{"version":"1.0","provider_name":"MRKT Insights - Football Consultancy Services","provider_url":"https:\/\/mrktinsights.com","title":"Spending your way to success - an investor's guide. - MRKT Insights - Football Consultancy Services","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"lHEI7llAka\"><a href=\"https:\/\/mrktinsights.com\/index.php\/2022\/06\/21\/spending-your-way-to-success-an-investors-guide\/\">Spending your way to success &#8211; an investor&#8217;s guide.<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/mrktinsights.com\/index.php\/2022\/06\/21\/spending-your-way-to-success-an-investors-guide\/embed\/#?secret=lHEI7llAka\" width=\"600\" height=\"338\" title=\"&#8220;Spending your way to success &#8211; an investor&#8217;s guide.&#8221; &#8212; MRKT Insights - Football Consultancy Services\" data-secret=\"lHEI7llAka\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/**\n * WordPress inline HTML embed\n *\n * @since 4.4.0\n * @output wp-includes\/js\/wp-embed.js\n *\n * Single line comments should not be used since they will break\n * the script when inlined in get_post_embed_html(), specifically\n * when the comments are not stripped out due to SCRIPT_DEBUG\n * being turned on.\n *\/\n(function ( window, document ) {\n\t'use strict';\n\n\t\/* Abort for ancient browsers. *\/\n\tif ( ! document.querySelector || ! window.addEventListener || typeof URL === 'undefined' ) {\n\t\treturn;\n\t}\n\n\t\/** @namespace wp *\/\n\twindow.wp = window.wp || {};\n\n\t\/* Abort if script was already executed. *\/\n\tif ( !! window.wp.receiveEmbedMessage ) {\n\t\treturn;\n\t}\n\n\t\/**\n\t * Receive embed message.\n\t *\n\t * @param {MessageEvent} e\n\t *\/\n\twindow.wp.receiveEmbedMessage = function( e ) {\n\t\tvar data = e.data;\n\n\t\t\/* Verify shape of message. *\/\n\t\tif (\n\t\t\t! ( data || data.secret || data.message || data.value ) ||\n\t\t\t\/[^a-zA-Z0-9]\/.test( data.secret )\n\t\t) {\n\t\t\treturn;\n\t\t}\n\n\t\tvar iframes = document.querySelectorAll( 'iframe[data-secret=\"' + data.secret + '\"]' ),\n\t\t\tblockquotes = document.querySelectorAll( 'blockquote[data-secret=\"' + data.secret + '\"]' ),\n\t\t\tallowedProtocols = new RegExp( '^https?:$', 'i' ),\n\t\t\ti, source, height, sourceURL, targetURL;\n\n\t\tfor ( i = 0; i < blockquotes.length; i++ ) {\n\t\t\tblockquotes[ i ].style.display = 'none';\n\t\t}\n\n\t\tfor ( i = 0; i < iframes.length; i++ ) {\n\t\t\tsource = iframes[ i ];\n\n\t\t\tif ( e.source !== source.contentWindow ) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\tsource.removeAttribute( 'style' );\n\n\t\t\tif ( 'height' === data.message ) {\n\t\t\t\t\/* Resize the iframe on request. *\/\n\t\t\t\theight = parseInt( data.value, 10 );\n\t\t\t\tif ( height > 1000 ) {\n\t\t\t\t\theight = 1000;\n\t\t\t\t} else if ( ~~height < 200 ) {\n\t\t\t\t\theight = 200;\n\t\t\t\t}\n\n\t\t\t\tsource.height = height;\n\t\t\t} else if ( 'link' === data.message ) {\n\t\t\t\t\/* Link to a specific URL on request. *\/\n\t\t\t\tsourceURL = new URL( source.getAttribute( 'src' ) );\n\t\t\t\ttargetURL = new URL( data.value );\n\n\t\t\t\tif (\n\t\t\t\t\tallowedProtocols.test( targetURL.protocol ) &&\n\t\t\t\t\ttargetURL.host === sourceURL.host &&\n\t\t\t\t\tdocument.activeElement === source\n\t\t\t\t) {\n\t\t\t\t\twindow.top.location.href = data.value;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t};\n\n\tfunction onLoad() {\n\t\tvar iframes = document.querySelectorAll( 'iframe.wp-embedded-content' ),\n\t\t\ti, source, secret;\n\n\t\tfor ( i = 0; i < iframes.length; i++ ) {\n\t\t\t\/** @var {IframeElement} *\/\n\t\t\tsource = iframes[ i ];\n\n\t\t\tsecret = source.getAttribute( 'data-secret' );\n\t\t\tif ( ! secret ) {\n\t\t\t\t\/* Add secret to iframe *\/\n\t\t\t\tsecret = Math.random().toString( 36 ).substring( 2, 12 );\n\t\t\t\tsource.src += '#?secret=' + secret;\n\t\t\t\tsource.setAttribute( 'data-secret', secret );\n\t\t\t}\n\n\t\t\t\/*\n\t\t\t * Let post embed window know that the parent is ready for receiving the height message, in case the iframe\n\t\t\t * loaded before wp-embed.js was loaded. When the ready message is received by the post embed window, the\n\t\t\t * window will then (re-)send the height message right away.\n\t\t\t *\/\n\t\t\tsource.contentWindow.postMessage( {\n\t\t\t\tmessage: 'ready',\n\t\t\t\tsecret: secret\n\t\t\t}, '*' );\n\t\t}\n\t}\n\n\twindow.addEventListener( 'message', window.wp.receiveEmbedMessage, false );\n\tdocument.addEventListener( 'DOMContentLoaded', onLoad, false );\n})( window, document );\n\/\/# sourceURL=https:\/\/mrktinsights.com\/wp-includes\/js\/wp-embed.js\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/mrktinsights.com\/wp-content\/uploads\/2022\/06\/Screenshot-2022-06-21-20.33.15.png","thumbnail_width":605,"thumbnail_height":404,"description":"By ANDREW WATSON How much do budgets really affect a league table? Often we hear stakeholders in the game, be they fans, owners, managers, say things such as &#8220;On our budget we should\u2026&#8221; or the famous &#8220;We have the smallest budget in the league.&#8221; This quote belonged to at least six Championship sides in 2021\/22 according to the media. Indeed, it is widely accepted that budget, transfer or wage, does have an impact on where a club can realistically expect to finish over the course of a season. The question is: How much of an impact does it have? The Difficulties With Financial Data Obviously this is a very difficult question to answer with any degree of certainty.&nbsp; The initial problem is that accurate financial data is difficult to come by, especially for all clubs in a league. Some may not enter accounts, if they do then they may not be full accounts. Even then the latest available accounts are often two years out of date. The data used is therefore imperfect. but when comparing the accounts of clubs who do publish full breakdowns and other sources (wage estimates of individual players) we can accurately estimate which clubs are the highest and the lowest paying within any given league.&nbsp; Building A Probability Model The next step is establishing a relationship between the financial data and the football. In this example we have used data from English League One. Accessing data for the football teams in this league is straightforward because of the availability of historic goals, xG and points. Data was gathered for seasons 2017\/18 up to 2021\/22. From this we were able to establish what relationship the wage budget had with the performance and results variables. Also at this stage we could produce an initial graph that demonstrated the general relationship between points won and wage budget. As we would expect there is indeed a positive correlation between wage budget and points won. However, what is clear is that a low budget in League One could mean anything in terms of points won. Some low budget teams had exceptional seasons, such as Shrewsbury Town&#8217;s 2017\/18 3rd place and Luton Town&#8217;s 2018\/19 title winning years. Equally, all of the desperately poor seasons in the last few years have come from clubs who are clearly struggling financially.&nbsp; On the graph it is possible to draw lines in to create a sector by which it is possible to identify the point at which a certain size of budget almost guarantees a degree of safety in League One, if not competitiveness. No club with a wage budget over \u00a3100k per week has won points at less than 1.2 points per game. However, a big budget is no guarantee of success. Indeed the four biggest estimated budgets in the sample all failed to achieve promotion. The highest points per game ratio in the sample was achieved by Chris Wilder&#8217; 2016\/17 Sheffield United, which is estimated at just under \u00a3100k per week budget. Calculating &#8220;best guess&#8221; probabilities Now that the relationships have been established we can take the coefficient of determination for goals for, goals against, xG and xGA to help us simulate a full season of League One. Taking Accrington as an example, their estimated budget is one of the lowest in the league. Therefore, as this model is solely concentrating on budget as the only variable of success, their performance and results should match up to around their budget stature. To do this we took Accrington\u2019s budget and found the difference between that and the average League One 22\/23 budget. Earlier we had calculated the average xG per match in League One to be 1.41, with an 11% causation to budget. Therefore we can then use the difference in budget as a variable to find an xG value for a team with Accrington\u2019s budget. In this case, 1.36xG per match. We can do the same with xGA (1.49), goals scored (1.24) and goals conceded (1.4). At the end of this we are in a position to give Accrington a budget-based rating that will be used in the simulations.&nbsp; When Accrington play a match there will be a number of goals they will be expected to score and a number they expect to concede. Those two numbers are estimated from the calculations above where xG and goals scored are put into a 65:35 ratio (xG has a better predictive value) and xGA and goals conceded are used in the same way. This gives Accrington final ratings of 1.32 goals and 1.46 against. This is just a base for the simulation to work with, but if a team ended up with these figures as an average for the season you may realistically expect a bottom half finish from this side. Single Season Simulation Once all the clubs are assigned goals for and against ratings then a fixture list is devised. The 24 teams all play each other twice to a total of 46 matches per club. In each of these matches a random number is assigned to each team based upon their respective ratings. Just as in real football, this means that just because a team has a higher rating that the other doesn\u2019t mean that they will automatically win that game. This is the element of randomness that we love about football, this time coded into the simulation via random numbers. If the gap between the generated numbers in a fixture is greater than 0.35 either way then a win is awarded. Below 0.35 difference is classed as a draw. All 46 league games for Accrington were simulated and in the initial season they won 51 points. That was good enough for 15th place in this first season, with MK Dons surprisingly finishing rock bottom with 39 points.&nbsp; Also relegated were new boys Exeter City (23rd) and Forest Green Rovers (21st), with lowest budget Cambridge United in 22nd. The league was won by Sheffield Wednesday on 85 points. Derby County bounced straight back"}