most proactive leagues in trying to maintain a high level of competitive balance whereas traditionally the MLB has been much less interventionist. The problem in making comparisons across leagues especially in different sports is the “apples-and-oranges” problem – trying to compare like with like. As highlighted earlier, there are massive differences between the NAMLs in the length of regular-season game schedules. I am more inclined to the view that the difference in win dispersion between the NAMLs is more a reflection of the difficulties in constructing a metric that properly controls for the length of game schedules, that is, it is more a measurement problem than a “true” reflection of differences in competitive balance.

The argument that win dispersion metrics can pick up trends within leagues but is less reliable for comparisons across leagues is reinforced by the results for performance persistence reported below in Table 2. Performance persistence measures the degree to which the final standings of teams are replicated in consecutive seasons. The length of game schedule has a much more indirect effect on performance persistence so that comparisons across leagues should be more reliable. And, indeed, we find that from the 1980s onwards the NFL has had the lowest degree of performance persistence which fits with the conventional view that the NFL has been the most proactive league in maintaining a high degree of competitive balance. Winning NFL teams face a number of “penalties” in the next season – tougher game schedules, lower-ranked draft picks and the constraints imposed by the salary cap in retaining free agents who have increased in value by virtue of their on-the-field success. It is more and more difficult for NFL teams to become “dynasty” teams which makes the Belichick-Brady era at the New England Patriots and, most recently, the success of the Kansas City Chiefs so remarkable.

As well as the NFL, the other NAML that has managed to reduce the degree of performance persistence is the NHL which had the highest degree of performance persistence in the 1960s and 1970s but now ranks second best behind the NFL. The MLB experienced reduced performance persistence in the 1980s and 1990s ( and had, on average, lower performance persistence than the NFL in the 1990s) but that downward trend has been reversed in the last two decades. The one major league that has had no discernible trend in performance persistence over the last 60 years and has the highest degree of performance persistence is the NBA despite instituting a salary cap albeit a rather “soft” cap with a number of exemptions. The high performance persistence of basketball teams is inherent in the very structure of the game. With only five players on court for a team at any point in time, basketball is much more susceptible to the “Michael Jordan” (i.e. “super-superstar”) effect and the soft salary cap makes it easier to retain these super-superstars.

The final set of results reported in Table 3 show how the relationship between win dispersion and performance persistence has varied over time and between leagues. One of the main motivations for this research is to determine whether or not the general presumption of a strong positive dispersion-persistence relationship is empirically valid. The evidence is mixed. There are only eight instances of a strong positive dispersion-persistence relationship (r > 0.5) out of a possible 24 which is hardly overwhelming evidence in favour of the general presumption. If medium-sized effects are included (0.3 < r < 0.5) then only half of the reported results provide support for the general presumption of a positive relationship with three strong/medium negative results and nine showing only small/negligible effects. There is one instance of a strong negative dispersion-persistence relationship in the NHL in 2010-19 indicating that reductions in performance persistence were associated with increases in win dispersion.

Competitive balance in the NAMLs has been much researched over the last 30 years. The results of our study are broadly in line with previous results but highlight that any conclusions are likely to be time-dependent and metric-dependent. The most definitive results are those on performance persistence which show a general tendency in both the NFL and NHL for improved competitive balance despite the advent of free agency. There is also clear evidence of continuing high levels of performance persistence in the NBA, likely to be due to the super-superstar effect inherent in the game structure of basketball. As for the general presumption that win dispersion and performance persistence tend to move together in the same direction, there is no overwhelming support that they do so in most cases. The practical implication is that leagues need to be clearer on which aspect of competitive balance is most important in driving uncertainty of outcome and spectator/viewer interest. Leagues must also recognise that the structures of their sports may limit the extent to which competitive balance can be regulated. Basketball is always likely to more susceptible to super-superstar effects that can lead to high levels of performance persistence. And leagues with short game schedules may always tend to have higher levels of win dispersion since there is more limited opportunity for winning or losing streaks to even themselves out – what statisticians call the “regression-to-the-mean” effect.

Other Related Posts

Competitive Balance Part 1: What Are The Issues?

Competitive Balance Part 2: European Football

Note: The results reported in this post are published in B. Gerrard and M. Kringstad, ‘Dispersion and persistence in the competitive balance of North American Major Leagues 1960 – 2019‘, Sport, Business, Management: An International Journal, vol. 13 no. 5 (2023), pp. 640-662.